Analysis and Reconstruction Method of Spatial Characteristics of Traditional Chinese Villages Based on Parameterization

Analysis and Reconstruction Method of Spatial Characteristics of Traditional Chinese Villages Based on Parameterization | 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 Analysis and Reconstruction Method of Spatial Characteristics of Traditional Chinese Villages Based on Parameterization Yong Fan, Xuan Li, Wen-jie Xiao, Di Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4072347/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract In recent years, the rapid development of computer-aided planning and design technology has provided a new perspective for the study of complex problems such as the generation of architectural complex forms. This study focuses on how to apply parameterization technology to analyze and articulate traditional spatial form composition rules, aiming to minimize reliance on subjective human judgment in the protection and renewal design of the historical style of traditional villages. It aims to establish digital generative design tools to address the challenges of accurately inheriting and innovatively utilizing historical and cultural information in traditional settlements. It introduces how to rely on parameterization technology to analyze the spatial form composition rules, parameter extraction rules, and spatial reconstruction rules of traditional villages, facilitating the complete process from spatial features to parameterization rules, and then to the application of computational methods to deduce spatial features. It also includes case studies demonstrating the application of parameterization technology tools for village protection and explores the role of generative design tools in preserving the spatial style of these settlements. Physical sciences/Engineering/Civil engineering Earth and environmental sciences/Environmental social sciences/Sustainability traditional Chinese villages spatial feature extraction parametric design digital generative design village reconstruction cultural heritage preservation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Figure 14 Figure 15 Figure 16 1. Introduction Traditional Chinese villages are a vital legacy of China’s agricultural civilization, embodying the historical memory of the nation and encompassing rich historical information and cultural landscapes. Spatial style is a key landscape resource of traditional Chinese villages and serves as a spatial carrier that reflects the historical and cultural traits of these villages. Understanding the value of traditional Chinese villages and preserving their spatial features and cultural elements are crucial for the innovation and continuation of Chinese civilization in the new era. Under the current new technological context and social development conditions, the protection and renewal of traditional Chinese villages face two problems. Firstly, how should traditional villages’ spatial feature information be identified and accurately transmitted? The spatial style of traditional villages has been severely impacted by China’s rapid urbanization. The integrity of spatial style and continuity of cultural inheritance have been disrupted, leading to a loss of spatial form characteristics and cultural functions [ 1 ]. Protecting traditional villages is a significant challenge in the urbanization process. The difficulties arise mainly from the mainstream planning model’s lack of detailed analysis and application of the internal dynamics of traditional village spatial forms. This is evident in the absence of precise quantitative analysis tools, efficient spatial form design technologies, and dynamic planning methods. To address this, it is essential to objectively identify and extract spatial feature information from traditional villages. Constructing a comprehensive information system and expressing this information through computer-recognizable coding methods is necessary. The second problem is how to effectively utilize traditional villages’ spatial feature data. Advancements in data technology have led to an increase in digital research on traditional villages, transitioning from manual to digital preservation methods [ 2 ]. Image recognition and spatial information databases for traditional villages are maturing [ 3 ]. However, the application of digital technology in village protection often stops at data visualization. The acquisition of extensive data enables the accurate transmission of historical and cultural information, crucial for restoring incomplete spatial features and reconstructing spatial textures [ 4 ]. Data mining is required to understand the objective rules behind the visual aspects. Relying solely on static guidelines or dynamic visualizations from data organization is insufficient. The deepening of data technology and artificial intelligence research has made the parametric extraction of spatial information features and the automatic generation of protection schemes for traditional villages an important research direction and practical approach [ 5 – 9 ]. Parametric design is a computer-aided technology based on processes and rules, which utilizes computer automation to execute manually formulated logical processes and generate rules, and quickly output specific content generation methods. This method is widely used in the field of computer graphics for virtual world synthesis modeling. In the field of spatial planning and design, parametric design was first widely applied in the nonlinear design of buildings, especially in the design of building skins, and gradually spread to the fields of urban design and urban spatial planning [ 10 ]. Based on parameterized computer-aided planning and design, the relevant processes and rules are based on mature design logic, and the interpretability of scheme generation is strong. The method based on process and rules is also convenient for carrying a powerful human-computer interaction interface, which can adjust generation conditions and modify generation results in real time, and the generation process is highly controllable. Parameterization has become an important development direction for computer-aided planning and design in the fields of architectural design and urban-rural planning. At present, the exploration of parameterization technology in urban and rural planning and design practice mainly involves the simulation of urban architectural group form, the simulation of urban overall structural form, and the design of urban road network form[ 11 – 14 ]. Most of the existing practical research has focused on the field of urban design, and its application in the planning and design of rural settlement spatial forms is close to blank. This article is an exploration of this blank field. The research on traditional Chinese villages mainly focuses on the analysis and excavation of spatial features and architectural construction characteristics [ 15 – 18 ], the management mechanism for the protection and utilization of traditional villages [ 19 – 21 ], the paths for the protection and renewal of traditional villages [ 22 – 23 ]. Practical research on the application of parameterization techniques in the planning and design of rural settlement spatial forms is limited. Parameterized research on traditional villages mainly focuses on parametric design of street and alley spaces [ 24 ], quantitative analysis of spatial texture [ 25 – 26 ], quantitative research on the spatial morphology of traditional villages based on spatial syntax [ 27 – 28 ], etc. This study integrates concepts of inheritance and innovation to construct a parametric analysis system that quantitatively analyzes the inherent laws and characteristics of traditional Chinese village spaces. Employing parametric-assisted planning and design techniques, it explores the automatic generation of traditional village protection schemes, guiding the continuation of the spatial style and providing effective, novel technical methods for optimizing spatial form planning in traditional villages. 2. Research Method This section outlines the parametric technology employed in the study and the choice of software platform, CityEngine, followed by the overarching research ideas guiding the investigation. 2.1. Parametric Technology Parametric technology is an advanced design technique that leverages numerical relationships between variables to define geometric properties. It establishes dynamic connections between parameters (variables) and geometric shapes, enabling control over geometric changes by adjusting parameter values [ 29 ]. This technology encompasses three essential components: identifying parameters, establishing rules, and choosing software platforms [ 30 ]. Its comprehensive advantages include dynamic and efficient responses to the complexities of urban planning and architectural design [ 31 – 33 ], positioning it as a key development direction in these fields. The application of parametric design in traditional village protection planning offers several benefits: Enables quantitative analysis of spatial characteristics in traditional villages. Allows for the reconstruction of spatial textures, providing an objective and rational design approach that enhances the scientific and rational aspects of planning and design. Utilizes computer software platforms as the data foundation for AI planning models, facilitating dynamic simulations of village growth processes. Features strong scalability and openness, allowing for manual modifications and adjustments to objectively generated plans, which supports efficient public participation and aids in building information management systems for traditional village protection. 2.2. Selection of Software Platform: CityEngine Parametric design technology operates on a computer software platform, and CityEngine has been chosen for this research. As a software compatible with Python programming, CityEngine can effectively address complex issues in traditional village spatial forms through secondary development. Its seamless integration with ArcGIS allows for rapid modeling using GIS data, making it particularly advantageous for large-scale 3D form modeling [ 34 – 35 ]. The parametric design process in CityEngine follows a sequence as illustrated in Fig. 1 : establishing the street network, segmenting blocks, modeling buildings, and creating detailed scenes. Through associative rules, CityEngine can dynamically adjust various objects within the model [ 36 ]. 2.3. Research Ideas Employing data technology, this study confronts the protection and development challenges of traditional Chinese villages with a focus on spatial analysis and reconstruction. Spatial analysis involves separately identifying the roads, blocks, and buildings that constitute the characteristic elements of traditional village space, and transforming optimized feature points into parameters and rules. Spatial reconstruction uses computer language algorithms to automatically generate spatial textures based on spatial feature data extraction and parameter analysis, facilitating the automatic reconstruction and weaving of traditional village spatial textures [ 37 ]. The logical framework of the research is detailed in Fig. 2 . 3. Extraction of Core Parameters of Spatial Characteristics in Traditional Chinese Villages This section details the process of identifying and codifying the core parameters that define the spatial characteristics of traditional Chinese villages. 3.1. Spatial Feature Analysis Spatial feature analysis involves converting spatial elements into quantifiable parameters and rules for descriptive analysis. This process includes two stages: quantitative analysis of spatial features and their parameterized translation. Initially, spatial features are deconstructed based on principles of spatial elements’ integrity, with basic elements of roads, blocks, and buildings being identified and separate parameter sets being constructed for each. These parameters are designed to independently represent and control specific features. Subsequently, algorithmic rules are developed to extract parameter values from spatial forms, translating them into computer-readable data linked to spatial elements through functions and equations, thus establishing constraint relationships. 3.2. Parameter Analysis and Extraction Rules of Road Spatial Features A detailed analysis of the spatial characteristics of traditional village roads reveals the internal dynamics and functional traits of their morphological development. The parameterized analysis begins with preprocessing existing roads to identify and remove redundant information. Roads are then segmented into subgraph sets to isolate fundamental compositional elements, which are subsequently translated into parameters or rules. Algorithmic rules are formulated to extract parameter values from the existing terrain [ 37 – 38 ]. The effective parameters and extraction rules for road spatial features, as determined through experimentation, are presented in Table 1 . Table 1 Road spatial features parameters and extraction algorithms. Classification Form Parameter Extraction Algorithm Overall morphological characteristics of roads Road network morphology Road network morphology mode Extract characteristics based on the current road network Number of village centers Based on on-site research and experience judgment Number of roads Number of road sections The number of sections of a single road Road intersection Minimum distance between road intersections f(IntersectionsDiatanceMin) = Min(d 1 , d 2 , d 3 ... d n ); d represent the shortest road distance between road network intersections Intersection ratio R = Nr/Ni Nr represent number of road nodes Ni represent number of intersection nodes Minimum angle of intersection f(MinAngle) = Min(θ 1 , θ 2 , θ 3 ... θ n ); θ represent minimum value of intersection angle Road deflection angle Maximum deviation angle of the road f(MaxDeflectionAngle) = Max(β 1 , β 2 , β 3 ... β n ); β represent the maximum value of the minimum angle set between adjacent two sections of road Characteristics of Road Plane Morphology Road length Long road length(lrl) l ave =Average(l 1 , l 2 , l 3 ... l n ) f(lrl) = Average(l a1 , l a2 , l a3 ... l an ), among them l an >l ave f(srl) = Average(l b1 , l b2 , l b3 ... l bn ), among them l bn <l ave Shorter road length(srl) Elastic interval of longer road length (elrl) f(elrl)= [│ max(l a1 , l a2 , ...l an )-f(lrl) │ + │ min(l a1 , l a2 , ...l an )-f(lrl) │] /2 Elastic interval of shorter road length (esrl) f(esrl)= [│ max(l b1 , l b2 , l b3 ... l bn )-f(srl) │ + │ min(l b1 , l b2 , l b3 ... l bn )-f(srl) │] /2 Road width Main road width (mrw) f(mrw) = Average(w m1 , w m2 , w m3 ... w mn ) secondary road width (srw) f(srw) = Average(w s1 , w s2 , w s3 ... w sn ) Elastic range of main road width (emrw) f(emrw)= [│ max(w m1 , w m2 , w m3 ... w mn )-f(mrw) │ + │ min(w m1 , w m2 , w m3 ... w mn )-f(mrw) │] /2 Elastic range of secondary road width (esrw) f(esrw)= [│ max(w s1 , w s2 , w s3 ... w sn )-f(srw) │ + │ min(w s1 , w s2 , w s3 ... w sn )-f(srw) │] /2 Vertical morphological characteristics of roads Road elevation Road elevation max f(RoadElevationMax) = Max [ Elevation(e 1 , e 2 , e 3 ... e n ) ] Road elevation min f(RoadElevationMin) = Min [ Elevation(e 1 , e 2 , e 3 ... e n ) ] Road elevation average f(RoadElevationAverage) = Ave [ Elevation(e 1 , e 2 , e 3 ... e n ) ] Elastic range of road elevation f(e ere )= [│ e max -e ave │ + │ e min -e ave │] /2 Road slope Slope range f(SlopeRange)= [ S max , S min ] The illustrations for parameterized translation of road spatial features are as follows: The road network morphology can be summarized into three types: organic, raster, and radial. Complex road networks can be achieved through the superposition and fusion of these three types (Fig. 3 ). The number of village centers refers to the number of public centers in the village, and the road density in the village center is often higher than that in the periphery (Fig. 4 ). Figure 5 illustrates the spatial quantification feature for road length, road angle, and road intersections, where 02 represents road intersections, 04 represents road nodes, d1 represents distance between road intersections, θ represents the road intersection angle, and β represents the angle between roads. 3.3. Parameter Analysis and Extraction Rules for Spatial Features of Blocks The organizational structure and planar morphology of blocks are crucial in shaping the spatial form of traditional villages. The parameterization analysis aims to delineate block divisions that reflect their functions and closely match actual property blocks. Blocks are decomposed into subgraphs, and their organizational and morphological characteristics are converted into parameters and rules [58]. Research and reconstruction experiments on traditional village block patterns have yielded specific parameter indicators and extraction rules, which are outlined in Table 2 . Table 2 Blocks spatial feature parameters and extraction algorithms. Classification Form Parameter Extraction Algorithm Organizational structure characteristics Cluster form Block subdivision form f(SubdivideType) = Recursive Subdivide; f(SubdivideType) = Offset Subdivide; f(SubdivideType) = Skeleton Subdivide; Subdivision type ratio a 1 %,a 2 %,a 3 %, a 1 + a 2 + a 3 =100 Block density Maximum block density f(DensityMax) = Max(a 1 , a 2 , a 3 , ...a n ) Minimum block density f(DensityMin) = Min(a 1 , a 2 , a 3 , ...a n ) Average block density f(DensityAverage) = Average(a 1 , a 2 , a 3 , ...a n ) Block direction Maximum block direction f(DirectionMax) = Max(β 1 , β 2 , β 3 , ...β n ) Minimum block direction f(DirectionMin) = Min(β 1 , β 2 , β 3 , ...β n ) Average block direction f(DirectionAverage) = Average(β 1 , β 2 , β 3 , ...β n ) Terrain adaptation methods Terrain adaptation methods f(LotAlignment)=ཛUneven,Minmum,Maxmum,Averageཝ Functional blocks number ratio Functional blocks number ratio a 1 %,a 2 %,a 3 ...a n %, a 1 + a 2 + a 3 +...a n =100 Block interface density Block interface density ,R i represent the length of the base on one side of the boundary of the i-th building adjacent to the block; L is the length of the block boundary Planar morphological features Block area Maximum block area f(AreaMax) = Max [ area(a 1 , a 2 , a 3 , ...a n ) ] Minimum block area f(AreaMin) = Min [ area(a 1 , a 2 , a 3 , ...a n ) ] Average block area f(AreaAverage) = Average [ area(a 1 , a 2 , a 3 , ...a n ) ] The interval size and probability distribution of block area f[AreaFrequency(i-j)] = Frequency(date_arry,bin_arry) Block boundary line The longest side length of the bounding rectangle on the block f(EdgeLongest) = Max(l 1 , l 2 , l 3 , ...l n ) The shortest side length of the bounding rectangle of the block f(EdgeShortest) = Min(l 1 , l 2 , l 3 , ...l n ) The average side length of the bounding rectangle of the block f(EdgeAverage) = Average(l 1 , l 2 , l 3 , ...l n ) The maximum length-width ratio of bounding rectangle outside the block f(MaxtLength/Width ratio) = Max(a 1 , a 2 , a 3 , ...a n ) The minimum length-width ratio of bounding rectangle outside the block f(MintLength/Width ratio) = Min(a 1 , a 2 , a 3 , ...a n ) The average length-width ratio of bounding rectangle outside the block f(AverageLength/Width ratio) = Average(a 1 , a 2 , a 3 , ...a n ) Block interior angle Maximum block interior angle f(CoenerAngleMax) = Max(θ 1 , θ 2 , θ 3 , ...θ n ) Minimum block interior angle f(CoenerAngleMim) = Min(θ 1 , θ 2 , θ 3 , ...θ n ) Average block interior angle f(CoenerAngleAverage) = Average(θ 1 , θ 2 , θ 3 , ...θ n ) The illustrations of parameterized translation of block spatial features are as follows: The block subdivision forms have three types: recursive subdivide, offset subdivide and skeleton subdivide (Fig. 6 ). Figure 7 illustrates the quantitative extraction method for block planar morphological features, where θ represents the block interior angle, L and W represent block boundary lines, and L’ represents the block direction line, which is a straight line parallel to the long side of the bounding rectangle outside the block. 3.4. Parameter Analysis and Extraction Rules of Building Space Features The spatial characteristics of buildings are captured by translating their planar and facade form elements into parameters and rules. The established parameter indicators and corresponding extraction rules are detailed in Table 3 . Table 3 Buildings spatial feature parameters and extraction algorithms. Classification Form Parameter Extraction Algorithm Characteristics of building plane form Building foundation Building foundation shape Using typological methods to extract the shape of building plans Scale of building foundation shape s 1 %,s 2 %,s 3... s n. %, s 1 + s 2 + s 3 +...s n =100 , s n % represent the ratio of the number of n-th type building plans to the total number of buildings Building width Maximum building width f(BuildingWidthMax) = Max(w 1 , w 2 , w 3 , ...w n ) Minimum building width f(BuildingWidthMin) = Min(w 1 , w 2 , w 3 , ...w n ) Average building width f(BuildingWidthAverage) = Average(w 1 , w 2 , w 3 , ...w n ) Building depth Maximum building depth f(BuildingDepthMax) = Max(d 1 , d 2 , d 3 , ...d n ) Minimum building depth f(BuildingDepthMin) = Min(d 1 , d 2 , d 3 , ...d n )) Average building depth f(BuildingDepthAverage) = Average(d 1 , d 2 , d 3 , ...d n )) Building area Maximum building area f(BuildingShapeAreaMax) = Max [ area(a 1 , a 2 , a 3 , ...a n ) ] Minimum building area f(BuildingShapeAreaMin) = Min [ area(a 1 , a 2 , a 3 , ...a n ) ] Average building area f(BuildingShapeAreaAverage) = Average [ area(a 1 , a 2 , a 3 , ...a n ) ] Concentrated distribution range of building area f[BuildingShapeArea(i-j)] = Frequency(date_arry,bin_arry) Characteristics of building facade form Building height Maximum building height f(BuildingHeightMax) = Max(β 1 , β 2 , β 3 , ...β n ) Minimum building height f(BuildingHeightMin) = Min(β 1 , β 2 , β 3 , ...β n ) Average building height f(BuildingHeightAverage) = Average(β 1 , β 2 , β 3 , ...β n ) Concentrated distribution range of building height f[BuildingHeight(i-j)] = Frequency(date_arry,bin_arry) Building storey number Building storey number s 1 %,s 2 %,s 3... s n. %, s 1 + s 2 + s 3 +...s n =100 , s n % represent the proportion of floors in the n-th type of building Building direction Maximum building direction f(BuildingDirectionMax) = Max(β 1 , β 2 , β 3 , ...β n ) Minimum building direction f(BuildingDirectionMin) = Min(β 1 , β 2 , β 3 , ...β n ) Average building direction f(BuildingDirectionAverage) = Average(β 1 , β 2 , β 3 , ...β n ) Concentrated distribution range of building direction f [ BuildingDirection(i-j) ] = Frequency(date_arry,bin_arry) Roof Roof style b 1 %,b 2 %,b 3... b n. %, b 1 + b 2 + b 3 +...b n =100 , b n % represent the proportion of the n-th type of roof form Roof material c 1 %,c 2 %,c 3... c n. %, c 1 + c 2 + c 3 +...c n =100 , c n % represent the proportion of the n-th type roof material Wall Building wall material d 1 %,d 2 %,d 3... d n. %, d 1 + d 2 + d 3 +...d n =100 , d n % represent the proportion of the n-th type of building wall material The illustrations of parameterized translation of building spatial features are as follows: The patterns of building foundation shapes mainly include I-shaped, L-shaped, U-shaped, and combinations of these types (Fig. 8 ). The building angle is the smaller angle between the building direction line and the reference line. Figure 9 illustrates the extraction rules for building angle. Figure 10 illustrates the extracted elements of building facade morphological features. 4. Parameterized Reconstruction and Practical Application of Traditional Village Space This section outlines the process of parameterized reconstruction of traditional village space and its practical applications. 4.1. Parameterized Space Reconstruction Parameterization technology, coupled with computer programming algorithms, enables the automatic generation of spatial textures that mimic original features, facilitating the reconstruction and weaving of traditional village textures. The reconstruction process is divided into two main parts: the organization of associated feature elements and the construction of visualization models. 4.1.1. Organization of Associated Feature Elements Utilizing the CityEngine software platform’s generation module, a set of logical rules and code expressions are created to construct spatial "growth" within the constraints of space (dimensional and geometric) and organizational rules. The spatial form elements of roads, blocks, and buildings are arranged in a cohesive relationship model. Figure 11 illustrates this organization, where A, B, and C represent spatial types, a 1 , b 1 , and c 1 represent the feature elements constituting spatial types, the lines between elements indicate constraint relationships, b 31 signifies the conditions for constraining spatial elements, c 23 denotes the conditions for constraining different spatial elements of the same type, and ab 12 represents the constraint conditions for spatial elements between different types. The spatial generation of roads is carried out through the StreetModule of the CE software platform, which decomposes the roads into five components: street, sidewalk, crossing, junction, and junctionentry. The components are organized in an orderly manner into a framework according to constraint conditions, and through the secondary development of CGA rule files, revise and optimize the generated road spatial form. Figure 12 illustrates the process of road space reconstruction. The reconstruction of block space and building is mainly achieved through programming methods. By using the CGA language provided by CE and writing CGA rule files, spatial features and constraint relationships between features are integrated to form a spatial generation relationship model. Parameter values are substituted into the CGA file and imported into the CE platform for spatial generation. Figure 13 illustrates the process of block space and building reconstruction. 4.1.2. Visualization Model Construction Employing the CityEngine software platform, visual models are constructed based on the overall linked relationship model. This is done using parameter-driven and relationship-driven mechanisms to create two-dimensional graphics and three-dimensional visualization images. These models simulate the generation of basic spatial features and serve as a foundation for the subsequent reconstruction of the traditional village space. 4.2. Practical Application of Parameterized Space Reconstruction 4.2.1. Research Area Qiji Village, located in Yanggu County, Shandong Province, is recognized on the sixth list of traditional Chinese villages. As an important historical dock of the Grand Canal since the Yuan Dynasty, Qiji Village has been a prosperous trading hub. Its well-preserved ancient dock and connected commercial street are significant components of the Grand Canal’s World Heritage application, as shown in Fig. 14(a). However, with the decline of river transport, Qiji Village faces challenges such as depopulation, dilapidated buildings, and poor infrastructure, leading to the erosion of its social functions, cultural values, and spatial features. The study focuses on a 22-hectare area designated for the protection and renewal of Qiji Village, as shown in Fig. 14(b). In the national spatial planning context, Qiji Village is within the urban development boundaries. The main challenge is integrating traditional village protection with urban construction, preserving spatial patterns and historical buildings, improving infrastructure, and enhancing the village’s vitality. This research aims to address these challenges. 4.2.2. Data Acquisition and Establishment of Parameter Sets Data collection involves on-site research and the use of open-source geographic information to gather data on roads, land parcels, and buildings within the Qiji Village landscape protection area. This data serves as the foundation for generating renewed spatial morphological features. Following the earlier mentioned parameter analysis and extraction rules, the data is categorized, integrated, and current spatial feature parameter values are extracted. These values are optimized to reflect changes in urban development and residents’ needs, creating a traditional village spatial characteristic parameter database to support the automatic reconstruction of spatial styles (Fig. 15 ). 4.2.3. Reconstruction and Continuation of Spatial Texture Using the spatial feature parameter database, the study explores the automatic generation of traditional village spatial textures with the CityEngine software platform. The process begins with the application of traditional village boundary extraction rules, combined with the scope of traditional village protection planning and the construction area designated by national land space, to determine the areas requiring renewal. The road space form generation module is then used to generate the road network form by adjusting parameter values. The generated road form is further refined by importing rule files for secondary development (Fig. 16a). Following this, block segmentation and block spatial texture reconstruction are performed through programming using the CGA rule language provided by CityEngine or compatible Python language (Fig. 16b). Finally, parameterized 3D modeling of buildings is conducted using CGA syntax or rule files written in Python to generate and reconstruct the spatial texture of buildings (Fig. 16c). As demonstrated, parametric design can automatically generate planning schemes through programming with rule-based languages based on extracted parameter data. By adjusting parameter indicators, the automatically generated plans can be optimized and adaptively modified to reconstruct planning and design schemes that not only retain traditional village characteristics but also meet modern living needs. This alignment with traditional village protection and future development trends makes the planning and design process more rational and efficient. 5. Conclusion and Discussion Digital technology is increasingly applied to protect traditional settlements. Parameterization technology extracts the systematic rules governing the spatial information of traditional settlements, overcoming limitations such as potential biases and inaccuracies inherent in subjective methods of information transmission, and ensuring the accurate preservation of historical landscape information. By integrating advanced technologies and combining human and computer decision-making, planning schemes are generated that preserve the spatial characteristics of case studies while incorporating modern living needs. Digital technology promises to bring order and innovation to traditional spaces. The digital generation of Qiji Village’s protection and development planning scheme validates the effectiveness and technical advantages of automatic generation methods based on the parameterization of spatial feature elements. Parametric design utilizes parameters and algorithms, with its rich and rigorous design logic, to improve design efficiency. This reflects the advantages of parametric design methods in terms of systematicity, interpretability, and controllability. Despite the diversity of traditional Chinese villages, their unique bottom-up growth pattern provides a recognizable and consistent basis for digital generative design techniques. With advancements in artificial intelligence and digital technology, and as spatial data on traditional villages becomes richer and more refined, data-driven automatic generation of planning and design schemes will increasingly address the complex challenges of protecting and renewing traditional settlements and historical buildings. One important purpose of computer-aided planning and design is to gradually move towards intelligent systems that alleviate human workload and ensure that the process remains human-centric. It transforms design principles into intelligent rules and hands them over to computers, freeing more human energy into design decisions and forming a human-machine interactive planning and design process. Any planning and design scheme is almost never carried out on a blank sheet of paper. The current situation, existing constraints themselves, manual preset of key design intentions are important factors in determining the outcome of the scheme, which is a work scope that computers cannot automatically complete. For the results generated through assisted generation, human intelligence needs to be deeply involved in screening, evaluating, and adjusting, ultimately transforming them into design solutions guided by the thinking of planners. During the adjustment process, the barriers between planners and computers are broken to the greatest extent possible. Human intelligence and role become the top priority in the computer-aided process. There are certain limitations to this research. First, The traditional parameterization method is mainly based on human settings. If designers intervene excessively in the design process, the resulting designs may lack true intelligence and automation, and it is difficult to get rid of the dependence on subjective factors of humans. Second, traditional village protection is a complex task that involves the inherent mechanism of multi-scale space, with more diverse humanistic and social content. It is necessary to consider a range of objectives, encompassing both objective constraints, such as land rights and heritage conservation, and subjective factors, such as culture, social systems, economy, and aesthetics. In future studies, deep learning methods can be applied to the process of extracting spatial features and organizational rules, to accurately perceive and recognize complex spatial forms[ 39 – 41 ], minimizing manual intervention during the generation process. In addition, it is necessary to multidimensional optimization parameterized content system, incorporate "invisible" indicators such as social and economic development, human demands, sociocultural and institutional structures into the parameterized indicator system. Application of planning and design considering traditional village differentiation is also important, the construction of a national database detailing the morphological characteristics of traditional villages would be beneficial. In contemplating the role of technology in planning, it is worth considering whether computer-aided planning and design have inadvertently given precedence to technology over other aspects. Does intelligent tool thinking weaken the dominant position of humanism in creative thinking? As the French philosopher Bernard Stiegler once said, “We need to create a new technological culture to respond to the era of technology” [ 42 ]. Therefore, under new technological conditions, we need to consider how to reshape spatial planning and design under human-machine symbiosis. Declarations Author Contributions: Conceptualization, Yong Fan; methodology, Yong Fan; software, Xuan Li, Yong Fan; validation, Xuan Li, Yong Fan; formal analysis, Yong Fan; investigation, Yong Fan, Xuan Li, Wen-jie Xiao; resources, Yong Fan, Xuan Li; data curation, Yong Fan, Xuan Li, Wen-jie Xiao; writing—original draft preparation, Yong Fan; writing—review & editing, Di Wang; visualization, Yong Fan, Xuan Li; supervision, Di Wang; project administration, Yong Fan, Di Wang. All authors have read and agreed to the published version of the manuscript. Data Availability: The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Funding: This research was funded by the Ministry of Education of the People’s Republic of China: 21YJCZH024 and the People’s Government of Shandong Province: ZR2021ME226. References Wen Quan; Tang Jianguo; Cai Kuangyuan. The Authenticity and Integrity of Traditional Village Protection from the Perspective of Vernacular Built Heritage: A Case Study of Three Gorges Original Township Hankuimen. Huazhong Architecture . 2023 , 41 , 143-147. He Ziyi; Liu Juan; Tan Jiaxing; Gao Chaoxuan. Research on Digital Protection and Inheritance of Traditional Villages Based on the Whole Life Cycle. Development of S mall C ities & T owns . 2023 , 41 , 46-52. Cai Jun; Wen Rigiang; Jiang Wei; Yan Jiao; Lu Lifuan. DeepLabV3+ Improved Algorithm for National Building Recognition in Traditional Village Aerial Images. Bulletin of Surveying and Mapping . 2023 , 04, 49-53. Wu Ning; Wen Tianrong; Tong Lei. Research On Application Of Parametric Analysis And Reconstruction In Village Space Exemplified By A Traditional Village In Guizhou. Architecture & Culture . 2016 , 0 5 , 142-143. Qin Qiaohua; Xiao Dawei; Luo Mingnan; Tao Jin. A Study on the classification of traditional village images based on convolutional neural network. City Planning Review . 2020 , 44 , 52-58. Yueping Kong; Peng Xue; Yuqian Xu; Xiaolong Li. An Environmental Pattern Recognition Method for Traditional Chinese Settlements Using Deep Learning. Applied Sciences . 2023 , 13 , 4778. Dai Jianhua; Peng Ruoyao; Xu Lu; et al. A Survey of Information Extraction Based on Deep Neural Networks. Journal of Southwest China Normal University (Natural Science Edition . 2022 , 4 , 1-11. Russakovsky O; Deng J; Su H; et al. ImageNet large Scale Visual Recognition Challenge. International Journal of Computer Vision . 2015 , 3 , 211-252. Quan Steven Jige; Park James; et al. Artificial intelligence-aided design: Smart Design for sustainable city development. Environment and Planning B: Urban Analytics and City Science . 2019 , 46 , 1581-1599. Xiao Liu; Xu Feng; Wang Jun. Preliminary Studies on Parametric Design of New Hutong Space:A Case Study on Qianmen District in Beijing. Huazhong Architecture. 2013 , 31 , 35-39. Chen Y; Feng M. Urban form simulation in 3D based on cellular automata and building objects generation. Building and Environment . 2022 , 226 , 109727. Pérez-Martínez I; Martínez-Rojas M; Soto-Hidalgo JM. A methodology for urban planning generation: A novel approach based on generative design. Engineering Applications of Artificial Intelligence . 2023 , 124 , 106609. Zhang K H; Zhang N; Quan F M; et al. Digital Form Generation of Heritage in Historical District Based on Plan Typology and Shape Grammar: A Case Study on Kulangsu Islet. Buildings . 2023 , 13 . Sugianto E; Hosea JF; Jabar BA; Irwansyah E; Fitrianah D. 3D Modelling Building of District Johar Baru Using ArcGIS Pro and CityEngine. Procedia Computer Science , 2023 , 22 7, 623-631. Yingtao Qi; Yulin Ren; Dian Zhou; Yupeng Wang; Yujia Liu; Bin Zhang. Quantitative Analysis and Cause Exploration of Architectural Feature Changes in a Traditional Chinese Village: Lingquan Village, Heyang County, Shaanxi Province. Land . 2023 , 12 . Zhe Li; Si Huang; Han Wang; Yan Li. Digital Analysis of the Water Layout Ecological Wisdom in Traditional Chinese Rural Settlements: A Case Study of Liukeng Village in Jiangxi Province. Journal of Resources and Ecology . 2022 , 13 , 371-381. Shen Yinlan; Yan Xingchen; Yu Piyong; Liu Hui; Wu Guofang; He Wei. Seismic Resistance of Timber Frames with Mud and Stone Infill Walls in a Chinese Traditional Village Dwelling. Buildings . 2021 , 11 , 580-580. Yang Simin; Yi Lina; Guan Hui; Li Yong. A meme-based approach for knowledge mining, organization, and presentation of traditional Chinese settlement culture. Heritage Science. 2023 , 11 . Zhongyi Nie; Chen Chen; Wei Pan; Tian Dong. Exploring the Dynamic Cultural Driving Factors Underlying the Regional Spatial Pattern of Chinese Traditional Villages. Buildings . 2023 , 13 . Liu Xuedong; Huang Yi; Xiang Huilin; Zhang Chen; Chen Juan; Xiao Dawei. Optimization strategies for the management mechanisms of conservation and utilization in traditional Chinese villages based on relevance analyses of performance evaluation. Journal of Asian Architecture and Building Engineering . 2023 , 22 , 1699-1713. Xu Luyao; Shi Lei; Wang Xin; Wan Yuliang; Fan Zhuo. Can tourists become disciples? The formation and mechanism of place conversion in traditional Chinese villages. Frontiers in Psychology. 2023 , 14 , 1301127-1301127. Xiaolong Hu; Tong Yao. Study on the Synergistic Development of Chinese Traditional Villages Protection and Landscape Development. Applied Mathematics and Nonlinear Sciences . 2024 , 9. Jialu Li. Community Building: An Exploration of the Path in Traditional Village Conservation and Renewal with an Example of Yim Tin Tze in Hong Kong. Journal of Environmental and Agricultural Studies . 2022 , 3 , 01-06. Yufei Lyu; Lei Zhang; Xin Liu; Xuan Ma. Microclimate-Adaptive Morphological Parametric Design of Streets and Alleys in Traditional Villages. Buildings . 2024 , 14 , 152. Wang Liangliang; Lu Yaru; Huang Wencan; HAN Jie. Analysis Methods for Landscapes and Features of Traditional Villages Based on Digital Technology: Taking Xiaocuo Village in Quanzhou as an Example. Chinese Landscape Architecture , 2023 , 39 , 13-19. Yang Xi. Advances in Quantitative Research Methodologies for the Spatial Layout of Rural Settlement in Recent 20 Years. Urban Planning International . 2020 , 35 , 72-80. Lin Kefeng; Tao Wei; Gu Hengyu. Spatial form and spatial cognition of traditional villages based on space syntax: A case study of jiaju Village, Guizhou Province. Scientia Geographica Sinica , 2023 , 43 , 1608-1618. Sun Li; Zhou Yifan; Sun Xuepu; Wang Ting; Yang Zhen. Spatial Syntax Analysis of Traditional Villages Based on Space Syntax: A Case Study of Linggong Village in Beijing. Journal of Beijing University of Civil Engineering and Architecture . 2023 , 39 , 1-9. Xu Weiguo; Xu Feng. Architectural Creation and Thinking of the Parametric Design in China: Interview with Professor Xu Weiguo & Xu Feng of School of Architecture of Tsinghua University. Urbanism and Architecture . 2010 , 06 , 108-113+3. Chi Zhi-wei; Chen Jie; Zhang De-shun. Process in Application of Parametric Design and Its Inspiration to Landscape Design. Chinese Landscape Architecture. 2012 , 28 , 40-45. Patik Schumacher. Parametric Patterns. Architectural Design. 2009 , 6 , 28-41. LI Xiaojun; Huang Jian; Zou Fu. Rapid Three-Dimension and Spatial Analysis for Village Planning Scheme. Journal of Geomatics . 2021 , 46(S1), 178-181. Li Hengkai; Li Xiaolong; Li Zivang; Chen Yueving. Three-dimensional modeling method of Hakka ancient village based on component model library-a case study in the BaiLu ancient village. Science of Surveying and Mapping . 2019 , 44 , 182-189. Zhang Hui; Liu Chao; Li Yan; Wang Youjie. Research on 3D Building Modeling Technology Based on CityEngine. Bulletin of Surveying and Mapping . 2014 , 11 , 108-112. Duarte J P; Rocha J; Ducla-Soares G; et al. An urban grammar for the Medina of Marrakech ; Springer: Berlin, Germany, 2006 ; pp. 483-502. Zhou Ling. Method of 3D Modeling for Digital City Based on Parametric Technology. Master, Zhe Jiang University, Hang Zhou, 2013. Tong Lei. Parametric Analysis and Reconstruction of Villages’ Spatial Texture and Its Planning Application Research. Dr, Zhe Jiang University, Hang Zhou, 2016 . Wu Meihan. Research on Parametric Analysis and Planning Application of Village Space Texture in Qin and Han New Towns. Master, Chang’an University, Xi’an, 2022 . Han Qing; Yin Chao; Deng Yunyuan; Liu Peilin. Towards Classification of Architectural Styles of Chinese Traditional Settlements Using Deep Learning: A Dataset, a New Framework, and Its Interpretability. Remote Sensing . 2022 , 14 , 5250-5250. Quan Steven Jige.. Urban-GAN: An artificial intelligence-aided computation system for plural urban design. Environment and Planning B: Urban Analytics and City Science . 2022 , 49 , 2500-2515. Yang Junyan, Zhu Xiao, Sun Haocheng. Research on artificial intelligence urban design method based on the combination of deep learning and characteristic parameters: taking the formation of urban multi-type building community as an example. Contemporary Architecture . 2022 , 06 , 33-36. Kouppanou Anna. Bernard Stiegler’s Philosophy of Technology: Invention, Decision, and Education in Times of Digitization. Educational Philosophy and Theory . 2015 , 47(10), 1110–1123. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4072347","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":284083595,"identity":"8bff3619-fe78-43ce-a1b9-57efe0b6cbdb","order_by":0,"name":"Yong Fan","email":"","orcid":"","institution":"University of Jinan","correspondingAuthor":false,"prefix":"","firstName":"Yong","middleName":"","lastName":"Fan","suffix":""},{"id":284083596,"identity":"72565057-c6a9-4bb3-a356-17e05da665c8","order_by":1,"name":"Xuan Li","email":"","orcid":"","institution":"University of Jinan","correspondingAuthor":false,"prefix":"","firstName":"Xuan","middleName":"","lastName":"Li","suffix":""},{"id":284083597,"identity":"96cb5f26-82e4-4b03-a022-b7f0230df479","order_by":2,"name":"Wen-jie Xiao","email":"","orcid":"","institution":"University of Jinan","correspondingAuthor":false,"prefix":"","firstName":"Wen-jie","middleName":"","lastName":"Xiao","suffix":""},{"id":284083598,"identity":"c70f5967-116f-499f-944a-208ee7f9c35b","order_by":3,"name":"Di Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5ElEQVRIie3RLwvCQBjH8ZODsxyunkF8Cw8caJH5ViYD04SBxWAYDLQtz3exZD44cOVegKJhaRaDSSz+2QbW22yC9w33lN8nHUIm00+XBgiK0wqaEyW+JnunOvXEWocZpsuTHR0uMPfRqJcInGc6wtQOMN3l7uboAY/RlCeCDEFHgDmAPSJdKAlFcpIISpiW9M9X7D0LclAleTUgjAKeraQNe1oSUU+Y8nz8iKTTVVOfU3D5RpKBlljrNGnFNznupHLL6cLuRWmYa0lR+148kwAhAtVn4pr9p3G5zRqOTSaT6c96A5tOSLXScG38AAAAAElFTkSuQmCC","orcid":"","institution":"University of Jinan","correspondingAuthor":true,"prefix":"","firstName":"Di","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2024-03-11 09:34:54","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4072347/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4072347/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":53671602,"identity":"1665524c-4720-4ab1-88d9-a8c2fb5cf484","added_by":"auto","created_at":"2024-03-28 18:00:00","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":157393,"visible":true,"origin":"","legend":"\u003cp\u003eCityEngine workflow diagram.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-4072347/v1/7a0c5f84159a39a2ea790218.png"},{"id":53670792,"identity":"0f88c14d-b84a-4d31-bbff-c8710666582e","added_by":"auto","created_at":"2024-03-28 17:52:00","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":67481,"visible":true,"origin":"","legend":"\u003cp\u003eThe logical framework of the research.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-4072347/v1/34423f2fb27ef23bab11886e.png"},{"id":53671603,"identity":"72f4a25a-f53f-4676-859c-2d95580535ce","added_by":"auto","created_at":"2024-03-28 18:00:00","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":193866,"visible":true,"origin":"","legend":"\u003cp\u003eThree basic road network forms.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-4072347/v1/94c4a94d7f4f66b6761850a7.png"},{"id":53670794,"identity":"59927383-eedc-4887-a140-7d28f298b68b","added_by":"auto","created_at":"2024-03-28 17:52:00","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":33497,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic diagram of village centers (a single center and two centers).\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-4072347/v1/d7972eda05d51211a6b44614.png"},{"id":53670803,"identity":"7532edad-95c6-48b8-aeef-d3b03f22965e","added_by":"auto","created_at":"2024-03-28 17:52:01","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":15951,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic diagram of parameter extraction for road length, angle, and nodes.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-4072347/v1/6cec0ee7be5de061607b9d0b.png"},{"id":53671604,"identity":"b720fb56-7d94-4383-9ade-63bb22387282","added_by":"auto","created_at":"2024-03-28 18:00:00","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":68953,"visible":true,"origin":"","legend":"\u003cp\u003eThree types of block subdivision forms.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-4072347/v1/941291b091f4dee030094378.png"},{"id":53670800,"identity":"0a0a85c4-a8a9-451b-8e5a-72d55784dcf7","added_by":"auto","created_at":"2024-03-28 17:52:00","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":23524,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic diagram of block planar morphological features.\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-4072347/v1/7c1080cd4964fcf5e3fde5d6.png"},{"id":53670796,"identity":"99c37edc-a52d-44a1-b56e-23df982bf568","added_by":"auto","created_at":"2024-03-28 17:52:00","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":52512,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic diagram for extracting the building foundation shape.\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-4072347/v1/c5aaad15a9856aaecb6fbc4e.png"},{"id":53670805,"identity":"d0b3e17d-3163-4d75-a9a1-215b9e9a8b1c","added_by":"auto","created_at":"2024-03-28 17:52:01","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":86144,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic diagram for extracting building angle parameter.\u003c/p\u003e","description":"","filename":"image9.png","url":"https://assets-eu.researchsquare.com/files/rs-4072347/v1/628019d1772d3f06dc4bac5e.png"},{"id":53670799,"identity":"33ae4b9e-8bee-4886-aac1-7151f6fd007d","added_by":"auto","created_at":"2024-03-28 17:52:00","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":261489,"visible":true,"origin":"","legend":"\u003cp\u003eExtracted elements of building facade morphological features.\u003c/p\u003e","description":"","filename":"image10.png","url":"https://assets-eu.researchsquare.com/files/rs-4072347/v1/61c7645bd62fd6d6fa7e9285.png"},{"id":53670807,"identity":"fb6a7c96-8667-4915-abf0-70bc9c77ddda","added_by":"auto","created_at":"2024-03-28 17:52:01","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":70917,"visible":true,"origin":"","legend":"\u003cp\u003eSpatial feature element relationship model.\u003c/p\u003e","description":"","filename":"image11.png","url":"https://assets-eu.researchsquare.com/files/rs-4072347/v1/651575674baa993f3bff9c13.png"},{"id":53670802,"identity":"0365e1a5-8d9b-4e7a-b222-bb33efa66972","added_by":"auto","created_at":"2024-03-28 17:52:00","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":96840,"visible":true,"origin":"","legend":"\u003cp\u003eThe process of road space reconstruction.\u003c/p\u003e","description":"","filename":"image12.png","url":"https://assets-eu.researchsquare.com/files/rs-4072347/v1/c54d694afee99724863a40e1.png"},{"id":53670808,"identity":"4a772ac0-31b8-46d7-bbd1-e230722a12cd","added_by":"auto","created_at":"2024-03-28 17:52:01","extension":"png","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":113353,"visible":true,"origin":"","legend":"\u003cp\u003eThe process of block space and building reconstruction.\u003c/p\u003e","description":"","filename":"image13.png","url":"https://assets-eu.researchsquare.com/files/rs-4072347/v1/5f015ef247ba777ce2c984b1.png"},{"id":53670804,"identity":"89804c20-81b2-4f22-926e-35d706ba8f52","added_by":"auto","created_at":"2024-03-28 17:52:01","extension":"png","order_by":14,"title":"Figure 14","display":"","copyAsset":false,"role":"figure","size":925053,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Current situation map of Qiji Village; (b) Study area range.\u003c/p\u003e","description":"","filename":"image14.png","url":"https://assets-eu.researchsquare.com/files/rs-4072347/v1/ae62c97a1e7922752b60c1e7.png"},{"id":53670801,"identity":"11d583fd-2b07-444e-9fe8-b3d7ba2e950c","added_by":"auto","created_at":"2024-03-28 17:52:00","extension":"png","order_by":15,"title":"Figure 15","display":"","copyAsset":false,"role":"figure","size":292704,"visible":true,"origin":"","legend":"\u003cp\u003eFeature extraction of spatial characteristics.\u003c/p\u003e","description":"","filename":"image15.png","url":"https://assets-eu.researchsquare.com/files/rs-4072347/v1/23463f1b8a4f59d98fe2eb66.png"},{"id":53670797,"identity":"12f83428-77eb-46c8-b151-607acf8e5dfa","added_by":"auto","created_at":"2024-03-28 17:52:00","extension":"png","order_by":16,"title":"Figure 16","display":"","copyAsset":false,"role":"figure","size":567319,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Parameterized automatic generation of the road network; (b) Parameterized automatic generation of the block segmentation; (c) Parameterized automatic generation of the building layout.\u003c/p\u003e","description":"","filename":"image16.png","url":"https://assets-eu.researchsquare.com/files/rs-4072347/v1/1733e594b4ad8fc5765f13b4.png"},{"id":55010437,"identity":"b4ffad7d-e66a-4a19-b5df-cdf021334e80","added_by":"auto","created_at":"2024-04-19 19:22:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3620387,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4072347/v1/502539ce-a859-4c61-8863-997aafcf9beb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Analysis and Reconstruction Method of Spatial Characteristics of Traditional Chinese Villages Based on Parameterization","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eTraditional Chinese villages are a vital legacy of China\u0026rsquo;s agricultural civilization, embodying the historical memory of the nation and encompassing rich historical information and cultural landscapes. Spatial style is a key landscape resource of traditional Chinese villages and serves as a spatial carrier that reflects the historical and cultural traits of these villages. Understanding the value of traditional Chinese villages and preserving their spatial features and cultural elements are crucial for the innovation and continuation of Chinese civilization in the new era.\u003c/p\u003e \u003cp\u003eUnder the current new technological context and social development conditions, the protection and renewal of traditional Chinese villages face two problems. Firstly, how should traditional villages\u0026rsquo; spatial feature information be identified and accurately transmitted? The spatial style of traditional villages has been severely impacted by China\u0026rsquo;s rapid urbanization. The integrity of spatial style and continuity of cultural inheritance have been disrupted, leading to a loss of spatial form characteristics and cultural functions [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Protecting traditional villages is a significant challenge in the urbanization process. The difficulties arise mainly from the mainstream planning model\u0026rsquo;s lack of detailed analysis and application of the internal dynamics of traditional village spatial forms. This is evident in the absence of precise quantitative analysis tools, efficient spatial form design technologies, and dynamic planning methods. To address this, it is essential to objectively identify and extract spatial feature information from traditional villages. Constructing a comprehensive information system and expressing this information through computer-recognizable coding methods is necessary. The second problem is how to effectively utilize traditional villages\u0026rsquo; spatial feature data. Advancements in data technology have led to an increase in digital research on traditional villages, transitioning from manual to digital preservation methods [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Image recognition and spatial information databases for traditional villages are maturing [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. However, the application of digital technology in village protection often stops at data visualization. The acquisition of extensive data enables the accurate transmission of historical and cultural information, crucial for restoring incomplete spatial features and reconstructing spatial textures [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Data mining is required to understand the objective rules behind the visual aspects. Relying solely on static guidelines or dynamic visualizations from data organization is insufficient. The deepening of data technology and artificial intelligence research has made the parametric extraction of spatial information features and the automatic generation of protection schemes for traditional villages an important research direction and practical approach [\u003cspan additionalcitationids=\"CR6 CR7 CR8\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eParametric design is a computer-aided technology based on processes and rules, which utilizes computer automation to execute manually formulated logical processes and generate rules, and quickly output specific content generation methods. This method is widely used in the field of computer graphics for virtual world synthesis modeling. In the field of spatial planning and design, parametric design was first widely applied in the nonlinear design of buildings, especially in the design of building skins, and gradually spread to the fields of urban design and urban spatial planning [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Based on parameterized computer-aided planning and design, the relevant processes and rules are based on mature design logic, and the interpretability of scheme generation is strong. The method based on process and rules is also convenient for carrying a powerful human-computer interaction interface, which can adjust generation conditions and modify generation results in real time, and the generation process is highly controllable. Parameterization has become an important development direction for computer-aided planning and design in the fields of architectural design and urban-rural planning. At present, the exploration of parameterization technology in urban and rural planning and design practice mainly involves the simulation of urban architectural group form, the simulation of urban overall structural form, and the design of urban road network form[\u003cspan additionalcitationids=\"CR12 CR13\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Most of the existing practical research has focused on the field of urban design, and its application in the planning and design of rural settlement spatial forms is close to blank. This article is an exploration of this blank field.\u003c/p\u003e \u003cp\u003eThe research on traditional Chinese villages mainly focuses on the analysis and excavation of spatial features and architectural construction characteristics [\u003cspan additionalcitationids=\"CR16 CR17\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], the management mechanism for the protection and utilization of traditional villages [\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], the paths for the protection and renewal of traditional villages [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Practical research on the application of parameterization techniques in the planning and design of rural settlement spatial forms is limited. Parameterized research on traditional villages mainly focuses on parametric design of street and alley spaces [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], quantitative analysis of spatial texture [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], quantitative research on the spatial morphology of traditional villages based on spatial syntax [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], etc. This study integrates concepts of inheritance and innovation to construct a parametric analysis system that quantitatively analyzes the inherent laws and characteristics of traditional Chinese village spaces. Employing parametric-assisted planning and design techniques, it explores the automatic generation of traditional village protection schemes, guiding the continuation of the spatial style and providing effective, novel technical methods for optimizing spatial form planning in traditional villages.\u003c/p\u003e"},{"header":"2. Research Method","content":"\u003cp\u003eThis section outlines the parametric technology employed in the study and the choice of software platform, CityEngine, followed by the overarching research ideas guiding the investigation.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Parametric Technology\u003c/h2\u003e \u003cp\u003eParametric technology is an advanced design technique that leverages numerical relationships between variables to define geometric properties. It establishes dynamic connections between parameters (variables) and geometric shapes, enabling control over geometric changes by adjusting parameter values [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. This technology encompasses three essential components: identifying parameters, establishing rules, and choosing software platforms [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Its comprehensive advantages include dynamic and efficient responses to the complexities of urban planning and architectural design [\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], positioning it as a key development direction in these fields. The application of parametric design in traditional village protection planning offers several benefits:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eEnables quantitative analysis of spatial characteristics in traditional villages.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eAllows for the reconstruction of spatial textures, providing an objective and rational design approach that enhances the scientific and rational aspects of planning and design.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eUtilizes computer software platforms as the data foundation for AI planning models, facilitating dynamic simulations of village growth processes.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eFeatures strong scalability and openness, allowing for manual modifications and adjustments to objectively generated plans, which supports efficient public participation and aids in building information management systems for traditional village protection.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Selection of Software Platform: CityEngine\u003c/h2\u003e \u003cp\u003eParametric design technology operates on a computer software platform, and CityEngine has been chosen for this research. As a software compatible with Python programming, CityEngine can effectively address complex issues in traditional village spatial forms through secondary development. Its seamless integration with ArcGIS allows for rapid modeling using GIS data, making it particularly advantageous for large-scale 3D form modeling [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. The parametric design process in CityEngine follows a sequence as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e: establishing the street network, segmenting blocks, modeling buildings, and creating detailed scenes. Through associative rules, CityEngine can dynamically adjust various objects within the model [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Research Ideas\u003c/h2\u003e \u003cp\u003eEmploying data technology, this study confronts the protection and development challenges of traditional Chinese villages with a focus on spatial analysis and reconstruction. Spatial analysis involves separately identifying the roads, blocks, and buildings that constitute the characteristic elements of traditional village space, and transforming optimized feature points into parameters and rules. Spatial reconstruction uses computer language algorithms to automatically generate spatial textures based on spatial feature data extraction and parameter analysis, facilitating the automatic reconstruction and weaving of traditional village spatial textures [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. The logical framework of the research is detailed in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3. Extraction of Core Parameters of Spatial Characteristics in Traditional Chinese Villages","content":"\u003cp\u003eThis section details the process of identifying and codifying the core parameters that define the spatial characteristics of traditional Chinese villages.\u003c/p\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n\u003ch2\u003e3.1. Spatial Feature Analysis\u003c/h2\u003e\n\u003cp\u003eSpatial feature analysis involves converting spatial elements into quantifiable parameters and rules for descriptive analysis. This process includes two stages: quantitative analysis of spatial features and their parameterized translation. Initially, spatial features are deconstructed based on principles of spatial elements\u0026rsquo; integrity, with basic elements of roads, blocks, and buildings being identified and separate parameter sets being constructed for each. These parameters are designed to independently represent and control specific features. Subsequently, algorithmic rules are developed to extract parameter values from spatial forms, translating them into computer-readable data linked to spatial elements through functions and equations, thus establishing constraint relationships.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n\u003ch2\u003e3.2. Parameter Analysis and Extraction Rules of Road Spatial Features\u003c/h2\u003e\n\u003cp\u003eA detailed analysis of the spatial characteristics of traditional village roads reveals the internal dynamics and functional traits of their morphological development. The parameterized analysis begins with preprocessing existing roads to identify and remove redundant information. Roads are then segmented into subgraph sets to isolate fundamental compositional elements, which are subsequently translated into parameters or rules. Algorithmic rules are formulated to extract parameter values from the existing terrain [\u003cspan class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e]. The effective parameters and extraction rules for road spatial features, as determined through experimentation, are presented in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eRoad spatial features parameters and extraction algorithms.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eClassification\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eForm\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eParameter\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eExtraction Algorithm\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"7\" align=\"left\"\u003e\n\u003cp\u003eOverall morphological characteristics of roads\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eRoad network morphology\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRoad network morphology mode\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eExtract characteristics based on the current road network\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNumber of village centers\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBased on on-site research and experience judgment\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNumber of roads\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNumber of road sections\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eThe number of sections of a single road\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eRoad intersection\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMinimum distance between road intersections\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(IntersectionsDiatanceMin)\u0026thinsp;=\u0026thinsp;Min(d\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ed\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ed\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e...\u003cem\u003ed\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e);\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ed represent the shortest road distance between road network intersections\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIntersection ratio\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eR\u0026thinsp;=\u0026thinsp;Nr/Ni\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNr represent number of road nodes\u003c/p\u003e\n\u003cp\u003eNi represent number of intersection nodes\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMinimum angle of intersection\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(MinAngle)\u0026thinsp;=\u0026thinsp;Min(\u0026theta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e\u0026theta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e\u0026theta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e...\u003cem\u003e\u0026theta;\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e);\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u0026theta; represent minimum value of intersection angle\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRoad deflection angle\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMaximum deviation angle of the road\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(MaxDeflectionAngle)\u0026thinsp;=\u0026thinsp;Max(\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e...\u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e);\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026beta;\u003c/em\u003e represent the maximum value of the minimum angle set between adjacent two sections of road\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"8\" align=\"left\"\u003e\n\u003cp\u003eCharacteristics of Road Plane Morphology\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"4\" align=\"left\"\u003e\n\u003cp\u003eRoad length\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLong road length(lrl)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003el\u003c/em\u003e\u003csub\u003e\u003cem\u003eave\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e=Average(l\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003el\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003el\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e...\u003cem\u003el\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ef(lrl)\u0026thinsp;=\u0026thinsp;Average(l\u003c/em\u003e\u003csub\u003e\u003cem\u003ea1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003el\u003c/em\u003e\u003csub\u003e\u003cem\u003ea2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003el\u003c/em\u003e\u003csub\u003e\u003cem\u003ea3\u003c/em\u003e\u003c/sub\u003e...\u003cem\u003el\u003c/em\u003e\u003csub\u003e\u003cem\u003ean\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e), among them l\u003c/em\u003e\u003csub\u003e\u003cem\u003ean\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e\u0026gt;l\u003c/em\u003e\u003csub\u003e\u003cem\u003eave\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ef(srl)\u0026thinsp;=\u0026thinsp;Average(l\u003c/em\u003e\u003csub\u003e\u003cem\u003eb1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003el\u003c/em\u003e\u003csub\u003e\u003cem\u003eb2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003el\u003c/em\u003e\u003csub\u003e\u003cem\u003eb3\u003c/em\u003e\u003c/sub\u003e...\u003cem\u003el\u003c/em\u003e\u003csub\u003e\u003cem\u003ebn\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e), among them l\u003c/em\u003e\u003csub\u003e\u003cem\u003ebn\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e\u0026lt;l\u003c/em\u003e\u003csub\u003e\u003cem\u003eave\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eShorter road length(srl)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eElastic interval of longer road length (elrl)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(elrl)=\u003c/em\u003e[│\u003cem\u003emax(l\u003c/em\u003e\u003csub\u003e\u003cem\u003ea1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003el\u003c/em\u003e\u003csub\u003e\u003cem\u003ea2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...l\u003c/em\u003e\u003csub\u003e\u003cem\u003ean\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)-f(lrl)\u003c/em\u003e│\u003cem\u003e+\u003c/em\u003e│\u003cem\u003emin(l\u003c/em\u003e\u003csub\u003e\u003cem\u003ea1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003el\u003c/em\u003e\u003csub\u003e\u003cem\u003ea2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...l\u003c/em\u003e\u003csub\u003e\u003cem\u003ean\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)-f(lrl)\u003c/em\u003e│]\u003cem\u003e/2\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eElastic interval of shorter road length (esrl)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(esrl)=\u003c/em\u003e[│\u003cem\u003emax(l\u003c/em\u003e\u003csub\u003e\u003cem\u003eb1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003el\u003c/em\u003e\u003csub\u003e\u003cem\u003eb2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003el\u003c/em\u003e\u003csub\u003e\u003cem\u003eb3\u003c/em\u003e\u003c/sub\u003e...\u003cem\u003el\u003c/em\u003e\u003csub\u003e\u003cem\u003ebn\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)-f(srl)\u003c/em\u003e│\u003cem\u003e+\u003c/em\u003e│\u003cem\u003emin(l\u003c/em\u003e\u003csub\u003e\u003cem\u003eb1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003el\u003c/em\u003e\u003csub\u003e\u003cem\u003eb2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003el\u003c/em\u003e\u003csub\u003e\u003cem\u003eb3\u003c/em\u003e\u003c/sub\u003e...\u003cem\u003el\u003c/em\u003e\u003csub\u003e\u003cem\u003ebn\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)-f(srl)\u003c/em\u003e│]\u003cem\u003e/2\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"4\" align=\"left\"\u003e\n\u003cp\u003eRoad width\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMain road width (mrw)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(mrw)\u0026thinsp;=\u0026thinsp;Average(w\u003c/em\u003e\u003csub\u003e\u003cem\u003em1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ew\u003c/em\u003e\u003csub\u003e\u003cem\u003em2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ew\u003c/em\u003e\u003csub\u003e\u003cem\u003em3\u003c/em\u003e\u003c/sub\u003e...\u003cem\u003ew\u003c/em\u003e\u003csub\u003e\u003cem\u003emn\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003esecondary road width (srw)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(srw)\u0026thinsp;=\u0026thinsp;Average(w\u003c/em\u003e\u003csub\u003e\u003cem\u003es1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ew\u003c/em\u003e\u003csub\u003e\u003cem\u003es2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ew\u003c/em\u003e\u003csub\u003e\u003cem\u003es3\u003c/em\u003e\u003c/sub\u003e...\u003cem\u003ew\u003c/em\u003e\u003csub\u003e\u003cem\u003esn\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eElastic range of main road width (emrw)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(emrw)=\u003c/em\u003e[│\u003cem\u003emax(w\u003c/em\u003e\u003csub\u003e\u003cem\u003em1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ew\u003c/em\u003e\u003csub\u003e\u003cem\u003em2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ew\u003c/em\u003e\u003csub\u003e\u003cem\u003em3\u003c/em\u003e\u003c/sub\u003e...\u003cem\u003ew\u003c/em\u003e\u003csub\u003e\u003cem\u003emn\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)-f(mrw)\u003c/em\u003e│\u003cem\u003e+\u003c/em\u003e│\u003cem\u003emin(w\u003c/em\u003e\u003csub\u003e\u003cem\u003em1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ew\u003c/em\u003e\u003csub\u003e\u003cem\u003em2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ew\u003c/em\u003e\u003csub\u003e\u003cem\u003em3\u003c/em\u003e\u003c/sub\u003e...\u003cem\u003ew\u003c/em\u003e\u003csub\u003e\u003cem\u003emn\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)-f(mrw)\u003c/em\u003e│]\u003cem\u003e/2\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eElastic range of secondary road width (esrw)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(esrw)=\u003c/em\u003e[│\u003cem\u003emax(w\u003c/em\u003e\u003csub\u003e\u003cem\u003es1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ew\u003c/em\u003e\u003csub\u003e\u003cem\u003es2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ew\u003c/em\u003e\u003csub\u003e\u003cem\u003es3\u003c/em\u003e\u003c/sub\u003e...\u003cem\u003ew\u003c/em\u003e\u003csub\u003e\u003cem\u003esn\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)-f(srw)\u003c/em\u003e│\u003cem\u003e+\u003c/em\u003e│\u003cem\u003emin(w\u003c/em\u003e\u003csub\u003e\u003cem\u003es1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ew\u003c/em\u003e\u003csub\u003e\u003cem\u003es2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ew\u003c/em\u003e\u003csub\u003e\u003cem\u003es3\u003c/em\u003e\u003c/sub\u003e...\u003cem\u003ew\u003c/em\u003e\u003csub\u003e\u003cem\u003esn\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)-f(srw)\u003c/em\u003e│]\u003cem\u003e/2\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eVertical morphological characteristics of roads\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"4\" align=\"left\"\u003e\n\u003cp\u003eRoad elevation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRoad elevation max\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(RoadElevationMax)\u0026thinsp;=\u0026thinsp;Max\u003c/em\u003e[\u003cem\u003eElevation(e\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ee\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ee\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e...\u003cem\u003ee\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e]\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRoad elevation min\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(RoadElevationMin)\u0026thinsp;=\u0026thinsp;Min\u003c/em\u003e[\u003cem\u003eElevation(e\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ee\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ee\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e...\u003cem\u003ee\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e]\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRoad elevation average\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(RoadElevationAverage)\u0026thinsp;=\u0026thinsp;Ave\u003c/em\u003e[\u003cem\u003eElevation(e\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ee\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ee\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e...\u003cem\u003ee\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e]\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eElastic range of road elevation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(e\u003c/em\u003e\u003csub\u003e\u003cem\u003eere\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)=\u003c/em\u003e[│\u003cem\u003ee\u003c/em\u003e\u003csub\u003e\u003cem\u003emax\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e-e\u003c/em\u003e\u003csub\u003e\u003cem\u003eave\u003c/em\u003e\u003c/sub\u003e│\u003cem\u003e+\u003c/em\u003e│\u003cem\u003ee\u003c/em\u003e\u003csub\u003e\u003cem\u003emin\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e-e\u003c/em\u003e\u003csub\u003e\u003cem\u003eave\u003c/em\u003e\u003c/sub\u003e│]\u003cem\u003e/2\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRoad slope\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSlope range\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(SlopeRange)=\u003c/em\u003e[\u003cem\u003eS\u003c/em\u003e\u003csub\u003e\u003cem\u003emax\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003eS\u003c/em\u003e\u003csub\u003e\u003cem\u003emin\u003c/em\u003e\u003c/sub\u003e]\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 illustrations for parameterized translation of road spatial features are as follows:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eThe road network morphology can be summarized into three types: organic, raster, and radial. Complex road networks can be achieved through the superposition and fusion of these three types (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eThe number of village centers refers to the number of public centers in the village, and the road density in the village center is often higher than that in the periphery (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eFigure 5 illustrates the spatial quantification feature for road length, road angle, and road intersections, where 02 represents road intersections, 04 represents road nodes, d1 represents distance between road intersections, \u0026theta; represents the road intersection angle, and \u0026beta; represents the angle between roads.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n\u003ch2\u003e3.3. Parameter Analysis and Extraction Rules for Spatial Features of Blocks\u003c/h2\u003e\n\u003cp\u003eThe organizational structure and planar morphology of blocks are crucial in shaping the spatial form of traditional villages. The parameterization analysis aims to delineate block divisions that reflect their functions and closely match actual property blocks. Blocks are decomposed into subgraphs, and their organizational and morphological characteristics are converted into parameters and rules [58]. Research and reconstruction experiments on traditional village block patterns have yielded specific parameter indicators and extraction rules, which are outlined in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eBlocks spatial feature parameters and extraction algorithms.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eClassification\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eForm\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eParameter\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eExtraction Algorithm\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"11\" align=\"left\"\u003e\n\u003cp\u003eOrganizational structure characteristics\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eCluster form\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBlock subdivision form\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(SubdivideType)\u0026thinsp;=\u0026thinsp;Recursive Subdivide;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ef(SubdivideType)\u0026thinsp;=\u0026thinsp;Offset Subdivide;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ef(SubdivideType)\u0026thinsp;=\u0026thinsp;Skeleton Subdivide;\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSubdivision type ratio\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ea\u003csub\u003e1\u003c/sub\u003e%,a\u003csub\u003e2\u003c/sub\u003e%,a\u003csub\u003e3\u003c/sub\u003e%, a\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;a\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;a\u003csub\u003e3\u003c/sub\u003e=100\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eBlock density\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMaximum block density\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(DensityMax)\u0026thinsp;=\u0026thinsp;Max(a\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ea\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ea\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...a\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMinimum block density\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(DensityMin)\u0026thinsp;=\u0026thinsp;Min(a\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ea\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ea\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...a\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAverage block density\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(DensityAverage)\u0026thinsp;=\u0026thinsp;Average(a\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ea\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ea\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...a\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eBlock direction\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMaximum block direction\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(DirectionMax)\u0026thinsp;=\u0026thinsp;Max(\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMinimum block direction\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(DirectionMin)\u0026thinsp;=\u0026thinsp;Min(\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAverage block direction\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(DirectionAverage)\u0026thinsp;=\u0026thinsp;Average(\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTerrain adaptation methods\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTerrain adaptation methods\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(LotAlignment)=ཛUneven,Minmum,Maxmum,Averageཝ\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFunctional blocks number ratio\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFunctional blocks number ratio\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ea\u003csub\u003e1\u003c/sub\u003e%,a\u003csub\u003e2\u003c/sub\u003e%,a\u003csub\u003e3\u003c/sub\u003e...a\u003csub\u003en\u003c/sub\u003e%, a\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;a\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;a\u003csub\u003e3\u003c/sub\u003e+...a\u003csub\u003en\u003c/sub\u003e=100\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBlock interface density\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBlock interface density\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e,R\u003csub\u003ei\u003c/sub\u003e represent the length of the base on one side of the boundary of the i-th building adjacent to the block; L is the length of the block boundary\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"13\" align=\"left\"\u003e\n\u003cp\u003ePlanar morphological features\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"4\" align=\"left\"\u003e\n\u003cp\u003eBlock area\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMaximum block area\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(AreaMax)\u0026thinsp;=\u0026thinsp;Max\u003c/em\u003e[\u003cem\u003earea(a\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ea\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ea\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...a\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e]\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMinimum block area\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(AreaMin)\u0026thinsp;=\u0026thinsp;Min\u003c/em\u003e[\u003cem\u003earea(a\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ea\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ea\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...a\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e]\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAverage block area\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(AreaAverage)\u0026thinsp;=\u0026thinsp;Average\u003c/em\u003e[\u003cem\u003earea(a\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ea\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ea\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...a\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e]\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eThe interval size and probability distribution of block area\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef[AreaFrequency(i-j)]\u0026thinsp;=\u0026thinsp;Frequency(date_arry,bin_arry)\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"6\" align=\"left\"\u003e\n\u003cp\u003eBlock boundary line\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eThe longest side length of the bounding rectangle on the block\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(EdgeLongest)\u0026thinsp;=\u0026thinsp;Max(l\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003el\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003el\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...l\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eThe shortest side length of the bounding rectangle of the block\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(EdgeShortest)\u0026thinsp;=\u0026thinsp;Min(l\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003el\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003el\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...l\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eThe average side length of the bounding rectangle of the block\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(EdgeAverage)\u0026thinsp;=\u0026thinsp;Average(l\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003el\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003el\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...l\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eThe maximum length-width\u0026nbsp;ratio of bounding rectangle outside the block\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(MaxtLength/Width ratio)\u0026thinsp;=\u0026thinsp;Max(a\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ea\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ea\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...a\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eThe minimum length-width\u0026nbsp;ratio of bounding rectangle outside the block\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(MintLength/Width ratio)\u0026thinsp;=\u0026thinsp;Min(a\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ea\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ea\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...a\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eThe average length-width\u0026nbsp;ratio of bounding rectangle outside the block\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(AverageLength/Width ratio)\u0026thinsp;=\u0026thinsp;Average(a\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ea\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ea\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...a\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eBlock interior angle\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMaximum block interior angle\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(CoenerAngleMax)\u0026thinsp;=\u0026thinsp;Max(\u0026theta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e\u0026theta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e\u0026theta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...\u0026theta;\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMinimum block interior angle\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(CoenerAngleMim)\u0026thinsp;=\u0026thinsp;Min(\u0026theta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e\u0026theta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e\u0026theta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...\u0026theta;\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAverage block interior angle\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(CoenerAngleAverage)\u0026thinsp;=\u0026thinsp;Average(\u0026theta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e\u0026theta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e\u0026theta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...\u0026theta;\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e\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 illustrations of parameterized translation of block spatial features are as follows:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eThe block subdivision forms have three types: recursive subdivide, offset subdivide and skeleton subdivide (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e illustrates the quantitative extraction method for block planar morphological features, where \u0026theta; represents the block interior angle, L and W represent block boundary lines, and L\u0026rsquo; represents the block direction line, which is a straight line parallel to the long side of the bounding rectangle outside the block.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n\u003ch2\u003e3.4. Parameter Analysis and Extraction Rules of Building Space Features\u003c/h2\u003e\n\u003cp\u003eThe spatial characteristics of buildings are captured by translating their planar and facade form elements into parameters and rules. The established parameter indicators and corresponding extraction rules are detailed in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\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\u003eBuildings spatial feature parameters and extraction algorithms.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eClassification\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eForm\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eParameter\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eExtraction Algorithm\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"12\" align=\"left\"\u003e\n\u003cp\u003eCharacteristics of building plane form\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eBuilding foundation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBuilding foundation shape\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eUsing typological methods to extract the shape of building plans\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eScale of building foundation shape\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003es\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e%,s\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e%,s\u003c/em\u003e\u003csub\u003e\u003cem\u003e3...\u003c/em\u003e\u003c/sub\u003e\u003cem\u003es\u003c/em\u003e\u003csub\u003e\u003cem\u003en.\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e%, s\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;s\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;s\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e+...s\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e=100\u003c/em\u003e, s\u003csub\u003en\u003c/sub\u003e% represent the ratio of the number of n-th type building plans to the total number of buildings\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eBuilding width\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMaximum building width\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(BuildingWidthMax)\u0026thinsp;=\u0026thinsp;Max(w\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ew\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ew\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...w\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMinimum building width\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(BuildingWidthMin)\u0026thinsp;=\u0026thinsp;Min(w\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ew\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ew\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...w\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAverage building width\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(BuildingWidthAverage)\u0026thinsp;=\u0026thinsp;Average(w\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ew\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ew\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...w\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eBuilding depth\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMaximum building depth\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(BuildingDepthMax)\u0026thinsp;=\u0026thinsp;Max(d\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ed\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ed\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...d\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMinimum building depth\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(BuildingDepthMin)\u0026thinsp;=\u0026thinsp;Min(d\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ed\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ed\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...d\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e))\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAverage building depth\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(BuildingDepthAverage)\u0026thinsp;=\u0026thinsp;Average(d\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ed\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ed\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...d\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e))\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"4\" align=\"left\"\u003e\n\u003cp\u003eBuilding area\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMaximum building area\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(BuildingShapeAreaMax)\u0026thinsp;=\u0026thinsp;Max\u003c/em\u003e[\u003cem\u003earea(a\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ea\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ea\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...a\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e]\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMinimum building area\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(BuildingShapeAreaMin)\u0026thinsp;=\u0026thinsp;Min\u003c/em\u003e[\u003cem\u003earea(a\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ea\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ea\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...a\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e]\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAverage building area\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(BuildingShapeAreaAverage)\u0026thinsp;=\u0026thinsp;Average\u003c/em\u003e[\u003cem\u003earea(a\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ea\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003ea\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...a\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e]\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eConcentrated distribution range of building area\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef[BuildingShapeArea(i-j)]\u0026thinsp;=\u0026thinsp;Frequency(date_arry,bin_arry)\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"12\" align=\"left\"\u003e\n\u003cp\u003eCharacteristics of building facade form\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"4\" align=\"left\"\u003e\n\u003cp\u003eBuilding height\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMaximum building height\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(BuildingHeightMax)\u0026thinsp;=\u0026thinsp;Max(\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMinimum building height\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(BuildingHeightMin)\u0026thinsp;=\u0026thinsp;Min(\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAverage building height\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(BuildingHeightAverage)\u0026thinsp;=\u0026thinsp;Average(\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eConcentrated distribution range of building height\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef[BuildingHeight(i-j)]\u0026thinsp;=\u0026thinsp;Frequency(date_arry,bin_arry)\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBuilding storey number\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBuilding storey number\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003es\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e%,s\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e%,s\u003c/em\u003e\u003csub\u003e\u003cem\u003e3...\u003c/em\u003e\u003c/sub\u003e\u003cem\u003es\u003c/em\u003e\u003csub\u003e\u003cem\u003en.\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e%, s\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;s\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;s\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e+...s\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e=100\u003c/em\u003e, s\u003csub\u003en\u003c/sub\u003e% represent the proportion of floors in the n-th type of building\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"4\" align=\"left\"\u003e\n\u003cp\u003eBuilding direction\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMaximum building direction\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(BuildingDirectionMax)\u0026thinsp;=\u0026thinsp;Max(\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMinimum building direction\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(BuildingDirectionMin)\u0026thinsp;=\u0026thinsp;Min(\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAverage building direction\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef(BuildingDirectionAverage)\u0026thinsp;=\u0026thinsp;Average(\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e,\u003cem\u003e...\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eConcentrated distribution range of building direction\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ef\u003c/em\u003e[\u003cem\u003eBuildingDirection(i-j)\u003c/em\u003e]\u0026thinsp;\u003cem\u003e=\u0026thinsp;Frequency(date_arry,bin_arry)\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eRoof\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRoof style\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eb\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e%,b\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e%,b\u003c/em\u003e\u003csub\u003e\u003cem\u003e3...\u003c/em\u003e\u003c/sub\u003e\u003cem\u003eb\u003c/em\u003e\u003csub\u003e\u003cem\u003en.\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e%, b\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;b\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;b\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e+...b\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e=100\u003c/em\u003e, b\u003csub\u003en\u003c/sub\u003e% represent the proportion of the n-th type of roof form\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRoof material\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ec\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e%,c\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e%,c\u003c/em\u003e\u003csub\u003e\u003cem\u003e3...\u003c/em\u003e\u003c/sub\u003e\u003cem\u003ec\u003c/em\u003e\u003csub\u003e\u003cem\u003en.\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e%, c\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;c\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;c\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e+...c\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e=100\u003c/em\u003e, c\u003csub\u003en\u003c/sub\u003e% represent the proportion of the n-th type roof material\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eWall\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBuilding wall material\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ed\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e%,d\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e%,d\u003c/em\u003e\u003csub\u003e\u003cem\u003e3...\u003c/em\u003e\u003c/sub\u003e\u003cem\u003ed\u003c/em\u003e\u003csub\u003e\u003cem\u003en.\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e%, d\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;d\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e+\u0026thinsp;d\u003c/em\u003e\u003csub\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e+...d\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e=100\u003c/em\u003e, d\u003csub\u003en\u003c/sub\u003e% represent the proportion of the n-th type of building wall material\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 illustrations of parameterized translation of building spatial features are as follows:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eThe patterns of building foundation shapes mainly include I-shaped, L-shaped, U-shaped, and combinations of these types (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eThe building angle is the smaller angle between the building direction line and the reference line. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003e illustrates the extraction rules for building angle.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e10\u003c/span\u003e illustrates the extracted elements of building facade morphological features.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/div\u003e"},{"header":"4. Parameterized Reconstruction and Practical Application of Traditional Village Space","content":"\u003cp\u003eThis section outlines the process of parameterized reconstruction of traditional village space and its practical applications.\u003c/p\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n\u003ch2\u003e4.1. Parameterized Space Reconstruction\u003c/h2\u003e\n\u003cp\u003eParameterization technology, coupled with computer programming algorithms, enables the automatic generation of spatial textures that mimic original features, facilitating the reconstruction and weaving of traditional village textures. The reconstruction process is divided into two main parts: the organization of associated feature elements and the construction of visualization models.\u003c/p\u003e\n\u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\n\u003ch2\u003e4.1.1. Organization of Associated Feature Elements\u003c/h2\u003e\n\u003cp\u003eUtilizing the CityEngine software platform\u0026rsquo;s generation module, a set of logical rules and code expressions are created to construct spatial \"growth\" within the constraints of space (dimensional and geometric) and organizational rules. The spatial form elements of roads, blocks, and buildings are arranged in a cohesive relationship model. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e11\u003c/span\u003e illustrates this organization, where A, B, and C represent spatial types, a\u003csub\u003e1\u003c/sub\u003e, b\u003csub\u003e1\u003c/sub\u003e, and c\u003csub\u003e1\u003c/sub\u003e represent the feature elements constituting spatial types, the lines between elements indicate constraint relationships, b\u003csub\u003e31\u003c/sub\u003e signifies the conditions for constraining spatial elements, c\u003csub\u003e23\u003c/sub\u003e denotes the conditions for constraining different spatial elements of the same type, and ab\u003csub\u003e12\u003c/sub\u003e represents the constraint conditions for spatial elements between different types.\u003c/p\u003e\n\u003cp\u003eThe spatial generation of roads is carried out through the StreetModule of the CE software platform, which decomposes the roads into five components: street, sidewalk, crossing, junction, and junctionentry. The components are organized in an orderly manner into a framework according to constraint conditions, and through the secondary development of CGA rule files, revise and optimize the generated road spatial form. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e12\u003c/span\u003e illustrates the process of road space reconstruction.\u003c/p\u003e\n\u003cp\u003eThe reconstruction of block space and building is mainly achieved through programming methods. By using the CGA language provided by CE and writing CGA rule files, spatial features and constraint relationships between features are integrated to form a spatial generation relationship model. Parameter values are substituted into the CGA file and imported into the CE platform for spatial generation. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e13\u003c/span\u003e illustrates the process of block space and building reconstruction.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\n\u003ch2\u003e4.1.2. Visualization Model Construction\u003c/h2\u003e\n\u003cp\u003eEmploying the CityEngine software platform, visual models are constructed based on the overall linked relationship model. This is done using parameter-driven and relationship-driven mechanisms to create two-dimensional graphics and three-dimensional visualization images. These models simulate the generation of basic spatial features and serve as a foundation for the subsequent reconstruction of the traditional village space.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n\u003ch2\u003e4.2. Practical Application of Parameterized Space Reconstruction\u003c/h2\u003e\n\u003cdiv id=\"Sec16\" class=\"Section3\"\u003e\n\u003ch2\u003e4.2.1. Research Area\u003c/h2\u003e\n\u003cp\u003eQiji Village, located in Yanggu County, Shandong Province, is recognized on the sixth list of traditional Chinese villages. As an important historical dock of the Grand Canal since the Yuan Dynasty, Qiji Village has been a prosperous trading hub. Its well-preserved ancient dock and connected commercial street are significant components of the Grand Canal\u0026rsquo;s World Heritage application, as shown in Fig.\u0026nbsp;14(a). However, with the decline of river transport, Qiji Village faces challenges such as depopulation, dilapidated buildings, and poor infrastructure, leading to the erosion of its social functions, cultural values, and spatial features. The study focuses on a 22-hectare area designated for the protection and renewal of Qiji Village, as shown in Fig.\u0026nbsp;14(b).\u003c/p\u003e\n\u003cp\u003eIn the national spatial planning context, Qiji Village is within the urban development boundaries. The main challenge is integrating traditional village protection with urban construction, preserving spatial patterns and historical buildings, improving infrastructure, and enhancing the village\u0026rsquo;s vitality. This research aims to address these challenges.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\" class=\"Section3\"\u003e\n\u003ch2\u003e4.2.2. Data Acquisition and Establishment of Parameter Sets\u003c/h2\u003e\n\u003cp\u003eData collection involves on-site research and the use of open-source geographic information to gather data on roads, land parcels, and buildings within the Qiji Village landscape protection area. This data serves as the foundation for generating renewed spatial morphological features. Following the earlier mentioned parameter analysis and extraction rules, the data is categorized, integrated, and current spatial feature parameter values are extracted. These values are optimized to reflect changes in urban development and residents\u0026rsquo; needs, creating a traditional village spatial characteristic parameter database to support the automatic reconstruction of spatial styles (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\" class=\"Section3\"\u003e\n\u003ch2\u003e4.2.3. Reconstruction and Continuation of Spatial Texture\u003c/h2\u003e\n\u003cp\u003eUsing the spatial feature parameter database, the study explores the automatic generation of traditional village spatial textures with the CityEngine software platform. The process begins with the application of traditional village boundary extraction rules, combined with the scope of traditional village protection planning and the construction area designated by national land space, to determine the areas requiring renewal. The road space form generation module is then used to generate the road network form by adjusting parameter values. The generated road form is further refined by importing rule files for secondary development (Fig.\u0026nbsp;16a). Following this, block segmentation and block spatial texture reconstruction are performed through programming using the CGA rule language provided by CityEngine or compatible Python language (Fig.\u0026nbsp;16b). Finally, parameterized 3D modeling of buildings is conducted using CGA syntax or rule files written in Python to generate and reconstruct the spatial texture of buildings (Fig.\u0026nbsp;16c).\u003c/p\u003e\n\u003cp\u003eAs demonstrated, parametric design can automatically generate planning schemes through programming with rule-based languages based on extracted parameter data. By adjusting parameter indicators, the automatically generated plans can be optimized and adaptively modified to reconstruct planning and design schemes that not only retain traditional village characteristics but also meet modern living needs. This alignment with traditional village protection and future development trends makes the planning and design process more rational and efficient.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/div\u003e"},{"header":"5. Conclusion and Discussion","content":"\u003cp\u003eDigital technology is increasingly applied to protect traditional settlements. Parameterization technology extracts the systematic rules governing the spatial information of traditional settlements, overcoming limitations such as potential biases and inaccuracies inherent in subjective methods of information transmission, and ensuring the accurate preservation of historical landscape information. By integrating advanced technologies and combining human and computer decision-making, planning schemes are generated that preserve the spatial characteristics of case studies while incorporating modern living needs. Digital technology promises to bring order and innovation to traditional spaces.\u003c/p\u003e \u003cp\u003eThe digital generation of Qiji Village\u0026rsquo;s protection and development planning scheme validates the effectiveness and technical advantages of automatic generation methods based on the parameterization of spatial feature elements. Parametric design utilizes parameters and algorithms, with its rich and rigorous design logic, to improve design efficiency. This reflects the advantages of parametric design methods in terms of systematicity, interpretability, and controllability. Despite the diversity of traditional Chinese villages, their unique bottom-up growth pattern provides a recognizable and consistent basis for digital generative design techniques. With advancements in artificial intelligence and digital technology, and as spatial data on traditional villages becomes richer and more refined, data-driven automatic generation of planning and design schemes will increasingly address the complex challenges of protecting and renewing traditional settlements and historical buildings.\u003c/p\u003e \u003cp\u003eOne important purpose of computer-aided planning and design is to gradually move towards intelligent systems that alleviate human workload and ensure that the process remains human-centric. It transforms design principles into intelligent rules and hands them over to computers, freeing more human energy into design decisions and forming a human-machine interactive planning and design process. Any planning and design scheme is almost never carried out on a blank sheet of paper. The current situation, existing constraints themselves, manual preset of key design intentions are important factors in determining the outcome of the scheme, which is a work scope that computers cannot automatically complete. For the results generated through assisted generation, human intelligence needs to be deeply involved in screening, evaluating, and adjusting, ultimately transforming them into design solutions guided by the thinking of planners. During the adjustment process, the barriers between planners and computers are broken to the greatest extent possible. Human intelligence and role become the top priority in the computer-aided process.\u003c/p\u003e \u003cp\u003eThere are certain limitations to this research. First, The traditional parameterization method is mainly based on human settings. If designers intervene excessively in the design process, the resulting designs may lack true intelligence and automation, and it is difficult to get rid of the dependence on subjective factors of humans. Second, traditional village protection is a complex task that involves the inherent mechanism of multi-scale space, with more diverse humanistic and social content. It is necessary to consider a range of objectives, encompassing both objective constraints, such as land rights and heritage conservation, and subjective factors, such as culture, social systems, economy, and aesthetics. In future studies, deep learning methods can be applied to the process of extracting spatial features and organizational rules, to accurately perceive and recognize complex spatial forms[\u003cspan additionalcitationids=\"CR40\" citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], minimizing manual intervention during the generation process. In addition, it is necessary to multidimensional optimization parameterized content system, incorporate \"invisible\" indicators such as social and economic development, human demands, sociocultural and institutional structures into the parameterized indicator system. Application of planning and design considering traditional village differentiation is also important, the construction of a national database detailing the morphological characteristics of traditional villages would be beneficial.\u003c/p\u003e \u003cp\u003eIn contemplating the role of technology in planning, it is worth considering whether computer-aided planning and design have inadvertently given precedence to technology over other aspects. Does intelligent tool thinking weaken the dominant position of humanism in creative thinking? As the French philosopher Bernard Stiegler once said, \u0026ldquo;We need to create a new technological culture to respond to the era of technology\u0026rdquo; [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Therefore, under new technological conditions, we need to consider how to reshape spatial planning and design under human-machine symbiosis.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u0026nbsp;\u003c/strong\u003eConceptualization, Yong Fan; methodology, Yong Fan; software, Xuan Li, Yong Fan; validation, Xuan Li, Yong Fan; formal analysis, Yong Fan; investigation, Yong Fan, Xuan Li, Wen-jie Xiao; resources, Yong Fan, Xuan Li; data curation, Yong Fan, Xuan Li, Wen-jie Xiao; writing\u0026mdash;original draft preparation, Yong Fan; writing\u0026mdash;review \u0026amp; editing, Di Wang; visualization, Yong Fan, Xuan Li; supervision, Di Wang; project administration, Yong Fan, Di Wang. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability:\u0026nbsp;\u003c/strong\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis research was funded by the Ministry of Education of the People\u0026rsquo;s Republic of China: 21YJCZH024 and the People\u0026rsquo;s Government of Shandong Province: ZR2021ME226.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWen Quan; Tang Jianguo; Cai Kuangyuan. The Authenticity and Integrity of Traditional Village Protection from the Perspective of Vernacular Built Heritage: A Case Study of Three Gorges Original Township Hankuimen. \u003cem\u003eHuazhong Architecture\u003c/em\u003e\u003cem\u003e. \u003c/em\u003e\u003cstrong\u003e2023\u003c/strong\u003e, \u003cem\u003e41\u003c/em\u003e, 143-147.\u003c/li\u003e\n\u003cli\u003eHe Ziyi; Liu Juan; Tan Jiaxing; Gao Chaoxuan. Research on Digital Protection and Inheritance of Traditional Villages Based on the Whole Life Cycle. \u003cem\u003eDevelopment of \u003c/em\u003e\u003cem\u003eS\u003c/em\u003e\u003cem\u003emall \u003c/em\u003e\u003cem\u003eC\u003c/em\u003e\u003cem\u003eities\u003c/em\u003e\u003cem\u003e \u003c/em\u003e\u003cem\u003e\u0026amp;\u003c/em\u003e\u003cem\u003e \u003c/em\u003e\u003cem\u003eT\u003c/em\u003e\u003cem\u003eowns\u003c/em\u003e\u003cem\u003e. \u003c/em\u003e\u003cstrong\u003e2023\u003c/strong\u003e, \u003cem\u003e41\u003c/em\u003e, 46-52.\u003c/li\u003e\n\u003cli\u003eCai Jun; Wen Rigiang; Jiang Wei; Yan Jiao; Lu Lifuan. DeepLabV3+ Improved Algorithm for National Building Recognition in Traditional Village Aerial Images. \u003cem\u003eBulletin of Surveying and Mapping\u003c/em\u003e\u003cem\u003e. \u003c/em\u003e\u003cstrong\u003e2023\u003c/strong\u003e, \u003cem\u003e04,\u003c/em\u003e\u003cem\u003e \u003c/em\u003e49-53.\u003c/li\u003e\n\u003cli\u003eWu Ning; Wen Tianrong; Tong Lei. Research On Application Of Parametric Analysis And Reconstruction In Village Space Exemplified By A Traditional Village In Guizhou. \u003cem\u003eArchitecture\u003c/em\u003e \u0026amp; \u003cem\u003eCulture\u003c/em\u003e\u003cem\u003e. \u003c/em\u003e\u003cstrong\u003e2016\u003c/strong\u003e, \u003cem\u003e0\u003c/em\u003e\u003cem\u003e5\u003c/em\u003e, 142-143.\u003c/li\u003e\n\u003cli\u003eQin Qiaohua; Xiao Dawei; Luo Mingnan; Tao Jin. A Study on the classification of traditional village images based on convolutional neural network. \u003cem\u003eCity Planning Review\u003c/em\u003e\u003cem\u003e. \u003c/em\u003e\u003cstrong\u003e2020\u003c/strong\u003e, \u003cem\u003e44\u003c/em\u003e, 52-58.\u003c/li\u003e\n\u003cli\u003eYueping Kong; Peng Xue; Yuqian Xu; Xiaolong Li. An Environmental Pattern Recognition Method for Traditional Chinese Settlements Using Deep Learning. \u003cem\u003eApplied Sciences\u003c/em\u003e\u003cem\u003e. \u003c/em\u003e\u003cstrong\u003e2023\u003c/strong\u003e\u003cstrong\u003e, \u003c/strong\u003e\u003cem\u003e13\u003c/em\u003e, 4778.\u003c/li\u003e\n\u003cli\u003eDai Jianhua; Peng Ruoyao; Xu Lu; et al. A Survey of Information Extraction Based on Deep Neural Networks. \u003cem\u003eJournal of Southwest China Normal University (Natural Science Edition\u003c/em\u003e\u003cem\u003e. \u003c/em\u003e\u003cstrong\u003e2022\u003c/strong\u003e, \u003cem\u003e4\u003c/em\u003e, 1-11.\u003c/li\u003e\n\u003cli\u003eRussakovsky O; Deng J; Su H; et al. ImageNet large Scale Visual Recognition Challenge. \u003cem\u003eInternational Journal of Computer Vision\u003c/em\u003e\u003cem\u003e. \u003c/em\u003e\u003cstrong\u003e2015\u003c/strong\u003e, \u003cem\u003e3\u003c/em\u003e, 211-252.\u003c/li\u003e\n\u003cli\u003eQuan Steven Jige; Park James; et al. Artificial intelligence-aided design: Smart Design for sustainable city development. \u003cem\u003eEnvironment and Planning B: Urban Analytics and City Science\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003e2019\u003c/strong\u003e, \u003cem\u003e46\u003c/em\u003e\u003cem\u003e, \u003c/em\u003e1581-1599.\u003c/li\u003e\n\u003cli\u003eXiao Liu; Xu Feng; Wang Jun. Preliminary Studies on Parametric Design of New Hutong Space:A Case Study on Qianmen District in Beijing. \u003cem\u003eHuazhong Architecture. \u003c/em\u003e\u003cstrong\u003e2013\u003c/strong\u003e, \u003cem\u003e31\u003c/em\u003e, 35-39.\u003c/li\u003e\n\u003cli\u003eChen Y; Feng M. Urban form simulation in 3D based on cellular automata and building objects generation. \u003cem\u003eBuilding and Environment\u003c/em\u003e. \u003cstrong\u003e2022\u003c/strong\u003e, \u003cem\u003e226\u003c/em\u003e, 109727.\u003c/li\u003e\n\u003cli\u003eP\u0026eacute;rez-Mart\u0026iacute;nez I; Mart\u0026iacute;nez-Rojas M; Soto-Hidalgo JM. A methodology for urban planning generation: A novel approach based on generative design. \u003cem\u003eEngineering Applications of Artificial Intelligence\u003c/em\u003e. \u003cstrong\u003e2023\u003c/strong\u003e, \u003cem\u003e124\u003c/em\u003e, 106609.\u003c/li\u003e\n\u003cli\u003eZhang K H; Zhang N; Quan F M; et al. Digital Form Generation of Heritage in Historical District Based on Plan Typology and Shape Grammar: A Case Study on Kulangsu Islet. \u003cem\u003eBuildings\u003c/em\u003e. \u003cstrong\u003e2023\u003c/strong\u003e,\u003cem\u003e13\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eSugianto E; Hosea JF; Jabar BA; Irwansyah E; Fitrianah D. 3D Modelling Building of District Johar Baru Using ArcGIS Pro and CityEngine. \u003cem\u003eProcedia Computer Science\u003c/em\u003e, \u003cstrong\u003e2023\u003c/strong\u003e, \u003cem\u003e22\u003c/em\u003e7, 623-631.\u003c/li\u003e\n\u003cli\u003eYingtao Qi; Yulin Ren; Dian Zhou; Yupeng Wang; Yujia Liu; Bin Zhang. Quantitative Analysis and Cause Exploration of Architectural Feature Changes in a Traditional Chinese Village: Lingquan Village, Heyang County, Shaanxi Province. \u003cem\u003eLand\u003c/em\u003e. \u003cstrong\u003e2023\u003c/strong\u003e, \u003cem\u003e12\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eZhe Li; Si Huang; Han Wang; Yan Li. Digital Analysis of the Water Layout Ecological Wisdom in Traditional Chinese Rural Settlements: A Case Study of Liukeng Village in Jiangxi Province. \u003cem\u003eJournal of Resources and Ecology\u003c/em\u003e. \u003cstrong\u003e2022\u003c/strong\u003e, \u003cem\u003e13\u003c/em\u003e, 371-381.\u003c/li\u003e\n\u003cli\u003eShen Yinlan; Yan Xingchen; Yu Piyong; Liu Hui; Wu Guofang; He Wei. Seismic Resistance of Timber Frames with Mud and Stone Infill Walls in a Chinese Traditional Village Dwelling. \u003cem\u003eBuildings\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003e2021\u003c/strong\u003e, \u003cem\u003e11\u003c/em\u003e , 580-580.\u003c/li\u003e\n\u003cli\u003eYang Simin; Yi Lina; Guan Hui; Li Yong. A meme-based approach for knowledge mining, organization, and presentation of traditional Chinese settlement culture. \u003cem\u003eHeritage Science.\u003c/em\u003e \u003cstrong\u003e2023\u003c/strong\u003e, \u003cem\u003e11\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eZhongyi Nie; Chen Chen; Wei Pan; Tian Dong. Exploring the Dynamic Cultural Driving Factors Underlying the Regional Spatial Pattern of Chinese Traditional Villages. \u003cem\u003eBuildings\u003c/em\u003e. \u003cstrong\u003e2023\u003c/strong\u003e, \u003cem\u003e13\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eLiu Xuedong; Huang Yi; Xiang Huilin; Zhang Chen; Chen Juan; Xiao Dawei. Optimization strategies for the management mechanisms of conservation and utilization in traditional Chinese villages based on relevance analyses of performance evaluation. \u003cem\u003eJournal of Asian Architecture and Building Engineering\u003c/em\u003e. \u003cstrong\u003e2023\u003c/strong\u003e, \u003cem\u003e22\u003c/em\u003e, 1699-1713.\u003c/li\u003e\n\u003cli\u003eXu Luyao; Shi Lei; Wang Xin; Wan Yuliang; Fan Zhuo. Can tourists become disciples? The formation and mechanism of place conversion in traditional Chinese villages. Frontiers in Psychology. \u003cstrong\u003e2023\u003c/strong\u003e, \u003cem\u003e14\u003c/em\u003e, 1301127-1301127.\u003c/li\u003e\n\u003cli\u003eXiaolong Hu; Tong Yao. Study on the Synergistic Development of Chinese Traditional Villages Protection and Landscape Development. \u003cem\u003eApplied Mathematics and Nonlinear Sciences\u003c/em\u003e. \u003cstrong\u003e2024\u003c/strong\u003e, 9.\u003c/li\u003e\n\u003cli\u003eJialu Li. Community Building: An Exploration of the Path in Traditional Village Conservation and Renewal with an Example of Yim Tin Tze in Hong Kong. \u003cem\u003eJournal of Environmental and Agricultural Studies\u003c/em\u003e. \u003cstrong\u003e2022\u003c/strong\u003e, \u003cem\u003e3\u003c/em\u003e, 01-06.\u003c/li\u003e\n\u003cli\u003eYufei Lyu; Lei Zhang; Xin Liu; Xuan Ma. Microclimate-Adaptive Morphological Parametric Design of Streets and Alleys in Traditional Villages.\u003cem\u003e Buildings\u003c/em\u003e. \u003cstrong\u003e2024\u003c/strong\u003e, \u003cem\u003e14\u003c/em\u003e, 152.\u003c/li\u003e\n\u003cli\u003eWang Liangliang; Lu Yaru; Huang Wencan; HAN Jie. Analysis Methods for Landscapes and Features of Traditional Villages Based on Digital Technology: Taking Xiaocuo Village in Quanzhou as an Example. \u003cem\u003eChinese Landscape Architecture\u003c/em\u003e, \u003cstrong\u003e2023\u003c/strong\u003e, \u003cem\u003e39\u003c/em\u003e, 13-19.\u003c/li\u003e\n\u003cli\u003eYang Xi. Advances in Quantitative Research Methodologies for the Spatial Layout of Rural Settlement in Recent 20 Years. \u003cem\u003eUrban Planning International\u003c/em\u003e. \u003cstrong\u003e2020\u003c/strong\u003e, \u003cem\u003e35\u003c/em\u003e, 72-80.\u003c/li\u003e\n\u003cli\u003eLin Kefeng; Tao Wei; Gu Hengyu. Spatial form and spatial cognition of traditional villages based on space syntax: A case study of jiaju Village, Guizhou Province. \u003cem\u003eScientia Geographica Sinica\u003c/em\u003e, \u003cstrong\u003e2023\u003c/strong\u003e, \u003cem\u003e43\u003c/em\u003e, 1608-1618.\u003c/li\u003e\n\u003cli\u003eSun Li; Zhou Yifan; Sun Xuepu; Wang Ting; Yang Zhen. Spatial Syntax Analysis of Traditional Villages Based on Space Syntax: A Case Study of Linggong Village in Beijing. \u003cem\u003eJournal of Beijing University of Civil Engineering and Architecture\u003c/em\u003e. \u003cstrong\u003e2023\u003c/strong\u003e, \u003cem\u003e39\u003c/em\u003e, 1-9.\u003c/li\u003e\n\u003cli\u003eXu Weiguo; Xu Feng. Architectural Creation and Thinking of the Parametric Design in China: Interview with Professor Xu Weiguo \u0026amp; Xu Feng of School of Architecture of Tsinghua University. \u003cem\u003eUrbanism and Architecture\u003c/em\u003e\u003cem\u003e. \u003c/em\u003e\u003cstrong\u003e2010\u003c/strong\u003e\u003cstrong\u003e, \u003c/strong\u003e\u003cem\u003e06\u003c/em\u003e, 108-113+3.\u003c/li\u003e\n\u003cli\u003eChi Zhi-wei; Chen Jie; Zhang De-shun. Process in Application of Parametric Design and Its Inspiration to Landscape Design. \u003cem\u003eChinese Landscape Architecture. \u003c/em\u003e\u003cstrong\u003e2012\u003c/strong\u003e, \u003cem\u003e28\u003c/em\u003e, 40-45.\u003c/li\u003e\n\u003cli\u003ePatik Schumacher. Parametric Patterns. \u003cem\u003eArchitectural Design. \u003c/em\u003e\u003cstrong\u003e2009\u003c/strong\u003e, \u003cem\u003e6\u003c/em\u003e, 28-41.\u003c/li\u003e\n\u003cli\u003eLI Xiaojun; Huang Jian; Zou Fu. Rapid Three-Dimension and Spatial Analysis for Village Planning Scheme. \u003cem\u003eJournal of Geomatics\u003c/em\u003e\u003cem\u003e. \u003c/em\u003e\u003cstrong\u003e2021\u003c/strong\u003e, \u003cem\u003e46(S1),\u003c/em\u003e 178-181.\u003c/li\u003e\n\u003cli\u003eLi Hengkai; Li Xiaolong; Li Zivang; Chen Yueving. Three-dimensional modeling method of Hakka ancient village based on component model library-a case study in the BaiLu ancient village. \u003cem\u003eScience of Surveying and Mapping\u003c/em\u003e\u003cem\u003e. \u003c/em\u003e\u003cstrong\u003e2019\u003c/strong\u003e, \u003cem\u003e44\u003c/em\u003e, 182-189.\u003c/li\u003e\n\u003cli\u003eZhang Hui; Liu Chao; Li Yan; Wang Youjie. Research on 3D Building Modeling Technology Based on CityEngine. \u003cem\u003eBulletin of Surveying and Mapping\u003c/em\u003e\u003cem\u003e. \u003c/em\u003e\u003cstrong\u003e2014\u003c/strong\u003e, \u003cem\u003e11\u003c/em\u003e, 108-112.\u003c/li\u003e\n\u003cli\u003eDuarte J P; Rocha J; Ducla-Soares G; et al. \u003cem\u003eAn urban grammar for the Medina of Marrakech\u003c/em\u003e\u003cem\u003e; \u003c/em\u003eSpringer: Berlin, Germany, \u003cstrong\u003e2006\u003c/strong\u003e; pp. 483-502.\u003c/li\u003e\n\u003cli\u003eZhou Ling. Method of 3D Modeling for Digital City Based on Parametric Technology. Master, Zhe Jiang University, Hang Zhou, \u003cstrong\u003e2013.\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003eTong Lei. Parametric Analysis and Reconstruction of Villages\u0026rsquo; Spatial Texture and Its Planning Application Research. Dr, Zhe Jiang University, Hang Zhou, \u003cstrong\u003e2016\u003c/strong\u003e.\u003c/li\u003e\n\u003cli\u003eWu Meihan. Research on Parametric Analysis and Planning Application of Village Space Texture in Qin and Han New Towns. Master, Chang\u0026rsquo;an University, Xi\u0026rsquo;an, \u003cstrong\u003e2022\u003c/strong\u003e.\u003c/li\u003e\n\u003cli\u003eHan Qing; Yin Chao; Deng Yunyuan; Liu Peilin. Towards Classification of Architectural Styles of Chinese Traditional Settlements Using Deep Learning: A Dataset, a New Framework, and Its Interpretability. \u003cem\u003eRemote Sensing\u003c/em\u003e. \u003cstrong\u003e2022\u003c/strong\u003e, \u003cem\u003e14\u003c/em\u003e, 5250-5250.\u003c/li\u003e\n\u003cli\u003eQuan Steven Jige.. Urban-GAN: An artificial intelligence-aided computation system for plural urban design. \u003cem\u003eEnvironment and Planning B: Urban Analytics and City Science\u003c/em\u003e. \u003cstrong\u003e2022\u003c/strong\u003e, \u003cem\u003e49\u003c/em\u003e\u003cem\u003e, \u003c/em\u003e2500-2515.\u003c/li\u003e\n\u003cli\u003eYang Junyan, Zhu Xiao, Sun Haocheng. Research on artificial intelligence urban design method based on the combination of deep learning and characteristic parameters: taking the formation of urban multi-type building community as an example. \u003cem\u003eContemporary Architecture\u003c/em\u003e.\u003cstrong\u003e2022\u003c/strong\u003e, \u003cem\u003e06\u003c/em\u003e, 33-36.\u003c/li\u003e\n\u003cli\u003eKouppanou Anna. Bernard Stiegler\u0026rsquo;s Philosophy of Technology: Invention, Decision, and Education in Times of Digitization. \u003cem\u003eEducational Philosophy and Theory\u003c/em\u003e. \u003cstrong\u003e2015\u003c/strong\u003e\u003cem\u003e,\u003c/em\u003e\u003cem\u003e 47(10),\u003c/em\u003e 1110\u0026ndash;1123.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"traditional Chinese villages, spatial feature extraction, parametric design, digital generative design, village reconstruction, cultural heritage preservation","lastPublishedDoi":"10.21203/rs.3.rs-4072347/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4072347/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn recent years, the rapid development of computer-aided planning and design technology has provided a new perspective for the study of complex problems such as the generation of architectural complex forms. This study focuses on how to apply parameterization technology to analyze and articulate traditional spatial form composition rules, aiming to minimize reliance on subjective human judgment in the protection and renewal design of the historical style of traditional villages. It aims to establish digital generative design tools to address the challenges of accurately inheriting and innovatively utilizing historical and cultural information in traditional settlements. It introduces how to rely on parameterization technology to analyze the spatial form composition rules, parameter extraction rules, and spatial reconstruction rules of traditional villages, facilitating the complete process from spatial features to parameterization rules, and then to the application of computational methods to deduce spatial features. It also includes case studies demonstrating the application of parameterization technology tools for village protection and explores the role of generative design tools in preserving the spatial style of these settlements.\u003c/p\u003e","manuscriptTitle":"Analysis and Reconstruction Method of Spatial Characteristics of Traditional Chinese Villages Based on Parameterization","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-28 17:51:55","doi":"10.21203/rs.3.rs-4072347/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1a29d98d-ce07-4520-9315-7d0aeed35aa5","owner":[],"postedDate":"March 28th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":29905282,"name":"Physical sciences/Engineering/Civil engineering"},{"id":29905283,"name":"Earth and environmental sciences/Environmental social sciences/Sustainability"}],"tags":[],"updatedAt":"2024-04-19T19:14:22+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-28 17:51:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4072347","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4072347","identity":"rs-4072347","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}