A Study on the Evaluation of Habitat Appropriateness of Huizhou Traditional Settlements

A Study on the Evaluation of Habitat Appropriateness of Huizhou Traditional Settlements | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article A Study on the Evaluation of Habitat Appropriateness of Huizhou Traditional Settlements Zhongsong Bi, Yunzhang Li, Jingwen Wang, Yixi Guo, Hongyuan Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4475062/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Aug, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract This study aims to establish an evaluation system for human settlement suitability utilizing geographic detectors, focusing on traditional human settlements in Huizhou region, situated in the southern region of Anhui province, China. Our research reveals several key findings: 1. Central Huizhou exhibits higher overall suitability for traditional human settlements compared to its southern and northern counterparts, with a predominant northeast-southwest spatial differentiation pattern following the mountainous terrain. 2. Approximately 34.03% of the Huizhou is deemed highly suitable for human settlement, while 57.22% is considered moderately suitable, and 8.75% is classified as low suitability. Notably, areas of medium and higher suitability collectively constitute 91.25% of the region, indicating a favorable overall suitability for human settlements. 3. Among traditional settlements, 91.75% are situated in areas classified as medium and above suitability, primarily encompassing plains, plateaus, hills, and low mountains characterized by fertile soil, abundant vegetation, ample precipitation, and favorable climatic conditions. 4. Factors such as precipitation, vegetation, landform, and wind speed exert a significant influence on the spatial distribution of traditional settlements in Huizhou, while others demonstrate comparatively weaker effects. Additionally, the interaction between any two factors exhibits a stronger impact on settlement distribution than individual factors, highlighting the complex interplay of multiple factors in site selection. This study provides valuable insights into the relationship between mountainous traditional settlement site selection and the natural environment, offering guidance for the development of human settlement environments in similar mountainous regions. Earth and environmental sciences/Environmental sciences Earth and environmental sciences/Environmental social sciences Huizhou region traditional settlements geographic detector human living environment suitability evaluation Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction China's expansive landscape, diverse topography, intricate climate, and rich cultural tapestry epitomize its profound heritage. Across different regions, rural settlements exhibit unique and captivating characteristics, reflecting the cultural diversity and natural splendor of the nation [1]. At the national level, efforts to safeguard rural settlements begin with the protection of "small towns and villages" and evolve to encompass historic and cultural towns /villages as well as traditional villages [2]. Since 2002, the Ministry of Housing and Urban-Rural Development, alongside other governmental bodies, has designated a total of 799 Chinese historical and cultural towns and villages across seven batches, among which there are 487 historical and cultural villages included. While the establishment and evolution of this protection system have significantly bolstered rural settlement preservation, the coverage of historical and cultural towns and villages remains inadequate compared to the vast number of natural villages, numbering 2.61 million nationwide [3]. In response to this disparity, the Ministry of Housing and Urban-Rural Development initiated a nationwide investigation and development endeavor focused on traditional villages since 2012. This initiative aimed to elucidate the fundamental essence of traditional villages and their historical-cultural significance [4]. Consequently, China has announced the recognition of six batches comprising 8,155 traditional Chinese villages since 2012, marking a significant stride in the maturation of the protection system for historic and cultural towns / villages, and traditional villages nationwide. The establishment and development process of the protection system of famous historical and cultural towns, villages and traditional villages in China is also the process of the protection and development of traditional settlements. The Party's "19th National Congress" put forward the basic national strategy of "rural revitalization"for the first time, and the Party's "20th National Congress" further clearly proposed to comprehensively promote rural revitalization. Rural areas are a diverse collection of geography, economy, society, politics and culture [5]. As an important part of rural areas in China, traditional villages play an important role in the development of urban and rural areas in China. Traditional villages retain very rich material and intangible cultural heritage, which is an important carrier of Chinese excellent traditional culture. As the protection system for historical and cultural landmarks and traditional villages continues to mature, traditional villages have garnered increasing attention within academic circles. Although domestic research on traditional villages commenced relatively late, it has progressively captivated scholars from diverse backgrounds, leading to a proliferation of studies in this area. Consequently, disciplinary perspectives have broadened, and research methodologies have diversified. In the realm of traditional settlement spatial form analysis, scholars focus on dissecting traditional rural settlement spatial patterns [6], examining traditional settlement forms [7], and investigating traditional settlement groups [8]. Research on settlement spatial distribution delves into the evolution of settlement spatial characteristics [9], the distribution patterns of settlements [10,11,12], and the underlying mechanisms driving settlement spatial distribution [13,14,15,16]. Within the domain of settlement landscape genes, this paper scrutinizes the expression and spatial variability of traditional residential planar prototypes [17], elucidates the processes and mechanisms governing landscape gene production [18], explores methods for constructing spatial gene maps [19,20,21], and investigates landscape gene variation and its governing rules [22], among other facets. Additionally, research on the intangible cultural heritage protection of traditional settlements centers on elucidating the correlation between traditional villages and the spatial distribution of intangible cultural heritage [23,24]. Concerning the protection and utilization of traditional settlements, this paper primarily assesses the tourism value of traditional villages [25] and explores strategies for activating settlement utilization [26]. Methodologically, the research predominantly employs Arc GIS spatial analysis [27,28], the MGWR model [29], literature research, and other quantitative and qualitative analysis methods. While interdisciplinary research on traditional settlements is prevalent, there is a call for further strengthening cross-disciplinary fusion in research methods and contents. Overall, the study of traditional settlements spans multiple disciplines and employs diverse research methods, underscoring the need for enhanced interdisciplinary collaboration and integration. In the investigation of Huizhou traditional settlements, previous research has predominantly centered on aspects such as settlement form [30,31], village culture [32], village protection [33], and village tourism [34]. However, there has been a relative dearth of comprehensive analysis regarding the holistic impact of various factors, including terrain, climate, environment, society, and economy, on the spatial distribution of traditional settlements, as well as the evaluation of human settlement suitability. Building upon this contextual backdrop, this paper endeavors to address these gaps by employing the suitability evaluation theory of human settlements. Specifically, it focuses on traditional settlements in Huizhou as the primary research object, utilizing quantitative analysis methods, particularly the geographic detector technique. The aim is to elucidate the intricate interrelationships between the spatial distribution of traditional settlements in Huizhou and the diverse environmental factors. This investigation operates within two dimensions: factor detection and interactive detection. The overarching goal is to construct a comprehensive suitability model for human settlements in the Huizhou. By exploring the suitability zoning of traditional human settlements, this paper endeavors to offer valuable insights and practical guidance for the development of human settlements, particularly in mountainous areas like Huizhou. Ultimately, this research aims to contribute to informed decision-making processes and facilitate sustainable development initiatives in the region. Research methods and data sources 1.1 Research area overview and database construction Situated within the picturesque southern mountainous region of Anhui Province, Huizhou is graced by the majestic presence of Huangshan Mountain, stretching from northeast to southwest, alongside Tianmu Mountain, Baiji Mountain, and Wulong Mountain, all towering above 1,000 meters in elevation. The landscape is punctuated by numerous valleys and basins, traversed by a labyrinthine network of waterways, including the Xin'an River system, Chang River System, and Qiupu River system [35]. Among these, the Xin'an River reigns as the principal watercourse, originating in Xiuning County of Huizhou (now part of Huangshan City) and flowing eastward to merge with the Qiantang River, serving as its primary source. Historically, much of the ancient Huizhou area was encompassed within present-day Huangshan City (with Wuyuan County now part of Shangrao City, Jiangxi Province). Anhui Province boasts a rich historical heritage, dating back to 216 BC when the first emperor of Qin, Yingzheng, established the two counties, Youxian (Yi) and Shexian, later transformed into Anhui during the Huizong Xuanhe era (1121) of the Song Dynasty. Subsequent governance under the Ming and Qing dynasties was administered by the Huizhou Prefecture. Following liberation, the Huizhou was formally established, culminating in the establishment of Huangshan City in 1987. The research area of this paper encompasses the administrative boundaries of the Huizhou region and Wuyuan County, corresponding to the territory of old Huizhou. Spanning approximately 117°198' to 118°925' north latitude and 29°019' to 30°520' east longitude, this area encompasses approximately 16,079 square kilometers (see Fig. 1 ). The distinctive geographical setting characterized by the proverbial "seven mountains, one water, one field, one road, and one manor" has rendered the Huizhou area a distinct and self-contained physical geographical entity. This unique landscape has not only fostered the emergence of Huizhou culture, characterized by its pronounced regional traits, but has also served as the cradle for the development of Huizhou traditional villages, which seamlessly coexist with the surrounding mountains and rivers. Following the epochs of the Qin, Sui, Tang, Song, and Yuan dynasties, particularly during the Ming and Qing dynasties, the exponential growth of population and the rapid expansion of Huizhou merchants propelled a period of rapid settlement construction in the region, resulting in the proliferation of traditional villages. These Huizhou traditional settlements serve as pivotal bearers of Huizhou culture's living legacy. Their ethos of crafting a living environment characterized by the presence of a "back mountain, surrounded by water, and face screen" artfully embodies the principle of "harmony between nature and humanity." This philosophy emphasizes a deep-seated reverence for, and preservation of, nature, offering a quintessential exemplar of regional characteristics for contemporary inquiries into the relationship between humanity and the land. The roster of Huizhou traditional settlements examined in this paper is drawn from the first to seventh batches of 27 Chinese historical and cultural villages, published by the Ministry of Housing and Urban-Rural Development and the State Administration of Cultural Heritage ( https://www.mohurd.gov.cn/ ) in 2003, 2005, 2007, 2008, 2010, 2014, and 2019, respectively. Additionally, the Ministry of Housing and Urban-Rural Development, along with the Ministry of Culture and other pertinent departments, announced the first to sixth batches of Chinese traditional villages in 2012, 2013, 2014, 2016, 2019, and 2023, amounting to a total of 388 traditional settlements within the study area. Notably, 27 renowned Chinese historical and cultural villages are also encompassed within the list of Chinese traditional villages, thereby comprising the comprehensive inventory of 388 traditional settlements under investigation in this study. 1.2 Research Methods 1.2.1 Human settlements suitability evaluation index Human settlements are profoundly influenced by a multitude of factors, spanning nature, ecology, society, culture, and economy, rendering the evaluation of such settlements complex and multifaceted. Consequently, there is a pressing need to establish a comprehensive, accurate, objective, and feasible evaluation index system to assess human settlements effectively [36]. Drawing upon existing evaluation frameworks for the human settlement environment [37,38] and considering the unique circumstances of Huizhou, this paper endeavors to develop such a system. In this pursuit, the paper selects 15 individual indicators from four dimensions, namely terrain, environment, climate, and society, constituting the criterion layer. These indicators are meticulously chosen to provide a holistic perspective on the human settlement environment of traditional settlements in Huizhou. Through quantitative analysis, these indicators will be utilized to evaluate the suitability of the human settlement environment in Huizhou, as outlined in Table 1 . Table 1 Evaluation index of human living environment suitability in Huizhou traditional settlements Target layer Criteria layer H Indicator layer N Indicator interpretation Indicator code Evaluation of habitat appreciateness Topographic factors Elevation Elevation of the spatial position of habitats X1 Slope Slope gradient of the spatial position of habitats X2 Slope orientation Slope orientation of the spatial position of habitats X3 Landform Landform of the spatial position of habitats X4 Topographic relief height Topographic relief height of the spatial position of habitats X5 Environmental factors Rivers The distance of habitats from the adjacent rivers X6 Vegetation Vegetation type of habitats X7 Soil Soil type of habitats X8 Land utilization land use type of habitats X9 Climate factors Temperature Average annual temperature of habitats X10 Precipitation Average annual precipitation at habitats X11 Sunshine uration Average annual sunshine duration of habitats X12 Wind speed Average annual wind speed at habitats X13 Social factors Huizhou ancient roads The distance of habitats from the adjacent Huizhou ancient roads X14 Highways The distance of habitats from the adjacent highways / county highways X15 1.2.2 Geographic detector model The geographical detector method, as delineated by its foundational work [39], primarily focuses on discerning the characteristics of spatial differentiation. By examining the coupling of variables' spatial distribution, this method identifies potential causal relationships between variables, thereby shedding light on their driving factors. The method encompasses four detectors: risk detection, factor detection, ecological detection, and interactive detection [40]. In this paper, emphasis is placed on factor detection and the Interaction detector method. Widely applied across various disciplines, including natural and social sciences, the geographical detector method serves to investigate the influencing mechanisms underlying the spatial distribution of settlements. This research approach offers several advantages, notably its ability to circumvent the limitations associated with statistical variables and its minimal reliance on presupposed conditions, rendering it relatively objective. Factor detection, a key component of the geographical detector method, primarily aims to identify the driving forces behind the spatial distribution of settlements and assesses the extent to which a factor elucidates the spatial differentiation of settlements. This assessment is quantified by the q value [40], expressed as follows: $$q=1-\frac{\sum _{ℎ=1}^{L}{N}_{ℎ}{\sigma }_{ℎ}^{2}}{N{\sigma }^{2}}= \frac{SSW}{SST}$$ 1 The parameter \(ℎ (\text{1,2},\dots , L)\) denotes the number of influencing factor ( \(\varvec{X}\) ), wherein \({\varvec{N}}_{\varvec{h}}\) and \(\varvec{N}\) signify the number of samples and the total number of samples within class h , respectively. Additionally, \({\varvec{\sigma }}_{\varvec{h}}^{2}\) and \({\varvec{\sigma }}^{2}\) represent the sum of variances and the sum of total variances in layer h, respectively. The terms \(\varvec{S}\varvec{S}\varvec{W}\) (Within Sum of Squares) and \(\varvec{S}\varvec{S}\varvec{T}\) (Total Sum of Squares) denote the sum of variances and the sum of total variances within layer h, respectively [41].The parameter \(\varvec{q}\) signifies the degree of influence factor on the spatial distribution of settlements, ranging from \(0\) to \(1\) . A value of \(\varvec{q}\) closer to \(1\) indicates a stronger influence of the factor on settlement distribution, while values tending towards \(0\) suggest a weaker influence of the factor on settlement distribution. The interactive detection aspect of geographical detectors primarily aims to discern the interaction between different impact factors. This entails examining whether the explanatory power of the dependent variables is enhanced or diminished when two factors operate in tandem [40]. In this paper, single-factor detection and double-factor interaction detection are conducted to ascertain the degree of influence of the combined interaction of factors on the spatial distribution of traditional settlements in Huizhou. 1.2.3 Fuzzy synthetic evaluation method Fuzzy comprehensive evaluation is a comprehensive assessment technique grounded in fuzzy mathematics, which delineates ambiguous boundaries using membership degrees [42]. In this study, the SPSSPRO network platform ( https://www.spsspro.com/ ) is employed for fuzzy weighted evaluation, utilizing the weighted average type (M(*,+)) operator method for computation. The fuzzy comprehensive evaluation model is depicted as follows: $$B=A\times R=\left({a}_{1},\dots ,{a}_{n}\right)\times \begin{array}{ccc}{r}_{1}^{1}& \dots & {r}_{1}^{m}\\ ⋮& \ddots & ⋮\\ {r}_{n}^{1}& \dots & {r}_{n}^{m}\end{array}$$ 2 , In this context, \(\varvec{B}\) represents the equivalent fuzzy subset, and \(\varvec{A}\) denotes the factor set, and \(\varvec{R}\) signifies the review set. The parameters \(\varvec{m}\) and \(\varvec{n}\) represent the number of review grades and factors, respectively, while \({\varvec{a}}_{\varvec{i}}\) ( \(\varvec{i}=\text{1,2},3...,\varvec{n}\) ) stands for the weight coefficient \(\varvec{q}\) assigned to each index. Furthermore, \({\varvec{r}}_{\varvec{n}}^{\varvec{m}}\) represents the membership degree of each factor to the review set. The weight ratio for the \(15\) indexes was derived through normalization processing, thereby facilitating the construction of the evaluation model for the habitability of Huizhou traditional settlements. 1.3 Data sources The pertinent foundational data were sourced from reputable repositories such as the Resources and Environmental Science Data Center at the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences ( http://www.resdc.cn/ ), as well as the National Data Center for Earth System Science ( http://www.geodata.cn/ ) and other relevant databases. Subsequently, all datasets underwent meticulous calibration and processing within the ArcGIS 10.8 environment. The spatial reference utilized throughout the analysis adhered to the GCS-WGS-1984 geographic coordinate system, ensuring consistency and compatibility across all spatial analyses (see Table 2 ). Table 2 Sources and processing of research data Data Data type Data resources Data processing Elevation 30m national elevation data Geospatial data cloud In ArcGIS, clipping or mask extraction tools are used to obtain the elevation data of the study area. Based on the elevation data, data extraction and analysis are carried out on slope, slope direction and topographic relief Water system and roads Map of river network and roads in China Resources and Environmental Science and Data Center, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences In ArcGIS, the tailoring tool is used to obtain water system and road data in the study area, and then the density analysis tool is used to analyze the water system and road Soil 1:1 million spatial distribution map of soil types In ArcGIS, clipping or mask extraction tools are used to extract soil, vegetation, geomorphic type, land use type and meteorological distribution data Map of vegetation type 1:1 million spatial distribution map of vegetation types Geomorphic type 1: 100,000 spatial distribution map of geomorphic types Land-use type 1: 100,000 land-use types (1980s) Resource and Environmental Science data Registration and Publication system, citation data papers [43,44] Meteorological data Average annual temperature, Precipitation, sunshine, Wind Speed (1960–2021) Huizhou ancient roads Ancient road map in Huizhou region Traffic History of Huizhou Region , etc According to the literature records, the routes of ancient roads are matched, and the density of ancient roads and settlements is analyzed In ArcGIS, the process involves utilizing clipping or mask extraction tools to acquire elevation data within the study area. Subsequently, leveraging this elevation data, extraction and analysis procedures are conducted to derive insights into slope, slope direction, and topographic relief. Furthermore, ArcGIS is employed to extract soil, vegetation, geomorphic type, land use type, and meteorological distribution data. This entails utilizing clipping or mask extraction tools to isolate and extract the relevant data layers for further analysis and interpretation. Results and analysis Utilizing the geographic detector model, this study investigates 15 factors influencing the spatial distribution of traditional settlements in Huizhou. Employing the natural breakpoint method within Arc GIS, the analysis aims to elucidate the extent of influence exerted by each factor on the spatial arrangement of settlements. Subsequently, the fuzzy comprehensive evaluation method is employed to develop a comprehensive assessment of human settlement suitability in the Huizhou region. 2.1 Influencing factors of spatial distribution of Huizhou settlements The distribution of traditional settlements in Huizhou is influenced by numerous factors. Through quantitative analysis utilizing the geographical detection model and interactive detection, this study obtained the q-values representing the influence degree of each factor on the spatial distribution of settlements. Additionally, the analysis assessed the influence degree of the combined action of all factors on the spatial distribution of traditional settlements in Huizhou, as illustrated in Fig. 2 . The analysis reveals variations in the degree of influence of each factor on the spatial distribution of traditional settlements in Huizhou, as indicated by the respective q-values, ranked from highest to lowest intensity. Specifically, the factors exerting the strongest influence are X11 precipitation (0.34613), followed by X7 vegetation (0.21925), X4 landform (0.11230), X13 wind speed (0.10814), X9 land use type (0.08067), X14 ancient road (0.07603), X10 air temperature (0.05703), and X13 wind speed (0.10814). Subsequently, the influence diminishes in the following order: X12 sunshine (0.04484), X8 soil (0.03467), X1 elevation (0.03349), X15 highway (0.03107), X3 aspect (0.02841), X6 river (0.02268), X5 topographic relief (0.01998), and X2 slope (0.01311). Table 3 Number and proportion of influencing factor’s settlements Continued Table 3 Number and proportion of influencing factor’s settlements Factor code Factor name Interval Number of habitats percentage(%) X6 Rivers [1234, 2420)m 83 21.39 [2420, 4547)m 8 2.06 X7 Vegetation Cultivated vegetation 115 29.64 Subtropical coniferous forest 145 37.37 Shrub vegetation 65 16.75 Tussock vegetation 39 10.05 Subtropical, temperate deciduous, evergreen, mixed broad-leaved forest, subtropical, tropical bamboo forest and bamboo cluster 24 6.19 X8 Soil Red soil, yellow soil 260 67.01 Paddy soil 64 16.49 Skeleton soil 32 8.25 Lime (rock) soil, purple soil, stony soil 31 7.99 Yellow brown soil, dark yellow brown soil 1 0.26 X9 Land-use Farmland 140 36.08 Forest land 189 48.71 Garden plot 12 3.09 Pasture land, grass land 45 11.60 Others 2 0.52 X10 Temperature [8.2°, 14.6°) 30 7.73 [14.6°, 15.5°) 71 18.30 [15.5°, 16.0°) 81 20.88 [16.0°, 16.6°) 125 32.22 [16.6°, 18.1°) 81 20.88 X11 Amount of precipitation [1578, 1722)mm 147 37.89 [1722, 1825)mm 89 22.94 [1825, 1915)mm 48 12.37 [1915, 1996)mm 89 22.94 [1996, 2219)mm 15 3.87 X12 Sunlight duration [1708, 1723)h 91 23.45 [1723, 1733)h 70 18.04 [1733, 1745)h 97 25.00 [1745, 1760)h 83 21.39 [1760, 1851)h 47 12.11 X13 Wind speed [1.4, 1.7)m/s 42 10.82 [1.7, 2.0)m/s 229 59.02 [2.0, 2.2)m/s 86 22.16 [2.2, 2.5)m/s 29 7.47 [2.5, 3.6)m/s 2 0.52 X14 Huizhou Ancient roads [0, 780)m 106 27.32 [780, 2245)m 82 21.13 [2245, 4993)m 91 23.45 [4993, 10152)m 73 18.81 [10152, 19835)m 36 9.28 X15 Highways [0, 528)m 94 24.23 [528, 1713)m 122 31.44 [1713, 4376)m 115 29.64 [4376, 10358)m 55 14.18 [10358, 23800)m 2 0.52 The analysis of q-values highlights the significant influence of precipitation, vegetation, landform, and wind speed, all surpassing the threshold of 0.1. This suggests that these four factors play a pivotal role in shaping the spatial distribution of traditional settlements in the Huizhou area. Further examination of the spatial distribution pattern of influencing factors and settlement points (as depicted in Fig. 3 and Table 3 – 4 ) reveals noteworthy observations. Predominantly, settlement points are concentrated in regions experiencing average annual rainfall ranging from 1578.183 to 1721.512mm and 1721.512 to 1824.607mm, encompassing 60.83% of the total number of settlement points. Given Huizhou's subtropical monsoon climate characterized by ample rainfall, settlement locations tend to avoid high precipitation areas due to the risk of mountain floods. Moreover, the majority of settlement sites are situated within cultivated plant and subtropical coniferous forest-covered areas, constituting 67.01% of all settlement sites. Analysis of landform types reveals a prevalent distribution of settlements in plains, plateaus, hills, and low mountains, totaling 232 settlement points or 59.8% of the total. This trend suggests a preference for low-altitude areas, although settlements also extend into middle and high mountain regions to accommodate the need for expanded living spaces. Furthermore, wind speed emerges as a significant determinant, with settlement points primarily located in areas experiencing moderate wind speeds of 1.7-2.0m/s. This accounts for 59.02% of all settlement points and signifies a preference for regions with moderate wind speeds, as they foster a conducive microclimate environment for habitation. The q-values associated with land use type, ancient road, air temperature, sunshine, soil, and road range from 0.03 to 0.1, indicating a relatively weaker influence on the spatial distribution of settlements in Huizhou compared to precipitation, vegetation, and landform. Concerning land use types, settlement sites predominantly occupy cultivated land and woodland areas, encompassing 84.78% of all settlement sites. Cultivated land provides essential food security, while woodland contributes to economic value. The relationship between ancient roads and settlements is noteworthy, demonstrating mutual influence. Strong coupling between settlement distribution and ancient road trends is evident, particularly in northern Huizhou, where 48.45% of settlements lie within 2245 meters of ancient roads. Similarly, highways exhibit a close association with settlement distribution, with 85.31% of settlements located within 4,376 meters of highways. This correlation underscores the influence of modern transportation systems on traditional settlements, highlighting their mutual developmental impact. Meteorological elements such as temperature, sunshine, and soil also play crucial roles in settlement location, impacting both the comfort of human settlement environments and crop and vegetation growth. Analysis reveals relatively balanced distribution of settlement points across different annual temperature and sunshine duration areas, indicating that while significant, temperature and sunshine may not be the primary influencing factors. Regarding soil type, settlements predominantly occupy areas with red soil, yellow soil, and paddy soil, comprising 83.51% of all settlement sites. This suggests a preference for soil cover conducive to crop and vegetation growth. Slope direction, slope, and topographic relief are additional factors influencing settlement site selection. Figure 3 and Table 3 illustrate that settlements are distributed predominantly in the south, southeast, and southwest directions, accounting for 43.56% of the total, suggesting a preference for sunny slopes in Huizhou's settlement selection process. Moreover, settlement points exhibit relative equilibrium in their distribution. Analysis of slope and topographic relief reveals that settlements with slopes < 15° constitute 52.06% of the total, while those with topographic relief < 27 meters comprise 67.01%, indicating a tendency to settle in low-altitude areas such as plains, plateaus, and hills. Despite their significance, slope direction, relief degree, and slope exhibit relatively low influence on Huizhou's settlement distribution compared to other factors, including landform, elevation, and sunshine. Regarding river factors, while they contribute minimally to Huizhou's settlement distribution, settlements tend to be located around rivers, with most situated within 1234 meters of rivers, totaling 76.55%. This phenomenon can be attributed to several reasons. First, Huizhou's subtropical monsoon climate, characterized by annual precipitation of 1100–2500 mm, ensures abundant rainfall, meeting the region's water needs for both living and agricultural production. Second, Huizhou's dense river network serves as a vital water source for settlements and facilitates transportation within and outside the region. Despite their importance, rivers exert a relatively minor influence on traditional settlement site selection in Huizhou compared to other factors. Table 4 Results of the interaction probes for each impact factor X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 X13 X14 X15 X1 0.03349 X2 0.16552 0.01311 X3 0.14096 0.15263 0.02841 X4 0.19248 0.17230 0.21674 0.11230 X5 0.14756 0.08842 0.15240 0.16282 0.01998 X6 0.12663 0.13549 0.14382 0.21236 0.11114 0.02268 X7 0.28585 0.30030 0.29192 0.36422 0.30539 0.29798 0.21925 X8 0.11245 0.09500 0.14251 0.18007 0.12083 0.10748 0.31306 0.03467 X9 0.14391 0.14698 0.17776 0.27247 0.17049 0.13393 0.33309 0.13778 0.08067 X10 0.11154 0.14882 0.15194 0.23033 0.16511 0.16516 0.33568 0.15626 0.18176 0.05703 X11 0.46274 0.46026 0.40068 0.55485 0.46095 0.42527 0.50608 0.48112 0.45433 0.52923 0.34613 X12 0.22330 0.14214 0.14333 0.30168 0.15098 0.15433 0.38728 0.22488 0.19122 0.29055 0.52304 0.04484 X13 0.20739 0.25131 0.19577 0.27419 0.23148 0.19055 0.41507 0.19566 0.21385 0.24229 0.52364 0.27987 0.10814 X14 0.16917 0.18553 0.19731 0.30609 0.20512 0.19029 0.34546 0.22972 0.19439 0.21977 0.42317 0.29170 0.27905 0.07603 X15 0.17803 0.12694 0.13091 0.22458 0.13163 0.14021 0.29657 0.17402 0.15068 0.19823 0.42926 0.15974 0.22181 0.16654 0.03107 The interactive detection results of the geographical detector, as depicted in Table 4 , reveal that the interaction values of the two factors surpass the single factor q value, ranging from 0.1 to 0.6. This indicates a substantial enhancement in the influence of the two factors on the spatial distribution of traditional settlements in Huizhou following their interaction. Analyzing the specific interaction of impact factors, in single-factor detection, precipitation exhibits the highest q value, with a significant increase observed after interacting with other factors. Notably, the maximum interaction value of 0.55485 occurs between the precipitation and geomorphic factors, underscoring their pivotal influence on traditional settlement location in Huizhou. Similarly, the interaction value of the slope factor, despite having the lowest q value in single-factor detection, experiences a notable increase after interacting with other factors, particularly with precipitation, vegetation, and wind speed, reaching 0.46026, 0.30030, and 0.25130, respectively. This highlights a significant amplification in the influence of the slope factor and other factors on settlement distribution after interaction. In two-factor interaction detection, the interaction value of the sunshine factor exhibits a markedly enhanced feature. While the q value of sunshine in single-factor detection is 0.04484, its interaction with other factors elevates its q value to over 0.14. Notably, interaction values with precipitation, vegetation, landform, and air temperature reach 0.52304, 0.38728, 0.30168, and 0.29055, respectively, indicating the significant impact of sunshine duration, precipitation, landform, and other factors on settlement distribution in Huizhou. The analysis of factor interaction highlights that the impact of two-factor interaction on traditional settlements in Huizhou surpasses that of single factors. Notably, factors with initially weak influence on settlement location experience a significant enhancement in their influence strength after factor interaction. This suggests that even factors with a q value < 0.1 contribute to the influencing factors of the spatial distribution of traditional settlements in Huizhou. Consequently, the spatial distribution of traditional settlements in Huizhou is shaped by the comprehensive influence of multiple factors, underscoring the complexity and multifaceted nature of settlement dynamics in the region. 2.2 Evaluation of the suitability of Huizhou traditional settlements environment The suitability of the residential environment in traditional settlements in Huizhou was categorized into five levels: very low suitability, low suitability, moderate suitability, high suitability, and very high suitability. This classification aimed to determine the membership degree of each influencing factor. The q value and membership degree derived from the geographical detection results of each factor were incorporated into Formula (2). Subsequently, after normalization, the weights assigned to the 15 influencing factors were determined as follows: 0.045, 0.087, 0.078, 0.094, 0.051, 0.047, 0.074, 0.118, 0.037, 0.050, 0.070, 0.086, 0.084, 0.043, and 0.036, respectively. Consequently, the comprehensive suitability model for the human settlement environment in Huizhou's traditional settlements was established as follows: f(Y)= 0.045 × elevation + 0.087 × slope gradient + 0.078 × slope aspect + 0.094 × physiognomy + 0.051× topographic relief height + 0.047 × rivers + 0.074 × vegetation + 0.118 × soil + 0.037 × land-use type + 0.050 × air temperature + 0.070 × rain temptation + 0.086 × sunshine + 0.084 × wind speed + 0.043 × ancient roads + 0.036 × highroad. This model delineates the residential environment suitability zoning map for traditional settlements in Huizhou, which is illustrated in Fig. 4 and summarized in Table 5 . Table 5 Area and number of settlements by suitability zones Habitat Appropriateness Area(km 2 ) Percentage(%) Number of settlements (units) Percentage(%) Very low 48.79 0.30 2 0.52 Low 1359.18 8.45 30 7.73 Medium 9200.63 57.22 189 48.71 High 4921.92 30.61 137 35.31 Very high 548.95 3.42 30 7.73 Based on the statistical analysis outcomes (see Fig. 4 and Table 5 ), it is evident that the region with moderate to high suitability spans 14,671.5 square kilometers, constituting a significant portion of 91.25% of territorial expanse in Huizhou region. Within this area, regions with moderate suitability encompass 30.61%, while those with high suitability account for 34.03%. These findings suggest an overall favorable suitability of Huizhou's human settlements. Regarding the spatial distribution of settlements, 356 settlements are situated within areas categorized as moderate suitability and above, representing a substantial 91.75% of the total settlements. Specifically, settlements within areas characterized by moderate, high, and very high suitability comprise 48.71%, 43.04%, and 0.0% respectively. In contrast, settlements within areas designated as having low to very low suitability constitute a mere 8.25%. This underscores that traditional settlements in Huizhou predominantly inhabit areas with moderate to high suitability, reflecting a strong spatial correlation between settlement distribution and regions with moderate to high suitability. According to the comprehensive suitability grade classification results (see Fig. 5 ), areas classified as having low suitability are characterized by specific environmental parameters. These areas typically exhibit elevations ranging from 899 to 1807 meters, characterized by high mountainous terrain. The topographic relief spans from 58 to 326 meters, indicating varied relief within this region. Slope angles fall within the range of 25° to 78°, with predominant slope directions oriented towards the east-north and north-north directions.Vegetation types within these areas include temperate deciduous broad-leaved forest, subtropical deciduous broad-leaved forest, subtropical and tropical bamboo forests, and bamboo clusters, as well as subtropical evergreen and mixed deciduous broad-leaved forests. Soil types consist of lime (rock) soil, purple soil, stony soil, and coarse bone soil. Climatically, the average annual temperature ranges from 8.2° to 12.6°C, while the average annual precipitation falls between 1578.1 and 1721.5 mm. Sunshine duration annually spans from 1708.3 to 1727.3 hours, with an average annual wind speed ranging between 1.4 and 1.7 m/s. Settlement points within these regions are notably distributed away from river systems, ancient roads, and highways, indicating a less favorable location for human settlement. According to the comprehensive suitability grade classification, the areas classified as having a low suitability degree exhibit specific environmental characteristics. These regions are characterized by elevations ranging from 612 to 899 meters, representing middle mountainous terrain. The relief degree within this area ranges from 41 to 58 meters, indicating moderate relief. Slope angles fall within the range of 15° to 25°, with predominant slope directions oriented towards the southwest and west.Vegetation types within these areas predominantly consist of subtropical coniferous forests. Soil types include red soil and yellow soil, typical of subtropical regions. Climatically, the average annual temperature ranges from 12.6° to 14.2°C. The average annual precipitation falls between 1721.5 and 1824.6 mm, with an annual sunshine duration spanning from 1727.3 to 1743.6 hours. Additionally, the average annual wind speed ranges from 1.7 to 2.0 m/s. Settlement sites within these regions are relatively distant from river systems, ancient roads, and highways, indicating less favorable conditions for human settlement. According to the comprehensive suitability grade classification, the medium suitability areas exhibit specific environmental characteristics conducive to human settlement. These regions are characterized by elevations ranging from 404 to 612 meters, representing low mountainous terrain. The relief degree within this area ranges from 27 to 41 meters, indicating moderate relief. Slope angles fall within the range of 5° to 15°, with predominant slope directions oriented towards the southeast and south. Vegetation types within these areas include subtropical and tropical evergreen broad-leaved and deciduous broad-leaved shrubs. Soil types consist of yellow brown soil and dark yellow brown soil, which are typical of subtropical regions. Climatically, the average annual temperature ranges from 14.2° to 15.4°C. The average annual precipitation falls between 1824.6 and 1915.1 mm, with an annual sunshine duration spanning from 1743.6 to 1762.1 hours. Additionally, the average annual wind speed ranges from 2.0 to 2.2 m/s. Settlement sites within these regions are relatively close to river systems, ancient roads, and highways, indicating favorable conditions for human settlement. The high suitability areas exhibit distinct environmental characteristics conducive to human settlement. These regions are characterized by elevations ranging from 238 to 404 meters, representing hilly terrain. The relief degree within this area ranges from 14 to 27 meters, indicating relatively gentle relief. Slope angles fall within the narrow range of 2° to 5°, predominantly oriented towards the southeast and east directions. Vegetation types within these areas include temperate grass, subtropical grass, and tropical grass varieties, indicative of favorable conditions for grazing and agriculture. Soil types consist primarily of tidal soil, suitable for agricultural activities. Climatically, the average annual temperature ranges from 15.4° to 16.4°C, creating a mild and favorable climate for human habitation. The average annual precipitation falls between 1915.1 and 1995.6 mm, ensuring sufficient water resources for agricultural and domestic purposes. Furthermore, the annual sunshine duration spans from 1762.1 to 1786.7 hours, providing ample sunlight for agricultural productivity. Additionally, the average annual wind speed ranges from 2.2 to 2.6 m/s, contributing to a comfortable living environment. Settlement sites within these regions are strategically located close to rivers, ancient roads, and highways, facilitating transportation and trade activities, further enhancing their suitability for human settlement. The high suitability areas exhibit favorable conditions for human settlement and agricultural activities. These regions are characterized by elevations ranging from − 86 to 238 meters, indicating predominantly plain and platform landforms. The topographic relief within this area ranges from 0 to 14 meters, showcasing relatively flat terrain conducive to agricultural cultivation. Slope angles fall within the narrow range of 0° to 2°, predominantly oriented towards the northwest and north directions. Vegetation types within these areas include two-crop water-drought grain crops, economic forests, two-crop or three-crop water-drought rotations, and evergreen fruit orchards, facilitating diverse agricultural practices. Soil types consist primarily of paddy soil, suitable for wetland agriculture. Climatically, the average annual temperature ranges from 16.4° to 18.1°C, creating favorable conditions for agricultural productivity. The average annual precipitation falls between 1995.6 and 2219.3 mm, ensuring ample water resources for agricultural irrigation. Furthermore, the annual sunshine duration spans from 1786.7 to 1851.2 hours, providing optimal conditions for crop growth. Additionally, the average annual wind speed ranges from 2.6 to 3.6 m/s, contributing to a comfortable living environment. Settlement sites within these regions are strategically located close to river systems, ancient roads, and highways, facilitating transportation and trade activities, further enhancing their suitability for human settlement and economic development. Upon comprehensive analysis, despite being situated in the mountainous terrain of southern Anhui, the Huizhou area benefits from favorable climatic conditions, an isolated geographical environment, and an extensive river network. These natural attributes collectively contribute to the creation of a conducive living environment. Influenced by various factors such as elevation, slope, slope direction, landform, topographic relief, river distribution, vegetation coverage, soil type, temperature, precipitation, and sunshine duration, traditional settlements in Huizhou are predominantly located in areas exhibiting medium to high suitability for human habitation. Despite the mountainous landscape, the region's favorable living conditions have encouraged its inhabitants to overcome geographical constraints and continuously expand their living spaces. In sum, the concentration of settlements in regions with favorable environmental conditions underscores the adaptability and resilience of the Huizhou people, who have effectively utilized their natural surroundings to establish thriving communities. This symbiotic relationship between humans and their environment highlights the importance of understanding and preserving the unique geographical and natural features that have shaped the cultural landscape of Huizhou over centuries. Conclusion and discussion 3.1 Conclusion Arc GIS and geographic detector were employed in tandem to comprehensively assess the influence of 15 factors, encompassing elevation, slope, landform, river distribution, vegetation coverage, soil type, and precipitation, on the site selection and spatial distribution of traditional settlements in Huizhou. Through this methodological approach, an evaluation of the suitability of the residential environment for traditional settlements in Huizhou was conducted. The key conclusions drawn from this study are summarized as follows: (1) The overall suitability of traditional settlements in the Huizhou region reveals that the central area exhibits higher suitability compared to the southern and northern regions, following the northeast-southwest spatial differentiation pattern typical of mountain ranges. Particularly, higher elevation mountain ranges exert a more pronounced impact on settlement suitability. (2) In Huizhou, areas deemed highly suitable for human settlements cover 5470.87 km2, constituting 34.03% of the region; those with moderate suitability span 9200.63 km2, accounting for 57.22%; and those with low suitability encompass 1407.97 km2, representing 8.75%. Notably, regions with moderate suitability and above account for 91.25%, suggesting an overall favorable suitability for human settlements in the Huizhou area. (3) Regarding the spatial distribution of traditional settlements in Huizhou, 167 settlements are situated in highly suitable areas, comprising 43.04% of the total; 189 settlements are in moderately suitable areas, making up 48.71%; and 32 settlements are located in areas with low suitability, accounting for 8.25%. Impressively, 91.75% of traditional villages are found in regions with moderate or higher suitability, predominantly in plains, platforms, hills, and low mountains boasting rich soil, abundant vegetation, and favorable climatic conditions. Additionally, the unique geographical landscape, characterized by numerous mountains and limited land, encouraged Huizhou ancestors to overcome environmental constraints and expand their living spaces, leading to the distribution of some traditional villages in less suitable areas. (4) Among the 15 influencing factors, including elevation, slope, landform, river distribution, vegetation coverage, precipitation, and wind speed, precipitation, vegetation, landform, and wind speed exert a substantial influence on the spatial distribution of traditional settlements in Huizhou, with precipitation being the most impactful. Conversely, factors such as land use, ancient roads, air temperature, sunshine, soil, elevation, and roads exhibit relatively weaker effects. However, slope direction, river distribution, relief degree, and slope demonstrate minimal influence on settlement distribution. Overall, ensuring access to essential land resources for survival and facilitating regional economic development through activities like tea cultivation and forestry are primary considerations for selecting traditional settlement sites in Huizhou. (5) Analysis of detection results reveals variations in the degree of influence of individual factors on the distribution of traditional settlements in Huizhou. However, interactive detection outcomes indicate that the interaction between any two factors surpasses the influence of a single factor and is significantly enhanced, underscoring the collective and amplified influence of multiple factors on traditional settlement locations in Huizhou. Therefore, a comprehensive analysis of several factors is essential for accurately assessing and dividing the suitability of the regional human settlement environment in Huizhou. 3.2 Discussion The analysis of the relationship between humans and the environment underscores the profound impact of natural ecological factors on the spatial distribution of traditional settlements in the Huizhou area. The guiding principles of Huizhou ancestors, emphasizing "respecting nature, protecting nature, and utilizing nature," form the foundational tenet governing the construction of the human settlement environment in the region. The simplistic yet powerful concept of "harmony between nature and man" is inherently embedded in the fabric of Huizhou's regional human settlement environment. To safeguard traditional settlements in Huizhou, it becomes imperative to fortify the protection of the ecological environment that serves as the bedrock for their existence. Leveraging the favorable climatic conditions of southern Anhui, deliberate efforts should be made to cultivate conducive vegetation communities and habitat conditions. This strategic approach aims to mitigate the impact and mitigate the risks of geological disasters resulting from environmental shifts on the human settlement environment. In doing so, it seeks to propel the profound inheritance and development of the traditional settlement culture in Huizhou. By building upon the solid foundation of the traditional living environment characterized by "back mountain - surrounding water - surface screen," an enhanced and harmonious living ecological and cultural environment can be meticulously crafted. This study delves into the suitability evaluation of traditional settlements in the mountainous Huizhou of southern Anhui province, focusing on natural elements using geographical detectors. Its aim is to offer insights that can inform the preservation and development of mountain settlements not only in Huizhou but also across China. Recognizing the inherent limitations in accessing historical data, this paper concentrates on examining the influence of natural environmental factors on settlement patterns and human habitat construction. It acknowledges that traditional human settlements are subject to multifaceted influences encompassing nature, society, economy, and culture. While this may affect the precision of the evaluation results regarding settlement suitability, it underscores the complexity of settlement dynamics. Future endeavors in the realm of traditional settlement construction will necessitate comprehensive evaluations and scientifically grounded predictions considering the interplay of human, social, economic, and natural ecological factors. Declarations Fund Projects Anhui Provincial Key Laboratory of Regional Culture and Smart Tourism Integration Effect Key Project (WLSYS202304), Anhui Provincial Philosophy and Social Science Research Key Project (2023AH051351, SK2020A0464). Author Contribution Conceptualization, H. L. and Y.L.; Methodology, H.L and Z. B.; Data curation, Y. G. and J. W.; Writing—original draft, Z.B., Y.G., and J.W.; Writing—review and editing, Y.L. and H.L.; Supervision, Y.L. and H.L.; All authors have read and agreed to the published version of the manuscript. Data Availability The datasets generated and/or analysed during the current study are available public in the Chinese Academy of Sciences (http://www.resdc.cn/), the Ministry of Housing and Urban-Rural Development and the State Administration of Cultural Heritage (https://www.mohurd.gov.cn/), and the National Data Center for Earth System Science (http://www.geodata.cn/). The specific information and sources of the data used are detailed in the last paragraph in Section 1.1 and Table 2 of the submitted manuscript. References XUE L P. An Introduction to the Preservation of Architectural Heritage (2nd Edition). Beijing: Building Industry Press, 2017: 24–39. Ministry of Urban and Rural Development, Ministry of Culture on Request for Announcement of the Second Batch of National Historical and Cultural Cities. State Council of the People’s Republic of China, Bulletin, 1986, (35): 1075–1086. Liu S Y, Cheng G Q. The Road to Rural Revitalization in China: Theory, Institutions and Policy. Beijing: Science Press, 2021: 107–132. Notice of the Ministry of Housing and Urban-Rural Development, Ministry of Culture, State Administration of Cultural Heritage, and Ministry of Finance on Carrying out Surveys on Traditional Villages. https://www.gov.cn/zwgk/2012-04/24/content_2121340.htm , 2014-02–24. ZHOU G H, LONG H L, LIN W L, et al. Theoretical debates and practical development of the "three rural issues" and rural revitalization in the New Era. Journal of Natural Resources, 2023,38(08):1919–1940. DING J, WANG R M. Understanding the Spatial Pattern of Historical Chinese Rural Settlements: A Syntactical Approach. Journal of Human Settlements in West China, 2023, 38(5): 103–109. CHEN C, LI B H, WANG M Z. Historical Evolution of the Space Form of Traditional Settlements influenced by Temples in Inner Mongolia Autonomous Region since the Qing Dynasty: A Case Study of Bailingmiao Town. Economic Geography, 2023,43(11):220–228. PEI Y F. The Research of Huizhou Traditional Village Group. Nanjing: Southeast University,2021. CHEN Q T, ZHANG L, DUAN Y P. Spatial-temporal pattern and evolution of traditional villages in Jiangxi province. National Remote Sensing Bulletin, 2021,25(12): 2460–2471 QIU Z Z, HU X J, QIAN H, et al. Spatiotemporal Distribution Characteristics and Influencing Factors of Traditional Villages in Fujian Province. Economic Geography, 2023,43(06):211–219. YANG Y, HU J, LIU D J, et al. Spatial differentiation of ethnic traditional villages in Guizhou province and the influencing factors. Journal of Arid Land Resources and Environment, 2022,36(02):178–185. YUAN J Y, HUANG L Y, YAO S, et al. Study on Spatial Distribution Characteristics and Influence Mechanism of Traditional Villages in Hebei Province. Territory & Natural Resources Study, 2023,(06):42–46. TANG M G, HU J, TANG X F, et al. Geographical pattern and differentiational mechanism of ancient villages in Guizhou province. Journal of Arid Land Resources and Environment, 2022,36(11):158–167. SHI Y W, ZHU X G, SUN J, et al. Spatial Distribution Characteristics and Influencing Factors of Traditional Villages in Yunnan Province. Resource Development & Market, 2022,38(07):809–817. DONG P, ZHOU X N, et al. Study on Spatial Distribution Characteristics and Influencing Factors of Historical and Cultural Towns and Villages in the Yangtze River Economic Belt. Geography and Geo-Information Science, 2022,38(03):66–73.8(03):66–73. JU X X, YANG C C,ZHAO M W, et al. Spatial Distribution Characteristics and Influencing Factors of Traditional Villages in Zhejiang, Anhui, Shaanxi, Yunnan Provinces. Economic Geography, 2022,42(02):222–230. YIN L C, LIU P L. Type expression and spatial differentiation of planar archetype genes of traditional dwellings of the Xiangjiang River Basin. Geographical Research, 2023,42(08):2191–2210. YANG L G, HU Y L, WU X F, et al. Cultural landscape gene production process and mechanism of Dong traditional village:A case study of Huangdu village. Journal of Natural Resources, 2023,38(05):1164–1177. CHENG J J, YAN Y, HU X F, et al. Construction of Spatial Gene Map of Traditional Villages, Anhui Province. Planners, 2022,38(12):65–71. YIN LC, LIU P L, LI B H, et al. Map of traditional settlement landscape morphology gene: A case study of the Xiangjiang River Basin. Scientia Geographica Sinica,2023,43(6):1053–1065. WANG Y S, ZHANG Z H. Construction of Local Knowledge Graph of Traditional Cave Dwelling Settlement Landscape: A Case Study of Northern Shaanxi. Landscape Architecture,2023,30(08):103–110. LI B H, LI Z, LIU P L, et al. Landscape gene variation and differentiation law of traditional villages in Xiangjiang River Basin. Journal of Natural Resources, 2022,37(02):362–377. TIAN L, SHI B X, SUN F Z, et al. Spatial correlation between traditional villages and intangible cultural heritage in the Yellow River Basin. Journal of Arid Land Resources and Environment, 2023,37(03):186–19. LI R Y, SHI Z Y. Spatial Dislocation and Mechanism of the Distribution of Traditional Villages and Intangible Cultural Heritage in the Y angtze River Economic Belt. Geography and Geo-Information Science, 2022,38(05):129–137. CHEN X Y, HUANG R, HONG X T, et al. The measurement of xiangchou and its resource value in traditional village tourism destinations: A case study in Southern Jiangsu. Journal of Natural Resources, 2020,35(07):1602–1616. XU Shaohui, DONG Liping. Spatial Distribution and Tourism Activation of Traditional Villages in Yunnan Province[J]. Journal of Resources and Ecology,2022,13(05):851–859. CHEN B, XU S Z, ZHOU Y Y, et al. Analysis of Multi scale Characteristics and Influencing Factors Under the Spatial Distribution of Traditional Villages - Taking 263 Traditional Villages in Guangdong Province as Examples. Research of Soil and Water Conservation, 2023,30(01):423–429. FANG Y L, LU H Y, HUANG Z F, et al. Spatiotemporal Distribution of Chinese Traditional Villages and Its Influencing Factors. Economic Geography, 2023,43(09):187–196. FAN L, ZHANG D Y. Study on Spatial Differentiation Characteristics and Influencing Factors of Traditional Villages in North China Based on MGWR Model. Chinese Landscape Architecture, 2022,38(10):56–61. JIN Z T, PRI Y F, GONG K. From Village Form to Traditional Residential Space: Survey and Mapping of Huizhou Villages with Layered Focuses. Heritage Architecture, 2021,(01):52–59. WANG Y. A Study on the Morphology of Imaginary Planes in Huizhou Ancient Villages from the Perspective of Flood Control. Jiang-huai Tribune, 2018,(01):155–160. KONG X, ZHUO F Y, MIAO C S. Influence of Tourism Development on Traditional Local Culture Preservation: Based on the Field Work in Hongcun, Chengkan and Xucun Villages. Tropical Geography, 2016,36(2):216–224. LI J L, CHU J L, LI Y. Reseach on the Spatial Distribution Pattern and Protection and development of Ancient Huizhou Traditional Villages. Chinese Journal of Agricultural Resources and Regional Planning, 2019,40(10):101–109. YUAN C, KONG X, LI L Q, et al. Traditional Village Image Perception Research Based on Tourist UGC Data: A Case of Chengkan Village. Economic Geography, 2020,40(08):203–211. Huangshan City Local Records Committee. Huangshan City Records (~ 2006). Hefei: Huangshan Bookstore, 2010:37–113. XIA X Y, CHEN H M, GAO Q, et al. A Study on Temporal and Spatial Variations of Suitability of Urban Living Environment in Jiangsu Province Based on a Geographical Detector [J]. Bulletin of Soil and Water Conservation, 2020,40 (3):289–296. DU X Y, HU X J, JIN X L, et al. Evaluation of human settlement environment suitability of Neolithic settlement sites in Hunan Province based on geographical detector. Journal of Earth Environment, 2020,40(08):203–211. Cao F, Ge Y, Wang J F. Optimal discretization for geographical detectors- based risk assessment[J]. GIScience& Remote Sensing, 2013,50(1): 78–92. Cao F, Ge Y, Wang J F. Optimal discretization for geographical detectors- based risk assessment[J]. GIScience& Remote Sensing, 2013,50(1): 78–92. WANG J F, XU C D. Geodetector: Principle and Prospective. Acta Geographica Sinica, 2017,72(1):116–134. CUI Z H, YAN Y. A GIS-based Research on the Spatial Evolution Characteristics and Influence Mechanism of the Rural Settlements in City Island: A Case Study of Baguazhou in Nanjing. Modern Urban Research, 2020(2):90–97. YIN X Y, SONG S M, YAN G H, et al. Construction and application of aquatic ecological risk assessment model for Dongting Lake. Water Resources and Hydropower Engineering, 2022, 53(S1): 45–53. XU X L. China’s 1 Million Land Use Data in the 1980s. Resource Environmental Science Data Registration and Publishing System ( http://www.resdc.cn/DOI) , 2023. DOI: 0.12078/2023010202. XU X L. Annual Spatial Interpolation Dataset of Meteorological Elements in China. Resource Environmental Science Data Registration and Publishing System ( http://www.resdc.cn/DOI) , 2023. DOI: 0.12078/2023010202. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 01 Aug, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 28 Oct, 2024 Reviews received at journal 26 Oct, 2024 Reviewers agreed at journal 14 Oct, 2024 Reviews received at journal 13 Aug, 2024 Reviewers agreed at journal 02 Aug, 2024 Reviewers invited by journal 02 Aug, 2024 Editor assigned by journal 02 Aug, 2024 Editor invited by journal 29 May, 2024 Submission checks completed at journal 29 May, 2024 First submitted to journal 25 May, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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19:21:23","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":61419,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDetection results of q value of each influence factor\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4475062/v1/6d591a749dbc2b1bc7977921.png"},{"id":58230617,"identity":"91624dbf-3936-49bd-b2cd-b20c707d1a04","added_by":"auto","created_at":"2024-06-12 19:21:22","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":362635,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe relationship map of each influencing factor and the geospatial of the settlement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(Y density of settlement points, X1 elevation, x2 slope, X3 aspect, X4 landform, X5 terrain undulation, X6 river, X7 vegetation, X8 soil, X9 land use, X10 air temperature, X11 precipitation, X12 sunshine duration, X13 wind speed, X14 ancient road, X15 highway)\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4475062/v1/f93a14e9b9c3180f97709a31.jpeg"},{"id":58230636,"identity":"c056e293-54c3-468a-a904-c9be00a0d27a","added_by":"auto","created_at":"2024-06-12 19:21:23","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":96927,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePartition of the human habitat suitability in Huizhou traditional settlements\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4475062/v1/a194a745048e1bb594b9f1c6.jpeg"},{"id":88268360,"identity":"472ed75c-82cf-4d43-b103-eda9b65f95f3","added_by":"auto","created_at":"2025-08-04 16:51:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1705580,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4475062/v1/f1351a34-9484-4c23-8268-dfaf635c2ad6.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Study on the Evaluation of Habitat Appropriateness of Huizhou Traditional Settlements","fulltext":[{"header":"Introduction","content":"\u003cp\u003eChina\u0026apos;s expansive landscape, diverse topography, intricate climate, and rich cultural tapestry epitomize its profound heritage. Across different regions, rural settlements exhibit unique and captivating characteristics, reflecting the cultural diversity and natural splendor of the nation [1]. At the national level, efforts to safeguard rural settlements begin with the protection of \u0026quot;small towns and villages\u0026quot; and evolve to encompass historic and cultural towns\u0026nbsp;/villages as well as traditional villages [2]. Since 2002, the Ministry of Housing and Urban-Rural Development, alongside other governmental bodies, has designated a total of 799 Chinese historical and cultural towns and villages across seven batches, among which there are 487 historical and cultural villages included. While the establishment and evolution of this protection system have significantly bolstered rural settlement preservation, the coverage of historical and cultural towns and villages remains inadequate compared to the vast number of natural villages, numbering 2.61 million nationwide [3]. In response to this disparity, the Ministry of Housing and Urban-Rural Development initiated a nationwide investigation and development endeavor focused on traditional villages since 2012. This initiative aimed to elucidate the fundamental essence of traditional villages and their historical-cultural significance [4]. Consequently, China has announced the recognition of six batches comprising 8,155 traditional Chinese villages since 2012, marking a significant stride in the maturation of the protection system for historic and cultural towns / villages, and traditional villages nationwide.\u003c/p\u003e\n\u003cp\u003eThe establishment and development process of the protection system of famous historical and cultural towns, villages and traditional villages in China is also the process of the protection and development of traditional settlements. The Party\u0026apos;s \u0026quot;19th National Congress\u0026quot; \u0026nbsp; put forward the basic national strategy of \u0026quot;rural revitalization\u0026quot;for the first time, and the Party\u0026apos;s \u0026quot;20th National Congress\u0026quot; further clearly proposed to comprehensively promote rural revitalization. Rural areas are a diverse collection of geography, economy, society, politics and culture [5]. As an important part of rural areas in China, traditional villages play an important role in the development of urban and rural areas in China. Traditional villages retain very rich material and intangible cultural heritage, which is an important carrier of Chinese excellent traditional culture.\u003c/p\u003e\n\u003cp\u003eAs the protection system for historical and cultural landmarks and traditional villages continues to mature, traditional villages have garnered increasing attention within academic circles. Although domestic research on traditional villages commenced relatively late, it has progressively captivated scholars from diverse backgrounds, leading to a proliferation of studies in this area. Consequently, disciplinary perspectives have broadened, and research methodologies have diversified. In the realm of traditional settlement spatial form analysis, scholars focus on dissecting traditional rural settlement spatial patterns [6], examining traditional settlement forms [7], and investigating traditional settlement groups [8]. Research on settlement spatial distribution delves into the evolution of settlement spatial characteristics [9], the distribution patterns of settlements [10,11,12], and the underlying mechanisms driving settlement spatial distribution [13,14,15,16]. Within the domain of settlement landscape genes, this paper scrutinizes the expression and spatial variability of traditional residential planar prototypes [17], elucidates the processes and mechanisms governing landscape gene production [18], explores methods for constructing spatial gene maps [19,20,21], and investigates landscape gene variation and its governing rules [22], among other facets. Additionally, research on the intangible cultural heritage protection of traditional settlements centers on elucidating the correlation between traditional villages and the spatial distribution of intangible cultural heritage [23,24]. Concerning the protection and utilization of traditional settlements, this paper primarily assesses the tourism value of traditional villages [25] and explores strategies for activating settlement utilization [26]. Methodologically, the research predominantly employs Arc GIS spatial analysis [27,28], the MGWR model [29], literature research, and other quantitative and qualitative analysis methods. While interdisciplinary research on traditional settlements is prevalent, there is a call for further strengthening cross-disciplinary fusion in research methods and contents. Overall, the study of traditional settlements spans multiple disciplines and employs diverse research methods, underscoring the need for enhanced interdisciplinary collaboration and integration.\u003c/p\u003e\n\u003cp\u003eIn the investigation of Huizhou traditional settlements, previous research has predominantly centered on aspects such as settlement form [30,31], village culture [32], village protection [33], and village tourism [34]. However, there has been a relative dearth of comprehensive analysis regarding the holistic impact of various factors, including terrain, climate, environment, society, and economy, on the spatial distribution of traditional settlements, as well as the evaluation of human settlement suitability. Building upon this contextual backdrop, this paper endeavors to address these gaps by employing the suitability evaluation theory of human settlements. Specifically, it focuses on traditional settlements in Huizhou as the primary research object, utilizing quantitative analysis methods, particularly the geographic detector technique. The aim is to elucidate the intricate interrelationships between the spatial distribution of traditional settlements in Huizhou and the diverse environmental factors. This investigation operates within two dimensions: factor detection and interactive detection. The overarching goal is to construct a comprehensive suitability model for human settlements in the Huizhou. By exploring the suitability zoning of traditional human settlements, this paper endeavors to offer valuable insights and practical guidance for the development of human settlements, particularly in mountainous areas like Huizhou. Ultimately, this research aims to contribute to informed decision-making processes and facilitate sustainable development initiatives in the region.\u003c/p\u003e"},{"header":"Research methods and data sources","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003e1.1 Research area overview and database construction\u003c/h2\u003e \u003cp\u003eSituated within the picturesque southern mountainous region of Anhui Province, Huizhou is graced by the majestic presence of Huangshan Mountain, stretching from northeast to southwest, alongside Tianmu Mountain, Baiji Mountain, and Wulong Mountain, all towering above 1,000 meters in elevation. The landscape is punctuated by numerous valleys and basins, traversed by a labyrinthine network of waterways, including the Xin'an River system, Chang River System, and Qiupu River system [35]. Among these, the Xin'an River reigns as the principal watercourse, originating in Xiuning County of Huizhou (now part of Huangshan City) and flowing eastward to merge with the Qiantang River, serving as its primary source. Historically, much of the ancient Huizhou area was encompassed within present-day Huangshan City (with Wuyuan County now part of Shangrao City, Jiangxi Province). Anhui Province boasts a rich historical heritage, dating back to 216 BC when the first emperor of Qin, Yingzheng, established the two counties, Youxian (Yi) and Shexian, later transformed into Anhui during the Huizong Xuanhe era (1121) of the Song Dynasty. Subsequent governance under the Ming and Qing dynasties was administered by the Huizhou Prefecture. Following liberation, the Huizhou was formally established, culminating in the establishment of Huangshan City in 1987. The research area of this paper encompasses the administrative boundaries of the Huizhou region and Wuyuan County, corresponding to the territory of old Huizhou. Spanning approximately 117\u0026deg;198' to 118\u0026deg;925' north latitude and 29\u0026deg;019' to 30\u0026deg;520' east longitude, this area encompasses approximately 16,079 square kilometers (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe distinctive geographical setting characterized by the proverbial \"seven mountains, one water, one field, one road, and one manor\" has rendered the Huizhou area a distinct and self-contained physical geographical entity. This unique landscape has not only fostered the emergence of Huizhou culture, characterized by its pronounced regional traits, but has also served as the cradle for the development of Huizhou traditional villages, which seamlessly coexist with the surrounding mountains and rivers. Following the epochs of the Qin, Sui, Tang, Song, and Yuan dynasties, particularly during the Ming and Qing dynasties, the exponential growth of population and the rapid expansion of Huizhou merchants propelled a period of rapid settlement construction in the region, resulting in the proliferation of traditional villages. These Huizhou traditional settlements serve as pivotal bearers of Huizhou culture's living legacy. Their ethos of crafting a living environment characterized by the presence of a \"back mountain, surrounded by water, and face screen\" artfully embodies the principle of \"harmony between nature and humanity.\" This philosophy emphasizes a deep-seated reverence for, and preservation of, nature, offering a quintessential exemplar of regional characteristics for contemporary inquiries into the relationship between humanity and the land.\u003c/p\u003e \u003cp\u003eThe roster of Huizhou traditional settlements examined in this paper is drawn from the first to seventh batches of 27 Chinese historical and cultural villages, published by the Ministry of Housing and Urban-Rural Development and the State Administration of Cultural Heritage (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.mohurd.gov.cn/\u003c/span\u003e\u003cspan address=\"https://www.mohurd.gov.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) in 2003, 2005, 2007, 2008, 2010, 2014, and 2019, respectively. Additionally, the Ministry of Housing and Urban-Rural Development, along with the Ministry of Culture and other pertinent departments, announced the first to sixth batches of Chinese traditional villages in 2012, 2013, 2014, 2016, 2019, and 2023, amounting to a total of 388 traditional settlements within the study area. Notably, 27 renowned Chinese historical and cultural villages are also encompassed within the list of Chinese traditional villages, thereby comprising the comprehensive inventory of 388 traditional settlements under investigation in this study.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e1.2 Research Methods\u003c/h2\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003e1.2.1 Human settlements suitability evaluation index\u003c/h2\u003e \u003cp\u003eHuman settlements are profoundly influenced by a multitude of factors, spanning nature, ecology, society, culture, and economy, rendering the evaluation of such settlements complex and multifaceted. Consequently, there is a pressing need to establish a comprehensive, accurate, objective, and feasible evaluation index system to assess human settlements effectively [36]. Drawing upon existing evaluation frameworks for the human settlement environment [37,38] and considering the unique circumstances of Huizhou, this paper endeavors to develop such a system. In this pursuit, the paper selects 15 individual indicators from four dimensions, namely terrain, environment, climate, and society, constituting the criterion layer. These indicators are meticulously chosen to provide a holistic perspective on the human settlement environment of traditional settlements in Huizhou. Through quantitative analysis, these indicators will be utilized to evaluate the suitability of the human settlement environment in Huizhou, as outlined in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEvaluation index of human living environment suitability in Huizhou traditional settlements\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTarget layer\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCriteria layer H\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIndicator layer N\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIndicator interpretation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIndicator code\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"14\" rowspan=\"15\"\u003e \u003cp\u003eEvaluation of habitat appreciateness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eTopographic factors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eElevation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eElevation of the spatial position of habitats\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eX1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSlope\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSlope gradient of the spatial position of habitats\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eX2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSlope orientation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSlope orientation of the spatial position of habitats\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eX3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLandform\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLandform of the spatial position of habitats\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eX4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTopographic relief height\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTopographic relief height of the spatial position of habitats\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eX5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eEnvironmental factors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRivers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eThe distance of habitats from the adjacent rivers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eX6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVegetation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVegetation type of habitats\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eX7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSoil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSoil type of habitats\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eX8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLand utilization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eland use type of habitats\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eX9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eClimate factors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTemperature\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAverage annual temperature of habitats\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eX10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePrecipitation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAverage annual precipitation at habitats\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eX11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSunshine uration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAverage annual sunshine duration of habitats\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eX12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWind speed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAverage annual wind speed at habitats\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eX13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSocial factors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHuizhou ancient roads\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eThe distance of habitats from the adjacent Huizhou ancient roads\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eX14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHighways\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eThe distance of habitats from the adjacent highways / county highways\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eX15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e1.2.2 Geographic detector model\u003c/h2\u003e \u003cp\u003eThe geographical detector method, as delineated by its foundational work [39], primarily focuses on discerning the characteristics of spatial differentiation. By examining the coupling of variables' spatial distribution, this method identifies potential causal relationships between variables, thereby shedding light on their driving factors. The method encompasses four detectors: risk detection, factor detection, ecological detection, and interactive detection [40]. In this paper, emphasis is placed on factor detection and the Interaction detector method. Widely applied across various disciplines, including natural and social sciences, the geographical detector method serves to investigate the influencing mechanisms underlying the spatial distribution of settlements. This research approach offers several advantages, notably its ability to circumvent the limitations associated with statistical variables and its minimal reliance on presupposed conditions, rendering it relatively objective.\u003c/p\u003e \u003cp\u003eFactor detection, a key component of the geographical detector method, primarily aims to identify the driving forces behind the spatial distribution of settlements and assesses the extent to which a factor elucidates the spatial differentiation of settlements. This assessment is quantified by the q value [40], expressed as follows:\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$q=1-\\frac{\\sum _{ℎ=1}^{L}{N}_{ℎ}{\\sigma }_{ℎ}^{2}}{N{\\sigma }^{2}}= \\frac{SSW}{SST}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThe parameter \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(ℎ (\\text{1,2},\\dots , L)\\)\u003c/span\u003e\u003c/span\u003e denotes the number of influencing factor (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\varvec{X}\\)\u003c/span\u003e\u003c/span\u003e), wherein \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{N}}_{\\varvec{h}}\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\varvec{N}\\)\u003c/span\u003e\u003c/span\u003e signify the number of samples and the total number of samples within class \u003cb\u003eh\u003c/b\u003e, respectively. Additionally,\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{\\sigma }}_{\\varvec{h}}^{2}\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{\\sigma }}^{2}\\)\u003c/span\u003e\u003c/span\u003e represent the sum of variances and the sum of total variances in layer h, respectively. The terms \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\varvec{S}\\varvec{S}\\varvec{W}\\)\u003c/span\u003e\u003c/span\u003e(Within Sum of Squares) and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\varvec{S}\\varvec{S}\\varvec{T}\\)\u003c/span\u003e\u003c/span\u003e (Total Sum of Squares) denote the sum of variances and the sum of total variances within layer h, respectively [41].The parameter \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\varvec{q}\\)\u003c/span\u003e\u003c/span\u003e signifies the degree of influence factor on the spatial distribution of settlements, ranging from \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(0\\)\u003c/span\u003e\u003c/span\u003e to \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(1\\)\u003c/span\u003e\u003c/span\u003e. A value of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\varvec{q}\\)\u003c/span\u003e\u003c/span\u003e closer to \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(1\\)\u003c/span\u003e\u003c/span\u003e indicates a stronger influence of the factor on settlement distribution, while values tending towards \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(0\\)\u003c/span\u003e\u003c/span\u003e suggest a weaker influence of the factor on settlement distribution.\u003c/p\u003e \u003cp\u003eThe interactive detection aspect of geographical detectors primarily aims to discern the interaction between different impact factors. This entails examining whether the explanatory power of the dependent variables is enhanced or diminished when two factors operate in tandem [40]. In this paper, single-factor detection and double-factor interaction detection are conducted to ascertain the degree of influence of the combined interaction of factors on the spatial distribution of traditional settlements in Huizhou.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e1.2.3 Fuzzy synthetic evaluation method\u003c/h2\u003e \u003cp\u003eFuzzy comprehensive evaluation is a comprehensive assessment technique grounded in fuzzy mathematics, which delineates ambiguous boundaries using membership degrees [42]. In this study, the SPSSPRO network platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.spsspro.com/\u003c/span\u003e\u003cspan address=\"https://www.spsspro.com/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) is employed for fuzzy weighted evaluation, utilizing the weighted average type (M(*,+)) operator method for computation. The fuzzy comprehensive evaluation model is depicted as follows:\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$B=A\\times R=\\left({a}_{1},\\dots ,{a}_{n}\\right)\\times \\begin{array}{ccc}{r}_{1}^{1}\u0026amp; \\dots \u0026amp; {r}_{1}^{m}\\\\ ⋮\u0026amp; \\ddots \u0026amp; ⋮\\\\ {r}_{n}^{1}\u0026amp; \\dots \u0026amp; {r}_{n}^{m}\\end{array}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e,\u003c/p\u003e \u003cp\u003eIn this context, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\varvec{B}\\)\u003c/span\u003e\u003c/span\u003e represents the equivalent fuzzy subset, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\varvec{A}\\)\u003c/span\u003e\u003c/span\u003e denotes the factor set, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\varvec{R}\\)\u003c/span\u003e\u003c/span\u003e signifies the review set. The parameters \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\varvec{m}\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\varvec{n}\\)\u003c/span\u003e\u003c/span\u003e represent the number of review grades and factors, respectively, while \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{a}}_{\\varvec{i}}\\)\u003c/span\u003e\u003c/span\u003e\u003cb\u003e(\u003c/b\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\varvec{i}=\\text{1,2},3...,\\varvec{n}\\)\u003c/span\u003e\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e stands for the weight coefficient \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\varvec{q}\\)\u003c/span\u003e\u003c/span\u003e assigned to each index. Furthermore, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{r}}_{\\varvec{n}}^{\\varvec{m}}\\)\u003c/span\u003e\u003c/span\u003e represents the membership degree of each factor to the review set. The weight ratio for the \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(15\\)\u003c/span\u003e\u003c/span\u003e indexes was derived through normalization processing, thereby facilitating the construction of the evaluation model for the habitability of Huizhou traditional settlements.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e1.3 Data sources\u003c/h2\u003e \u003cp\u003eThe pertinent foundational data were sourced from reputable repositories such as the Resources and Environmental Science Data Center at the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.resdc.cn/\u003c/span\u003e\u003cspan address=\"http://www.resdc.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), as well as the National Data Center for Earth System Science (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.geodata.cn/\u003c/span\u003e\u003cspan address=\"http://www.geodata.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and other relevant databases. Subsequently, all datasets underwent meticulous calibration and processing within the ArcGIS 10.8 environment. The spatial reference utilized throughout the analysis adhered to the GCS-WGS-1984 geographic coordinate system, ensuring consistency and compatibility across all spatial analyses (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSources and processing of research data\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eData\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eData type\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eData resources\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eData processing\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElevation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30m national elevation data\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGeospatial data cloud\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIn ArcGIS, clipping or mask extraction tools are used to obtain the elevation data of the study area. Based on the elevation data, data extraction and analysis are carried out on slope, slope direction and topographic relief\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWater system and roads\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMap of river network and roads in China\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eResources and Environmental Science and Data Center, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIn ArcGIS, the tailoring tool is used to obtain water system and road data in the study area, and then the density analysis tool is used to analyze the water system and road\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1:1\u0026nbsp;million spatial distribution map of soil types\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eIn ArcGIS, clipping or mask extraction tools are used to extract soil, vegetation, geomorphic type, land use type and meteorological distribution data\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMap of vegetation type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1:1\u0026nbsp;million spatial distribution map of vegetation types\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGeomorphic type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1: 100,000 spatial distribution map of geomorphic types\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLand-use type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1: 100,000 land-use types (1980s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eResource and Environmental Science data Registration and Publication system, citation data papers [43,44]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeteorological data\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAverage annual temperature, Precipitation, sunshine, Wind Speed (1960\u0026ndash;2021)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHuizhou ancient roads\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAncient road map in Huizhou region\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eTraffic History of Huizhou Region\u003c/em\u003e, etc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAccording to the literature records, the routes of ancient roads are matched, and the density of ancient roads and settlements is analyzed\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn ArcGIS, the process involves utilizing clipping or mask extraction tools to acquire elevation data within the study area. Subsequently, leveraging this elevation data, extraction and analysis procedures are conducted to derive insights into slope, slope direction, and topographic relief. Furthermore, ArcGIS is employed to extract soil, vegetation, geomorphic type, land use type, and meteorological distribution data. This entails utilizing clipping or mask extraction tools to isolate and extract the relevant data layers for further analysis and interpretation.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results and analysis","content":"\u003cp\u003eUtilizing the geographic detector model, this study investigates 15 factors influencing the spatial distribution of traditional settlements in Huizhou. Employing the natural breakpoint method within Arc GIS, the analysis aims to elucidate the extent of influence exerted by each factor on the spatial arrangement of settlements. Subsequently, the fuzzy comprehensive evaluation method is employed to develop a comprehensive assessment of human settlement suitability in the Huizhou region.\u003c/p\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n\u003ch2\u003e2.1 Influencing factors of spatial distribution of Huizhou settlements\u003c/h2\u003e\n\u003cp\u003eThe distribution of traditional settlements in Huizhou is influenced by numerous factors. Through quantitative analysis utilizing the geographical detection model and interactive detection, this study obtained the q-values representing the influence degree of each factor on the spatial distribution of settlements. Additionally, the analysis assessed the influence degree of the combined action of all factors on the spatial distribution of traditional settlements in Huizhou, as illustrated in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe analysis reveals variations in the degree of influence of each factor on the spatial distribution of traditional settlements in Huizhou, as indicated by the respective q-values, ranked from highest to lowest intensity. Specifically, the factors exerting the strongest influence are X11 precipitation (0.34613), followed by X7 vegetation (0.21925), X4 landform (0.11230), X13 wind speed (0.10814), X9 land use type (0.08067), X14 ancient road (0.07603), X10 air temperature (0.05703), and X13 wind speed (0.10814). Subsequently, the influence diminishes in the following order: X12 sunshine (0.04484), X8 soil (0.03467), X1 elevation (0.03349), X15 highway (0.03107), X3 aspect (0.02841), X6 river (0.02268), X5 topographic relief (0.01998), and X2 slope (0.01311).\u003c/p\u003e\n\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eNumber and proportion of influencing factor\u0026rsquo;s settlements Continued Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e Number and proportion of influencing factor\u0026rsquo;s settlements\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eFactor code\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eFactor name\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eInterval\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eNumber of habitats\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003epercentage(%)\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eX6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eRivers\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e[1234, 2420)m\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e83\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e21.39\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e[2420, 4547)m\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.06\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eX7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eVegetation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCultivated vegetation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e115\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e29.64\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSubtropical coniferous forest\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e145\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e37.37\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eShrub vegetation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e65\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e16.75\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTussock vegetation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e39\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e10.05\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSubtropical, temperate deciduous, evergreen, mixed broad-leaved forest, subtropical, tropical bamboo forest and bamboo cluster\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6.19\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eX8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eSoil\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRed soil, yellow soil\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e260\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e67.01\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePaddy soil\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e16.49\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSkeleton soil\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e32\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e8.25\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLime (rock) soil, purple soil, stony soil\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e31\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7.99\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYellow brown soil, dark yellow brown soil\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.26\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eX9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eLand-use\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFarmland\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e140\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e36.08\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eForest land\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e189\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e48.71\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGarden plot\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.09\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePasture land, grass land\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e45\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e11.60\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOthers\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.52\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eX10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eTemperature\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e[8.2\u0026deg;, 14.6\u0026deg;)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7.73\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e[14.6\u0026deg;, 15.5\u0026deg;)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e71\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e18.30\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e[15.5\u0026deg;, 16.0\u0026deg;)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e81\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e20.88\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e[16.0\u0026deg;, 16.6\u0026deg;)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e125\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e32.22\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e[16.6\u0026deg;, 18.1\u0026deg;)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e81\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e20.88\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eX11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eAmount of precipitation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e[1578, 1722)mm\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e147\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e37.89\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e[1722, 1825)mm\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e89\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e22.94\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e[1825, 1915)mm\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e48\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e12.37\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e[1915, 1996)mm\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e89\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e22.94\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e[1996, 2219)mm\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.87\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eX12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eSunlight duration\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e[1708, 1723)h\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e91\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e23.45\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e[1723, 1733)h\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e70\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e18.04\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e[1733, 1745)h\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e97\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e25.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e[1745, 1760)h\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e83\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e21.39\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e[1760, 1851)h\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e47\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e12.11\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eX13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eWind speed\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e[1.4, 1.7)m/s\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e42\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e10.82\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e[1.7, 2.0)m/s\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e229\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e59.02\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e[2.0, 2.2)m/s\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e86\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e22.16\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e[2.2, 2.5)m/s\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e29\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7.47\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e[2.5, 3.6)m/s\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.52\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eX14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eHuizhou Ancient roads\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e[0, 780)m\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e106\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e27.32\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e[780, 2245)m\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e82\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e21.13\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e[2245, 4993)m\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e91\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e23.45\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e[4993, 10152)m\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e73\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e18.81\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e[10152, 19835)m\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e36\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e9.28\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eX15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eHighways\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e[0, 528)m\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e94\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e24.23\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e[528, 1713)m\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e122\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e31.44\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e[1713, 4376)m\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e115\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e29.64\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e[4376, 10358)m\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e55\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e14.18\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e[10358, 23800)m\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.52\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe analysis of q-values highlights the significant influence of precipitation, vegetation, landform, and wind speed, all surpassing the threshold of 0.1. This suggests that these four factors play a pivotal role in shaping the spatial distribution of traditional settlements in the Huizhou area. Further examination of the spatial distribution pattern of influencing factors and settlement points (as depicted in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e and Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e) reveals noteworthy observations. Predominantly, settlement points are concentrated in regions experiencing average annual rainfall ranging from 1578.183 to 1721.512mm and 1721.512 to 1824.607mm, encompassing 60.83% of the total number of settlement points. Given Huizhou's subtropical monsoon climate characterized by ample rainfall, settlement locations tend to avoid high precipitation areas due to the risk of mountain floods. Moreover, the majority of settlement sites are situated within cultivated plant and subtropical coniferous forest-covered areas, constituting 67.01% of all settlement sites. Analysis of landform types reveals a prevalent distribution of settlements in plains, plateaus, hills, and low mountains, totaling 232 settlement points or 59.8% of the total. This trend suggests a preference for low-altitude areas, although settlements also extend into middle and high mountain regions to accommodate the need for expanded living spaces. Furthermore, wind speed emerges as a significant determinant, with settlement points primarily located in areas experiencing moderate wind speeds of 1.7-2.0m/s. This accounts for 59.02% of all settlement points and signifies a preference for regions with moderate wind speeds, as they foster a conducive microclimate environment for habitation.\u003c/p\u003e\n\u003cp\u003eThe q-values associated with land use type, ancient road, air temperature, sunshine, soil, and road range from 0.03 to 0.1, indicating a relatively weaker influence on the spatial distribution of settlements in Huizhou compared to precipitation, vegetation, and landform. Concerning land use types, settlement sites predominantly occupy cultivated land and woodland areas, encompassing 84.78% of all settlement sites. Cultivated land provides essential food security, while woodland contributes to economic value. The relationship between ancient roads and settlements is noteworthy, demonstrating mutual influence. Strong coupling between settlement distribution and ancient road trends is evident, particularly in northern Huizhou, where 48.45% of settlements lie within 2245 meters of ancient roads. Similarly, highways exhibit a close association with settlement distribution, with 85.31% of settlements located within 4,376 meters of highways. This correlation underscores the influence of modern transportation systems on traditional settlements, highlighting their mutual developmental impact. Meteorological elements such as temperature, sunshine, and soil also play crucial roles in settlement location, impacting both the comfort of human settlement environments and crop and vegetation growth. Analysis reveals relatively balanced distribution of settlement points across different annual temperature and sunshine duration areas, indicating that while significant, temperature and sunshine may not be the primary influencing factors. Regarding soil type, settlements predominantly occupy areas with red soil, yellow soil, and paddy soil, comprising 83.51% of all settlement sites. This suggests a preference for soil cover conducive to crop and vegetation growth.\u003c/p\u003e\n\u003cp\u003eSlope direction, slope, and topographic relief are additional factors influencing settlement site selection. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e and Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e illustrate that settlements are distributed predominantly in the south, southeast, and southwest directions, accounting for 43.56% of the total, suggesting a preference for sunny slopes in Huizhou's settlement selection process. Moreover, settlement points exhibit relative equilibrium in their distribution. Analysis of slope and topographic relief reveals that settlements with slopes\u0026thinsp;\u0026lt;\u0026thinsp;15\u0026deg; constitute 52.06% of the total, while those with topographic relief\u0026thinsp;\u0026lt;\u0026thinsp;27 meters comprise 67.01%, indicating a tendency to settle in low-altitude areas such as plains, plateaus, and hills. Despite their significance, slope direction, relief degree, and slope exhibit relatively low influence on Huizhou's settlement distribution compared to other factors, including landform, elevation, and sunshine. Regarding river factors, while they contribute minimally to Huizhou's settlement distribution, settlements tend to be located around rivers, with most situated within 1234 meters of rivers, totaling 76.55%. This phenomenon can be attributed to several reasons. First, Huizhou's subtropical monsoon climate, characterized by annual precipitation of 1100\u0026ndash;2500 mm, ensures abundant rainfall, meeting the region's water needs for both living and agricultural production. Second, Huizhou's dense river network serves as a vital water source for settlements and facilitates transportation within and outside the region. Despite their importance, rivers exert a relatively minor influence on traditional settlement site selection in Huizhou compared to other factors.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab4\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eResults of the interaction probes for each impact factor\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eX1\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eX2\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eX3\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eX4\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eX5\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eX6\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eX7\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eX8\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eX9\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eX10\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eX11\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eX12\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eX13\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eX14\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eX15\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eX1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.03349\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eX2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.16552\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.01311\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eX3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.14096\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.15263\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.02841\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eX4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.19248\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.17230\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.21674\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.11230\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eX5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.14756\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.08842\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.15240\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.16282\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.01998\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eX6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.12663\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.13549\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.14382\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.21236\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.11114\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.02268\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eX7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.28585\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.30030\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.29192\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.36422\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.30539\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.29798\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.21925\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eX8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.11245\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.09500\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.14251\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.18007\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.12083\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.10748\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.31306\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.03467\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eX9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.14391\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.14698\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.17776\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.27247\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.17049\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.13393\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.33309\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.13778\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.08067\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eX10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.11154\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.14882\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.15194\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.23033\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.16511\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.16516\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.33568\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.15626\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.18176\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.05703\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eX11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.46274\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.46026\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.40068\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.55485\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.46095\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.42527\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.50608\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.48112\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.45433\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.52923\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.34613\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eX12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.22330\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.14214\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.14333\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.30168\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.15098\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.15433\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.38728\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.22488\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.19122\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.29055\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.52304\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.04484\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eX13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.20739\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.25131\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.19577\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.27419\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.23148\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.19055\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.41507\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.19566\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.21385\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.24229\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.52364\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.27987\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.10814\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eX14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.16917\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.18553\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.19731\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.30609\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.20512\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.19029\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.34546\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.22972\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.19439\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.21977\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.42317\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.29170\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.27905\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.07603\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eX15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.17803\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.12694\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.13091\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.22458\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.13163\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.14021\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.29657\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.17402\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.15068\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.19823\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.42926\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.15974\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.22181\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.16654\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.03107\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe interactive detection results of the geographical detector, as depicted in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e, reveal that the interaction values of the two factors surpass the single factor q value, ranging from 0.1 to 0.6. This indicates a substantial enhancement in the influence of the two factors on the spatial distribution of traditional settlements in Huizhou following their interaction. Analyzing the specific interaction of impact factors, in single-factor detection, precipitation exhibits the highest q value, with a significant increase observed after interacting with other factors. Notably, the maximum interaction value of 0.55485 occurs between the precipitation and geomorphic factors, underscoring their pivotal influence on traditional settlement location in Huizhou. Similarly, the interaction value of the slope factor, despite having the lowest q value in single-factor detection, experiences a notable increase after interacting with other factors, particularly with precipitation, vegetation, and wind speed, reaching 0.46026, 0.30030, and 0.25130, respectively. This highlights a significant amplification in the influence of the slope factor and other factors on settlement distribution after interaction. In two-factor interaction detection, the interaction value of the sunshine factor exhibits a markedly enhanced feature. While the q value of sunshine in single-factor detection is 0.04484, its interaction with other factors elevates its q value to over 0.14. Notably, interaction values with precipitation, vegetation, landform, and air temperature reach 0.52304, 0.38728, 0.30168, and 0.29055, respectively, indicating the significant impact of sunshine duration, precipitation, landform, and other factors on settlement distribution in Huizhou.\u003c/p\u003e\n\u003cp\u003eThe analysis of factor interaction highlights that the impact of two-factor interaction on traditional settlements in Huizhou surpasses that of single factors. Notably, factors with initially weak influence on settlement location experience a significant enhancement in their influence strength after factor interaction. This suggests that even factors with a q value\u0026thinsp;\u0026lt;\u0026thinsp;0.1 contribute to the influencing factors of the spatial distribution of traditional settlements in Huizhou. Consequently, the spatial distribution of traditional settlements in Huizhou is shaped by the comprehensive influence of multiple factors, underscoring the complexity and multifaceted nature of settlement dynamics in the region.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n\u003ch2\u003e2.2 Evaluation of the suitability of Huizhou traditional settlements environment\u003c/h2\u003e\n\u003cp\u003eThe suitability of the residential environment in traditional settlements in Huizhou was categorized into five levels: very low suitability, low suitability, moderate suitability, high suitability, and very high suitability. This classification aimed to determine the membership degree of each influencing factor. The q value and membership degree derived from the geographical detection results of each factor were incorporated into Formula (2). Subsequently, after normalization, the weights assigned to the 15 influencing factors were determined as follows: 0.045, 0.087, 0.078, 0.094, 0.051, 0.047, 0.074, 0.118, 0.037, 0.050, 0.070, 0.086, 0.084, 0.043, and 0.036, respectively. Consequently, the comprehensive suitability model for the human settlement environment in Huizhou's traditional settlements was established as follows: f(Y)= 0.045 \u0026times; elevation\u0026thinsp;+\u0026thinsp;0.087 \u0026times; slope gradient\u0026thinsp;+\u0026thinsp;0.078 \u0026times; slope aspect\u0026thinsp;+\u0026thinsp;0.094 \u0026times; physiognomy\u0026thinsp;+\u0026thinsp;0.051\u0026times; topographic relief height\u0026thinsp;+\u0026thinsp;0.047 \u0026times; rivers\u0026thinsp;+\u0026thinsp;0.074 \u0026times; vegetation\u0026thinsp;+\u0026thinsp;0.118 \u0026times; soil\u0026thinsp;+\u0026thinsp;0.037 \u0026times; land-use type\u0026thinsp;+\u0026thinsp;0.050 \u0026times; air temperature\u0026thinsp;+\u0026thinsp;0.070 \u0026times; rain temptation\u0026thinsp;+\u0026thinsp;0.086 \u0026times; sunshine\u0026thinsp;+\u0026thinsp;0.084 \u0026times; wind speed\u0026thinsp;+\u0026thinsp;0.043 \u0026times; ancient roads\u0026thinsp;+\u0026thinsp;0.036 \u0026times; highroad. This model delineates the residential environment suitability zoning map for traditional settlements in Huizhou, which is illustrated in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e and summarized in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab5\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eArea and number of settlements by suitability zones\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eHabitat Appropriateness\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eArea(km\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003ePercentage(%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eNumber of settlements (units)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003ePercentage(%)\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eVery low\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e48.79\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.52\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLow\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1359.18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e8.45\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7.73\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMedium\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e9200.63\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e57.22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e189\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e48.71\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHigh\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4921.92\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e30.61\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e137\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e35.31\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eVery high\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e548.95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.42\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7.73\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eBased on the statistical analysis outcomes (see Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e and Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e), it is evident that the region with moderate to high suitability spans 14,671.5 square kilometers, constituting a significant portion of 91.25% of territorial expanse in Huizhou region. Within this area, regions with moderate suitability encompass 30.61%, while those with high suitability account for 34.03%. These findings suggest an overall favorable suitability of Huizhou's human settlements. Regarding the spatial distribution of settlements, 356 settlements are situated within areas categorized as moderate suitability and above, representing a substantial 91.75% of the total settlements. Specifically, settlements within areas characterized by moderate, high, and very high suitability comprise 48.71%, 43.04%, and 0.0% respectively. In contrast, settlements within areas designated as having low to very low suitability constitute a mere 8.25%. This underscores that traditional settlements in Huizhou predominantly inhabit areas with moderate to high suitability, reflecting a strong spatial correlation between settlement distribution and regions with moderate to high suitability.\u003c/p\u003e\n\u003cp\u003eAccording to the comprehensive suitability grade classification results (see \u003cstrong\u003eFig.\u0026nbsp;5\u003c/strong\u003e), areas classified as having low suitability are characterized by specific environmental parameters. These areas typically exhibit elevations ranging from 899 to 1807 meters, characterized by high mountainous terrain. The topographic relief spans from 58 to 326 meters, indicating varied relief within this region. Slope angles fall within the range of 25\u0026deg; to 78\u0026deg;, with predominant slope directions oriented towards the east-north and north-north directions.Vegetation types within these areas include temperate deciduous broad-leaved forest, subtropical deciduous broad-leaved forest, subtropical and tropical bamboo forests, and bamboo clusters, as well as subtropical evergreen and mixed deciduous broad-leaved forests. Soil types consist of lime (rock) soil, purple soil, stony soil, and coarse bone soil. Climatically, the average annual temperature ranges from 8.2\u0026deg; to 12.6\u0026deg;C, while the average annual precipitation falls between 1578.1 and 1721.5 mm. Sunshine duration annually spans from 1708.3 to 1727.3 hours, with an average annual wind speed ranging between 1.4 and 1.7 m/s. Settlement points within these regions are notably distributed away from river systems, ancient roads, and highways, indicating a less favorable location for human settlement.\u003c/p\u003e\n\u003cp\u003eAccording to the comprehensive suitability grade classification, the areas classified as having a low suitability degree exhibit specific environmental characteristics. These regions are characterized by elevations ranging from 612 to 899 meters, representing middle mountainous terrain. The relief degree within this area ranges from 41 to 58 meters, indicating moderate relief. Slope angles fall within the range of 15\u0026deg; to 25\u0026deg;, with predominant slope directions oriented towards the southwest and west.Vegetation types within these areas predominantly consist of subtropical coniferous forests. Soil types include red soil and yellow soil, typical of subtropical regions. Climatically, the average annual temperature ranges from 12.6\u0026deg; to 14.2\u0026deg;C. The average annual precipitation falls between 1721.5 and 1824.6 mm, with an annual sunshine duration spanning from 1727.3 to 1743.6 hours. Additionally, the average annual wind speed ranges from 1.7 to 2.0 m/s. Settlement sites within these regions are relatively distant from river systems, ancient roads, and highways, indicating less favorable conditions for human settlement.\u003c/p\u003e\n\u003cp\u003eAccording to the comprehensive suitability grade classification, the medium suitability areas exhibit specific environmental characteristics conducive to human settlement. These regions are characterized by elevations ranging from 404 to 612 meters, representing low mountainous terrain. The relief degree within this area ranges from 27 to 41 meters, indicating moderate relief. Slope angles fall within the range of 5\u0026deg; to 15\u0026deg;, with predominant slope directions oriented towards the southeast and south. Vegetation types within these areas include subtropical and tropical evergreen broad-leaved and deciduous broad-leaved shrubs. Soil types consist of yellow brown soil and dark yellow brown soil, which are typical of subtropical regions. Climatically, the average annual temperature ranges from 14.2\u0026deg; to 15.4\u0026deg;C. The average annual precipitation falls between 1824.6 and 1915.1 mm, with an annual sunshine duration spanning from 1743.6 to 1762.1 hours. Additionally, the average annual wind speed ranges from 2.0 to 2.2 m/s. Settlement sites within these regions are relatively close to river systems, ancient roads, and highways, indicating favorable conditions for human settlement.\u003c/p\u003e\n\u003cp\u003eThe high suitability areas exhibit distinct environmental characteristics conducive to human settlement. These regions are characterized by elevations ranging from 238 to 404 meters, representing hilly terrain. The relief degree within this area ranges from 14 to 27 meters, indicating relatively gentle relief. Slope angles fall within the narrow range of 2\u0026deg; to 5\u0026deg;, predominantly oriented towards the southeast and east directions. Vegetation types within these areas include temperate grass, subtropical grass, and tropical grass varieties, indicative of favorable conditions for grazing and agriculture. Soil types consist primarily of tidal soil, suitable for agricultural activities. Climatically, the average annual temperature ranges from 15.4\u0026deg; to 16.4\u0026deg;C, creating a mild and favorable climate for human habitation. The average annual precipitation falls between 1915.1 and 1995.6 mm, ensuring sufficient water resources for agricultural and domestic purposes. Furthermore, the annual sunshine duration spans from 1762.1 to 1786.7 hours, providing ample sunlight for agricultural productivity. Additionally, the average annual wind speed ranges from 2.2 to 2.6 m/s, contributing to a comfortable living environment. Settlement sites within these regions are strategically located close to rivers, ancient roads, and highways, facilitating transportation and trade activities, further enhancing their suitability for human settlement.\u003c/p\u003e\n\u003cp\u003eThe high suitability areas exhibit favorable conditions for human settlement and agricultural activities. These regions are characterized by elevations ranging from \u0026minus;\u0026thinsp;86 to 238 meters, indicating predominantly plain and platform landforms. The topographic relief within this area ranges from 0 to 14 meters, showcasing relatively flat terrain conducive to agricultural cultivation. Slope angles fall within the narrow range of 0\u0026deg; to 2\u0026deg;, predominantly oriented towards the northwest and north directions. Vegetation types within these areas include two-crop water-drought grain crops, economic forests, two-crop or three-crop water-drought rotations, and evergreen fruit orchards, facilitating diverse agricultural practices. Soil types consist primarily of paddy soil, suitable for wetland agriculture. Climatically, the average annual temperature ranges from 16.4\u0026deg; to 18.1\u0026deg;C, creating favorable conditions for agricultural productivity. The average annual precipitation falls between 1995.6 and 2219.3 mm, ensuring ample water resources for agricultural irrigation. Furthermore, the annual sunshine duration spans from 1786.7 to 1851.2 hours, providing optimal conditions for crop growth. Additionally, the average annual wind speed ranges from 2.6 to 3.6 m/s, contributing to a comfortable living environment. Settlement sites within these regions are strategically located close to river systems, ancient roads, and highways, facilitating transportation and trade activities, further enhancing their suitability for human settlement and economic development.\u003c/p\u003e\n\u003cp\u003eUpon comprehensive analysis, despite being situated in the mountainous terrain of southern Anhui, the Huizhou area benefits from favorable climatic conditions, an isolated geographical environment, and an extensive river network. These natural attributes collectively contribute to the creation of a conducive living environment. Influenced by various factors such as elevation, slope, slope direction, landform, topographic relief, river distribution, vegetation coverage, soil type, temperature, precipitation, and sunshine duration, traditional settlements in Huizhou are predominantly located in areas exhibiting medium to high suitability for human habitation. Despite the mountainous landscape, the region's favorable living conditions have encouraged its inhabitants to overcome geographical constraints and continuously expand their living spaces.\u003c/p\u003e\n\u003cp\u003eIn sum, the concentration of settlements in regions with favorable environmental conditions underscores the adaptability and resilience of the Huizhou people, who have effectively utilized their natural surroundings to establish thriving communities. This symbiotic relationship between humans and their environment highlights the importance of understanding and preserving the unique geographical and natural features that have shaped the cultural landscape of Huizhou over centuries.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Conclusion and discussion","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Conclusion\u003c/h2\u003e \u003cp\u003eArc GIS and geographic detector were employed in tandem to comprehensively assess the influence of 15 factors, encompassing elevation, slope, landform, river distribution, vegetation coverage, soil type, and precipitation, on the site selection and spatial distribution of traditional settlements in Huizhou. Through this methodological approach, an evaluation of the suitability of the residential environment for traditional settlements in Huizhou was conducted. The key conclusions drawn from this study are summarized as follows:\u003c/p\u003e \u003cp\u003e(1) The overall suitability of traditional settlements in the Huizhou region reveals that the central area exhibits higher suitability compared to the southern and northern regions, following the northeast-southwest spatial differentiation pattern typical of mountain ranges. Particularly, higher elevation mountain ranges exert a more pronounced impact on settlement suitability.\u003c/p\u003e \u003cp\u003e(2) In Huizhou, areas deemed highly suitable for human settlements cover 5470.87 km2, constituting 34.03% of the region; those with moderate suitability span 9200.63 km2, accounting for 57.22%; and those with low suitability encompass 1407.97 km2, representing 8.75%. Notably, regions with moderate suitability and above account for 91.25%, suggesting an overall favorable suitability for human settlements in the Huizhou area.\u003c/p\u003e \u003cp\u003e(3) Regarding the spatial distribution of traditional settlements in Huizhou, 167 settlements are situated in highly suitable areas, comprising 43.04% of the total; 189 settlements are in moderately suitable areas, making up 48.71%; and 32 settlements are located in areas with low suitability, accounting for 8.25%. Impressively, 91.75% of traditional villages are found in regions with moderate or higher suitability, predominantly in plains, platforms, hills, and low mountains boasting rich soil, abundant vegetation, and favorable climatic conditions. Additionally, the unique geographical landscape, characterized by numerous mountains and limited land, encouraged Huizhou ancestors to overcome environmental constraints and expand their living spaces, leading to the distribution of some traditional villages in less suitable areas.\u003c/p\u003e \u003cp\u003e(4) Among the 15 influencing factors, including elevation, slope, landform, river distribution, vegetation coverage, precipitation, and wind speed, precipitation, vegetation, landform, and wind speed exert a substantial influence on the spatial distribution of traditional settlements in Huizhou, with precipitation being the most impactful. Conversely, factors such as land use, ancient roads, air temperature, sunshine, soil, elevation, and roads exhibit relatively weaker effects. However, slope direction, river distribution, relief degree, and slope demonstrate minimal influence on settlement distribution. Overall, ensuring access to essential land resources for survival and facilitating regional economic development through activities like tea cultivation and forestry are primary considerations for selecting traditional settlement sites in Huizhou.\u003c/p\u003e \u003cp\u003e(5) Analysis of detection results reveals variations in the degree of influence of individual factors on the distribution of traditional settlements in Huizhou. However, interactive detection outcomes indicate that the interaction between any two factors surpasses the influence of a single factor and is significantly enhanced, underscoring the collective and amplified influence of multiple factors on traditional settlement locations in Huizhou. Therefore, a comprehensive analysis of several factors is essential for accurately assessing and dividing the suitability of the regional human settlement environment in Huizhou.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Discussion\u003c/h2\u003e \u003cp\u003eThe analysis of the relationship between humans and the environment underscores the profound impact of natural ecological factors on the spatial distribution of traditional settlements in the Huizhou area. The guiding principles of Huizhou ancestors, emphasizing \"respecting nature, protecting nature, and utilizing nature,\" form the foundational tenet governing the construction of the human settlement environment in the region. The simplistic yet powerful concept of \"harmony between nature and man\" is inherently embedded in the fabric of Huizhou's regional human settlement environment. To safeguard traditional settlements in Huizhou, it becomes imperative to fortify the protection of the ecological environment that serves as the bedrock for their existence. Leveraging the favorable climatic conditions of southern Anhui, deliberate efforts should be made to cultivate conducive vegetation communities and habitat conditions. This strategic approach aims to mitigate the impact and mitigate the risks of geological disasters resulting from environmental shifts on the human settlement environment. In doing so, it seeks to propel the profound inheritance and development of the traditional settlement culture in Huizhou. By building upon the solid foundation of the traditional living environment characterized by \"back mountain - surrounding water - surface screen,\" an enhanced and harmonious living ecological and cultural environment can be meticulously crafted.\u003c/p\u003e \u003cp\u003eThis study delves into the suitability evaluation of traditional settlements in the mountainous Huizhou of southern Anhui province, focusing on natural elements using geographical detectors. Its aim is to offer insights that can inform the preservation and development of mountain settlements not only in Huizhou but also across China. Recognizing the inherent limitations in accessing historical data, this paper concentrates on examining the influence of natural environmental factors on settlement patterns and human habitat construction. It acknowledges that traditional human settlements are subject to multifaceted influences encompassing nature, society, economy, and culture. While this may affect the precision of the evaluation results regarding settlement suitability, it underscores the complexity of settlement dynamics. Future endeavors in the realm of traditional settlement construction will necessitate comprehensive evaluations and scientifically grounded predictions considering the interplay of human, social, economic, and natural ecological factors.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eFund Projects\u003c/strong\u003e \u003cp\u003eAnhui Provincial Key Laboratory of Regional Culture and Smart Tourism Integration Effect Key Project (WLSYS202304), Anhui Provincial Philosophy and Social Science Research Key Project (2023AH051351, SK2020A0464).\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization, H. L. and Y.L.; Methodology, H.L and Z. B.; Data curation, Y. G. and J. W.; Writing\u0026mdash;original draft, Z.B., Y.G., and J.W.; Writing\u0026mdash;review and editing, Y.L. and H.L.; Supervision, Y.L. and H.L.; All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and/or analysed during the current study are available public in the Chinese Academy of Sciences (http://www.resdc.cn/), the Ministry of Housing and Urban-Rural Development and the State Administration of Cultural Heritage (https://www.mohurd.gov.cn/), and the National Data Center for Earth System Science (http://www.geodata.cn/). The specific information and sources of the data used are detailed in the last paragraph in Section 1.1 and Table 2 of the submitted manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eXUE L P. An Introduction to the Preservation of Architectural Heritage (2nd Edition). Beijing: Building Industry Press, 2017: 24\u0026ndash;39.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMinistry of Urban and Rural Development, Ministry of Culture on Request for Announcement of the Second Batch of National Historical and Cultural Cities. State Council of the People\u0026rsquo;s Republic of China, Bulletin, 1986, (35): 1075\u0026ndash;1086.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu S Y, Cheng G Q. The Road to Rural Revitalization in China: Theory, Institutions and Policy. Beijing: Science Press, 2021: 107\u0026ndash;132.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNotice of the Ministry of Housing and Urban-Rural Development, Ministry of Culture, State Administration of Cultural Heritage, and Ministry of Finance on Carrying out Surveys on Traditional Villages. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.gov.cn/zwgk/2012-04/24/content_2121340.htm\u003c/span\u003e\u003cspan address=\"https://www.gov.cn/zwgk/2012-04/24/content_2121340.htm\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, 2014-02\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZHOU G H, LONG H L, LIN W L, et al. Theoretical debates and practical development of the \"three rural issues\" and rural revitalization in the New Era. Journal of Natural Resources, 2023,38(08):1919\u0026ndash;1940.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDING J, WANG R M. Understanding the Spatial Pattern of Historical Chinese Rural Settlements: A Syntactical Approach. Journal of Human Settlements in West China, 2023, 38(5): 103\u0026ndash;109.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCHEN C, LI B H, WANG M Z. Historical Evolution of the Space Form of Traditional Settlements influenced by Temples in Inner Mongolia Autonomous Region since the Qing Dynasty: A Case Study of Bailingmiao Town. Economic Geography, 2023,43(11):220\u0026ndash;228.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePEI Y F. The Research of Huizhou Traditional Village Group. Nanjing: Southeast University,2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCHEN Q T, ZHANG L, DUAN Y P. Spatial-temporal pattern and evolution of traditional villages in Jiangxi province. National Remote Sensing Bulletin, 2021,25(12): 2460\u0026ndash;2471\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQIU Z Z, HU X J, QIAN H, et al. Spatiotemporal Distribution Characteristics and Influencing Factors of Traditional Villages in Fujian Province. Economic Geography, 2023,43(06):211\u0026ndash;219.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYANG Y, HU J, LIU D J, et al. Spatial differentiation of ethnic traditional villages in Guizhou province and the influencing factors. Journal of Arid Land Resources and Environment, 2022,36(02):178\u0026ndash;185.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYUAN J Y, HUANG L Y, YAO S, et al. Study on Spatial Distribution Characteristics and Influence Mechanism of Traditional Villages in Hebei Province. Territory \u0026amp; Natural Resources Study, 2023,(06):42\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTANG M G, HU J, TANG X F, et al. Geographical pattern and differentiational mechanism of ancient villages in Guizhou province. Journal of Arid Land Resources and Environment, 2022,36(11):158\u0026ndash;167.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSHI Y W, ZHU X G, SUN J, et al. Spatial Distribution Characteristics and Influencing Factors of Traditional Villages in Yunnan Province. Resource Development \u0026amp; Market, 2022,38(07):809\u0026ndash;817.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDONG P, ZHOU X N, et al. Study on Spatial Distribution Characteristics and Influencing Factors of Historical and Cultural Towns and Villages in the Yangtze River Economic Belt. Geography and Geo-Information Science, 2022,38(03):66\u0026ndash;73.8(03):66\u0026ndash;73.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJU X X, YANG C C,ZHAO M W, et al. Spatial Distribution Characteristics and Influencing Factors of Traditional Villages in Zhejiang, Anhui, Shaanxi, Yunnan Provinces. Economic Geography, 2022,42(02):222\u0026ndash;230.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYIN L C, LIU P L. Type expression and spatial differentiation of planar archetype genes of traditional dwellings of the Xiangjiang River Basin. Geographical Research, 2023,42(08):2191\u0026ndash;2210.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYANG L G, HU Y L, WU X F, et al. Cultural landscape gene production process and mechanism of Dong traditional village:A case study of Huangdu village. Journal of Natural Resources, 2023,38(05):1164\u0026ndash;1177.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCHENG J J, YAN Y, HU X F, et al. Construction of Spatial Gene Map of Traditional Villages, Anhui Province. Planners, 2022,38(12):65\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYIN LC, LIU P L, LI B H, et al. Map of traditional settlement landscape morphology gene: A case study of the Xiangjiang River Basin. Scientia Geographica Sinica,2023,43(6):1053\u0026ndash;1065.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWANG Y S, ZHANG Z H. Construction of Local Knowledge Graph of Traditional Cave Dwelling Settlement Landscape: A Case Study of Northern Shaanxi. Landscape Architecture,2023,30(08):103\u0026ndash;110.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLI B H, LI Z, LIU P L, et al. Landscape gene variation and differentiation law of traditional villages in Xiangjiang River Basin. Journal of Natural Resources, 2022,37(02):362\u0026ndash;377.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTIAN L, SHI B X, SUN F Z, et al. Spatial correlation between traditional villages and intangible cultural heritage in the Yellow River Basin. Journal of Arid Land Resources and Environment, 2023,37(03):186\u0026ndash;19.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLI R Y, SHI Z Y. Spatial Dislocation and Mechanism of the Distribution of Traditional Villages and Intangible Cultural Heritage in the Y angtze River Economic Belt. Geography and Geo-Information Science, 2022,38(05):129\u0026ndash;137.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCHEN X Y, HUANG R, HONG X T, et al. The measurement of xiangchou and its resource value in traditional village tourism destinations: A case study in Southern Jiangsu. Journal of Natural Resources, 2020,35(07):1602\u0026ndash;1616.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXU Shaohui, DONG Liping. Spatial Distribution and Tourism Activation of Traditional Villages in Yunnan Province[J]. Journal of Resources and Ecology,2022,13(05):851\u0026ndash;859.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCHEN B, XU S Z, ZHOU Y Y, et al. Analysis of Multi scale Characteristics and Influencing Factors Under the Spatial Distribution of Traditional Villages - Taking 263 Traditional Villages in Guangdong Province as Examples. Research of Soil and Water Conservation, 2023,30(01):423\u0026ndash;429.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFANG Y L, LU H Y, HUANG Z F, et al. Spatiotemporal Distribution of Chinese Traditional Villages and Its Influencing Factors. Economic Geography, 2023,43(09):187\u0026ndash;196.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFAN L, ZHANG D Y. Study on Spatial Differentiation Characteristics and Influencing Factors of Traditional Villages in North China Based on MGWR Model. Chinese Landscape Architecture, 2022,38(10):56\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJIN Z T, PRI Y F, GONG K. From Village Form to Traditional Residential Space: Survey and Mapping of Huizhou Villages with Layered Focuses. Heritage Architecture, 2021,(01):52\u0026ndash;59.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWANG Y. A Study on the Morphology of Imaginary Planes in Huizhou Ancient Villages from the Perspective of Flood Control. Jiang-huai Tribune, 2018,(01):155\u0026ndash;160.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKONG X, ZHUO F Y, MIAO C S. Influence of Tourism Development on Traditional Local Culture Preservation: Based on the Field Work in Hongcun, Chengkan and Xucun Villages. Tropical Geography, 2016,36(2):216\u0026ndash;224.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLI J L, CHU J L, LI Y. Reseach on the Spatial Distribution Pattern and Protection and development of Ancient Huizhou Traditional Villages. Chinese Journal of Agricultural Resources and Regional Planning, 2019,40(10):101\u0026ndash;109.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYUAN C, KONG X, LI L Q, et al. Traditional Village Image Perception Research Based on Tourist UGC Data: A Case of Chengkan Village. Economic Geography, 2020,40(08):203\u0026ndash;211.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuangshan City Local Records Committee. Huangshan City Records (~\u0026thinsp;2006). Hefei: Huangshan Bookstore, 2010:37\u0026ndash;113.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXIA X Y, CHEN H M, GAO Q, et al. A Study on Temporal and Spatial Variations of Suitability of Urban Living Environment in Jiangsu Province Based on a Geographical Detector [J]. Bulletin of Soil and Water Conservation, 2020,40 (3):289\u0026ndash;296.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDU X Y, HU X J, JIN X L, et al. Evaluation of human settlement environment suitability of Neolithic settlement sites in Hunan Province based on geographical detector. Journal of Earth Environment, 2020,40(08):203\u0026ndash;211.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCao F, Ge Y, Wang J F. Optimal discretization for geographical detectors- based risk assessment[J]. GIScience\u0026amp; Remote Sensing, 2013,50(1): 78\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCao F, Ge Y, Wang J F. Optimal discretization for geographical detectors- based risk assessment[J]. GIScience\u0026amp; Remote Sensing, 2013,50(1): 78\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWANG J F, XU C D. Geodetector: Principle and Prospective. Acta Geographica Sinica, 2017,72(1):116\u0026ndash;134.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCUI Z H, YAN Y. A GIS-based Research on the Spatial Evolution Characteristics and Influence Mechanism of the Rural Settlements in City Island: A Case Study of Baguazhou in Nanjing. Modern Urban Research, 2020(2):90\u0026ndash;97.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYIN X Y, SONG S M, YAN G H, et al. Construction and application of aquatic ecological risk assessment model for Dongting Lake. Water Resources and Hydropower Engineering, 2022, 53(S1): 45\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXU X L. China\u0026rsquo;s 1 Million Land Use Data in the 1980s. Resource Environmental Science Data Registration and Publishing System (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.resdc.cn/DOI)\u003c/span\u003e\u003cspan address=\"http://www.resdc.cn/DOI)\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, 2023. DOI: 0.12078/2023010202.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXU X L. Annual Spatial Interpolation Dataset of Meteorological Elements in China. Resource Environmental Science Data Registration and Publishing System (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.resdc.cn/DOI)\u003c/span\u003e\u003cspan address=\"http://www.resdc.cn/DOI)\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, 2023. DOI: 0.12078/2023010202.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Huizhou region, traditional settlements, geographic detector, human living environment, suitability evaluation","lastPublishedDoi":"10.21203/rs.3.rs-4475062/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4475062/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study aims to establish an evaluation system for human settlement suitability utilizing geographic detectors, focusing on traditional human settlements in Huizhou region, situated in the southern region of Anhui province, China. Our research reveals several key findings: 1. Central Huizhou exhibits higher overall suitability for traditional human settlements compared to its southern and northern counterparts, with a predominant northeast-southwest spatial differentiation pattern following the mountainous terrain. 2. Approximately 34.03% of the Huizhou is deemed highly suitable for human settlement, while 57.22% is considered moderately suitable, and 8.75% is classified as low suitability. Notably, areas of medium and higher suitability collectively constitute 91.25% of the region, indicating a favorable overall suitability for human settlements. 3. Among traditional settlements, 91.75% are situated in areas classified as medium and above suitability, primarily encompassing plains, plateaus, hills, and low mountains characterized by fertile soil, abundant vegetation, ample precipitation, and favorable climatic conditions. 4. Factors such as precipitation, vegetation, landform, and wind speed exert a significant influence on the spatial distribution of traditional settlements in Huizhou, while others demonstrate comparatively weaker effects. Additionally, the interaction between any two factors exhibits a stronger impact on settlement distribution than individual factors, highlighting the complex interplay of multiple factors in site selection. This study provides valuable insights into the relationship between mountainous traditional settlement site selection and the natural environment, offering guidance for the development of human settlement environments in similar mountainous regions.\u003c/p\u003e","manuscriptTitle":"A Study on the Evaluation of Habitat Appropriateness of Huizhou Traditional Settlements","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-12 19:21:17","doi":"10.21203/rs.3.rs-4475062/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-10-28T07:35:43+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-26T20:42:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"211649336928590766022901063509343441449","date":"2024-10-14T06:47:12+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-13T20:02:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"71821844993332433063583807687754616575","date":"2024-08-02T08:22:47+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-02T07:54:46+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-02T07:46:45+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-05-29T15:03:57+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-29T05:37:51+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-05-25T04:10:13+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5721887d-c8ed-4780-88cd-c6a3a6bac71c","owner":[],"postedDate":"June 12th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":33004815,"name":"Earth and environmental sciences/Environmental sciences"},{"id":33004816,"name":"Earth and environmental sciences/Environmental social sciences"}],"tags":[],"updatedAt":"2025-08-04T16:43:04+00:00","versionOfRecord":{"articleIdentity":"rs-4475062","link":"https://doi.org/10.1038/s41598-025-13268-w","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-08-01 16:13:21","publishedOnDateReadable":"August 1st, 2025"},"versionCreatedAt":"2024-06-12 19:21:17","video":"","vorDoi":"10.1038/s41598-025-13268-w","vorDoiUrl":"https://doi.org/10.1038/s41598-025-13268-w","workflowStages":[]},"version":"v1","identity":"rs-4475062","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4475062","identity":"rs-4475062","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}