Analysis of Greenery Cover Change in Lower Hanthana in Sri Lanka for two decades

Analysis of Greenery Cover Change in Lower Hanthana in Sri Lanka for two decades | 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 Research Article Analysis of Greenery Cover Change in Lower Hanthana in Sri Lanka for two decades Ashvin Wickramasooriya, Shashini Bandara This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6066362/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 The Hanthana mountain range, nestled in Kandy, Sri Lanka, has long been celebrated for its breath-taking hiking trails. However, recent years have seen a concerning decline in vegetation across its lower reaches, triggering environmental degradation. A comprehensive study has been initiated, employing a two-phase methodology to tackle this issue. In the initial phase, advanced unsupervised classification techniques were applied using ArcGIS software on satellite imagery from 2000 to 2022. Moving on to the second phase, "Land-use change metrics" within Microsoft Excel were harnessed to precisely quantify alterations in vegetation cover alongside changes in other crucial land-use categories such as urban expanses, barren terrain, and green cover. These meticulous assessments, conducted regarding percentage shifts and hectares impacted, offer invaluable insights into the magnitude of biodiversity decline, developmental encroachments, soil erosion patterns, air quality deterioration, and overall environmental distress prevalent in the lower Hanthana area. The results reveal significant land use changes between 2000 and 2022, with green cover declining by 57%, built-up areas increasing by 208%, and bare land expanding by 234%. These shifts indicate rapid urbanization and ecological degradation, leading to habitat fragmentation and biodiversity loss. The findings emphasize the need for sustainable land management strategies, including reforestation and green infrastructure, to mitigate environmental impacts and balance development with conservation. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1. Introduction The Hanthana mountain range in Central Sri Lanka is a bastion of biodiversity, captivating locals and travelers with its serene landscapes and diverse ecosystems [ 2 ]. From its aquatic environments to broad-leaved wet forests and Pinus plantations, the range hosts a rich array of arthropod populations intricately linked to its verdant surroundings [ 18 ]. Hanthana is a habitat for various flora and fauna, contributing to biodiversity conservation, promoting sustainable practices, and enhancing environmental awareness. The upper Hanthana area is a bastion of untouched wilderness, preserving its natural heritage in isolation [ 4 ]. The lower Hanthana area is located very close to the Kandy city area, and this positioning ensures frequent interaction with human presence and development. Therefore, challenges such as urbanization and industrial development threaten these natural resources within the lower Hanthana area. Human-related events, such as inappropriate forest management, encroachment of forest land, and overharvesting in the lower Hanthana area, also contribute to biodiversity loss and vegetation degradation [ 5 ],[ 1 ],[ 10 ],[ 15 ]. vegetation loss in that area brings environmental problems such as climate change, urban heat islands, temperature increase, lack of evapotranspiration, loss of shade, and decreased vegetation [ 7 ], [ 16 ]. In Kolkata, urban development has drastically reduced green cover to just 5%, far below the recommended 15% for Indian metros, and Over 5,000 trees were lost in a single year due to construction and unauthorized activities, contributing to a significant increase in carbon emissions [ 14 ], [ 3 ]. similarly, within the Hanthana lower area, during the British colonial period, significant deforestation occurred to make way for plantations of tea, coffee, and rubber [ 12 ]. But In recent years, efforts have been made to restore the degraded lands of Hanthana, such as the "Regreen Hantana" project, led by the University of Peradeniya in collaboration with the Forest Department of Sri Lanka and local communities. Despite these restoration efforts, the lower Hanthana area continues to experience significant human encroachment, leading to changes in land use and vegetation cover. Therefore, this research paper aims to analyze the patterns of vegetation change in this region from 2000 to 2022 and offers valuable insights into sustainable land management and conservation practices within the Hanthana region and on a broader scale. 2. Study Area The Lower Hanthana area (Fig. 1 ) is within the Kandy District, Central Province of Sri Lanka, and lies within the southern limits of the Kandy Municipal Council (KMC). It is part of the Hanthana mountain range, a renowned landscape in Sri Lanka, with its rolling hills and rich biodiversity. Lower Hanthana's terrain is predominantly hilly, with altitudes ranging from 500 m to 700 m above sea level. Lower Hanthana experiences a tropical monsoon climate with an annual rainfall of 2,000 mm to 3,500 mm and the average annual temperature is around 24°C to 26°C, with cooler temperatures in higher elevations [ 9 ]. Historically, Lower Hanthana has been known for its dense green cover, consisting of small patches of secondary forests and shrublands, especially in steeper and less accessible areas, a mix of fruit trees, ornamental plants, and crops on residential lands and Reforestation initiatives, including fast-growing species like eucalyptus and mahogany [ 12 ]. 3. Materials and Methodology 3.1 Materials In this study, Landsat 7 and Landsat 8 satellite images, sourced from the USGS EarthExplorer website [ 6 ], spanning the period from 2000 to 2022, serve as the foundational data for assessing land use and land cover changes. These images provide valuable multispectral data, enabling a detailed analysis of various land cover types and their transformations over time. To validate the accuracy of land cover classifications derived from the Landsat imagery, Google Earth Pro [ 6 ] is employed. Its historical imagery tool allows for an in-depth comparison of significant land cover changes between 2000 and 2022. With its high-resolution imagery and interactive features, Google Earth Pro facilitates verification against real-world observations. The study utilizes ArcGIS and ArcGIS Pro to process and analyze satellite imagery and calculate land use change metrics. These Geographic Information System (GIS) tools are critical for conducting spatial analysis, performing land cover classifications, and generating visualizations of the study area. Additionally, Microsoft Excel organizes data, performs statistical analyses, and creates charts and graphs to communicate findings effectively. By integrating these software tools and platforms, the study adopts a comprehensive approach to assess land use and land cover changes, encompassing data acquisition, processing, analysis, and result visualization. 3.2 Methodology The methodology employed in the study can be delineated into several sequential steps, as illustrated in Fig. 2 . Initially, a meticulous comparison was conducted among various sources, including satellite images, which were downloaded by USGS EarthExplorer [ 6 ], Google Earth Pro images [ 6 ] (2000 & 2022), and maps of the Department of Survey [ 8 ], Sri Lanka, within the study area, which promptly revealed significant changes in land utilization patterns. Subsequently, an exhaustive review of pertinent literature about the Hanthana region ensued, encompassing methodologies and techniques for analyzing land use changes, as well as applications of geoinformatics. A comprehensive compilation of pertinent data and materials from diverse institutes and websites was undertaken. The methodology's core involved data analysis, which utilized a widely recognized image analysis technique, specifically the unsupervised classification within the ArcGIS software framework. The outcomes of this analysis were meticulously reclassified for both the years 2000 and 2022, facilitating a comparative assessment of land use extents over time in the Hanthana lower area. This comparative analysis elucidated the variations in green cover between the specified years. Lastly, the findings were synthesized and presented comprehensively through tables and graphics, enhancing the clarity and accessibility of the results for stakeholders and readers alike. 3.2.1. Data Collection For this research, we collected data by obtaining Landsat satellite images from the USGS EarthExplorer website [ 6 ] for 2000 and 2022. We chose Landsat satellite imagery because of its consistent coverage, multispectral capabilities, and historical archive, which allowed us to analyze land cover and land use dynamics over time. The images were downloaded in digital format with a spatial resolution of 30 meters, ensuring a detailed representation of land surface features. After obtaining the Landsat imagery, a series of preprocessing steps were taken to improve the quality and usability of the data. These steps included radiometric calibration, atmospheric correction, and geometric correction to account for sensor artifacts, atmospheric interference, and geometric distortions. Standardizing the imagery across both periods prepared the data to accurately compare and analyze land use change. Following the preprocessing phase, we used ArcGIS software to conduct unsupervised classification on the Landsat images. Using the reclassify tool, we classified the images into different land cover categories: vegetation, Built-up areas, and bare lands. We trained the classification algorithm with known reference data to ensure accurate delineation of land cover features within the study area. To ensure the accuracy of the classification results, we utilized a combination of remote sensing data, ground truth data, and existing land cover maps. Google Earth Pro software was employed to visually interpret and compare the classified land cover maps with high-resolution satellite imagery. This process helped us identify any discrepancies and improve the classification accuracy. Subsequently, the resulting land cover classifications were combined using ArcGIS software to generate composite datasets for both periods. These datasets were the basis for calculating land use change metrics for each land cover category, such as area change, percentage change, and spatial distribution indices. This data collection process involved a systematic approach to acquiring, preprocessing, and analyzing Landsat satellite imagery to assess land use change dynamics over time. The research achieved comprehensive insights into land use change dynamics by integrating remote sensing data and GIS analysis techniques. 3.2.2. Data Analysis The data analysis process commenced by utilizing ArcGIS software to delineate the boundary of the Hanthana Lower area. Initially, the shapefile of the study area boundary was imported, and spatial analysis tools were employed to precisely define the region's extent. This boundary-setting phase constrained subsequent analyses and interpretations to the specified geographical area, ensuring precision and representativeness by considering relevant geographic features, administrative boundaries, and topographic characteristics. Once the boundary of the Hanthana Lower area was established, Landsat satellite images from 2000 and 2022 were amalgamated using the Composite Bands tool within ArcGIS. This fusion produced yearly single, multispectral composite images, enhancing visual interpretation and land cover analysis. The extract by Mask tool was then utilized to trim the composited Landsat images to the boundary shapefile, facilitating focused analysis by isolating image pixels within the delineated boundary. Efficient utilization of the Extract by Mask tool enabled the subsetting of satellite images to match the spatial extent of the Hanthana Lower region, enabling precise analysis of land cover and land use dynamics over specific periods. Three land use classes, green cover, built-up areas, and bare land, were identified to examine changes in green cover from 2000 to 2022, focusing on understanding dynamics relative to other land use types. Unsupervised classification was performed on the Landsat satellite images for 2000 and 2022 using ArcGIS software. This involved categorizing pixels into three distinct land cover classes within the study area: Vegetation, built-up, and bare land areas. The next step involved reclassifying the classified satellite images using the Reclassify tool within ArcGIS to combine the two classified raster images of 2000 and 2022 to analyze land use change dynamics over time. Subsequently, a new raster dataset was generated using the "combine" tool to incorporate information on land cover categories in the 2000 and 2022 images. In the final analysis stage, "land use change metrics" were calculated using Microsoft Excel to quantify changes in various land cover categories for the years 2000 and 2022 in hectares. Graphical representations were created in Microsoft Excel to illustrate changes in these areas separately for each year, providing valuable insights into environmental change and informing land management strategies and conservation efforts in the study area. 4. Results 4.1 Land use dynamics of Lower Hanthana Area from 2000 to 2022 based on the classified maps The analysis of land use changes in the Lower Hanthana area, illustrated by two maps generated through unsupervised classification using ArcGIS software, reveals significant transformations in the landscape over the past two decades (Figs. 3 and 4 ). These maps, depicting land cover in 2000 and 2022, provide compelling visual evidence of substantial alterations in vegetation cover, urbanization, and bare land distribution. The land use map 2000 showcases the Lower Hanthana area as predominantly covered in lush vegetation, reflecting its status as a green corridor rich in biodiversity. The landscape was dominated by vast forests, woodlands, and other vegetation, highlighting the area's natural ecological wealth. Urban areas were relatively sparse, limited to established settlements and villages with minimal encroachment into the surrounding greenery. Bare land, representing regions devoid of vegetation, was minimal, indicating a landscape largely undisturbed by significant human intervention or land development activities. In contrast, the land use map of 2022 presents a markedly different scenario, characterized by significant shifts in land cover patterns. The once-dominant vegetation cover has experienced substantial decline, which is evident in the fragmentation and reduction of forested areas. Urbanization has emerged as a dominant feature, with the proliferation of built-up areas, residential zones, and infrastructure networks sprawling across the landscape. This expansion of urban settlements underscores the encroachment of human activities into previously undisturbed natural habitats, leading to habitat fragmentation and biodiversity loss. Additionally, the prevalence of bare land has increased significantly, indicating the conversion of vegetated areas into non-vegetated land cover types, likely attributed to agricultural expansion, deforestation, and land degradation processes. The combined raster map, derived from the reclassification of the 2000 and 2022 Classified images and generated using the combined tool in ArcGIS, offers a comprehensive overview of the land use change dynamics observed in the Lower Hanthana area over the past two decades. The map delineates areas of both loss and gain in vegetative biomass, indicating changes in forest cover, woodland distribution, and vegetated landscapes over the study period (Fig. 5 ). Urbanized areas are prominently visible, illustrating the expansion of built-up environments, infrastructure networks, and human settlement footprints across the landscape. Bare land patches indicate regions devoid of vegetation cover, reflecting land use changes driven by agricultural expansion, deforestation, or land degradation processes. Transition zones between different land cover classes are apparent, highlighting areas where land use changes are particularly dynamic or pronounced. The insights obtained from the combined raster map provide valuable information for land managers, policymakers, and researchers. These insights help us understand the spatial patterns of land use change and their implications for ecosystem health, biodiversity conservation, and sustainable development within the study area. 4.2 Land use dynamics of Lower Hanthana Area from 2000 to 2022 based on the attribute values A comparison of attribute values in classified images revealed significant changes in land use patterns between 2000 and 2022. The study analyzed pixel changes within the area using attribute table values from classified satellite images. Based on the land use classification for the year 2000, a substantial change was observed in the green cover, where 4,622 pixels (415.98 hectares) transitioned into built-up areas by 2022. In contrast, a significant portion of the vegetative cover recorded in 2000 has remained intact, with 4,714 pixels (424.25 hectares) retaining their green state up to 2022. However, a notable amount of vegetation was converted into barren land during this period, accounting for 2,155 pixels (193.97 hectares), potentially indicating a decline in the region's environmental condition. On the other hand, the urbanized areas of the region have experienced a slight increase in greenery, with an additional 93 pixels (8.28 hectares) of green coverage recorded between 2000 and 2022. This suggests a modest improvement in green coverage within these zones. Nonetheless, the expansion of built-up areas has been significant; however, 2,133 pixels (192.07 hectares) remained unaffected even in 2022 and continue to exist in their original state. Bare land areas in 2000 also changed, with notable conversions into built-up areas and green cover. Table 1. Land use types in the Lower Hanthana area either remained the same or shifted to other land use types between 2000 and 2022, measured in hectares 2000 (Hectares) 2022 (Hectares) Green Cover Built-up area Bare Land Green Cover 424.25 415.98 193.97 Built up area 8.28 192.07 8.37 Bare Land 8.37 34.11 25.74 Total 440.90 642.16 228.08 The study's results were further analyzed by converting pixel counts to area measurements, considering the Landsat satellite images' spatial resolution. The analysis revealed substantial changes in green cover from 2000 to 2022, with 415.98 hectares transitioning into built-up areas, highlighting the rapid pace of urbanization. However, some green spaces were preserved, with 424.25 hectares maintaining their vegetative state. Conversely, converting green cover to barren land, totaling 193.95 hectares, raises concerns about the region's ecological degradation and habitat loss (Table 1 ). These findings offer valuable insights into land use change patterns in the Hanthana Lower Area and comparable landscapes. They underscore the importance of implementing sustainable land management practices to balance urban development with environmental conservation efforts. 5. Discussion The analysis of land use change metrics, derived from attribute values of two classified satellite images spanning 22 years, reveals the shifting landscape dynamics in the study area. The comparison between land use types in 2000 and 2022 revealed significant transformations in vegetation, built-up areas, and bare lands. Accordingly, the green cover area experienced a decrease of 57% over the two decades, indicating significant loss within the vegetative landscape. In contrast, built-up areas and bare lands witnessed remarkable increases of 208% and 234%, respectively, highlighting the rapid urbanization and expansion of non-vegetated areas within the region (Table 2 and Fig. 7 ). Table 2 Land use Change Metrics Land use type Area (Hectares) Change Percentage (%) Area Description Percentage of each land use type based on its area (%) 2000 2022 2000 2022 Green cover 1034.20 440.90 -57.37 Loss 78.88 33.62 Built-up Area 208.71 642.16 207.89 Gain 15.92 48.98 Bare land 68.22 228.08 24.36 Gain 5.20 17.40 Additionally, examining land use percentages for the total area in both years highlights the significance of these changes. These changes are substantial and require our attention to ensure the sustainability of our environment. The land use change metrics show that 2000 green cover dominated the landscape, accounting for 79% of the total area, while built-up areas and bare lands constituted 16% and 5%, respectively. However, by 2022, there was a notable shift in land use composition, with built-up areas comprising the largest portion at 49%, followed by green cover at 34% and bare lands at 17% (Fig. 8 ). These findings underscore the urgent need for sustainable land management strategies to mitigate the adverse impacts of urbanization on green spaces and ecological systems in the study area and similar landscapes. The findings of this study highlight the extent and direction of vegetation cover change, urbanization, and bare land expansion between different land cover classes. Over the two decades, green cover in the Lower Hanthana area decreased by 57%, indicating rapid ecological degradation and habitat fragmentation. Concurrently, built-up areas expanded by over 208%, reflecting urbanization driven by population growth and economic activities. The increase in bare land, by 234%, further emphasizes the region's vulnerability to soil erosion and loss of vegetation. These dynamics underscore the critical need for sustainable land management practices to mitigate these adverse impacts. For instance, reforestation initiatives and preserving remaining green spaces could enhance ecological resilience and combat the adverse effects of urban sprawl. Integrating green infrastructure, such as urban parks and corridors, into future development plans could help balance human needs with environmental conservation. The results also demonstrate the importance of monitoring land use changes through GIS and remote sensing tools, as these technologies provide actionable insights for policymakers and stakeholders. By adopting these measures, the Lower Hanthana area can serve as a model for sustainable development, ensuring ecological integrity and improving the quality of life for future generations. 6. Conclusion The findings of this study highlight the extent and direction of vegetation cover change, urbanization, and bare land patches between different land cover classes. The transformation of Hanthana's greenery from 2000 to 2022 reflects a complex interplay of environmental, social, and economic factors. Over this period, there has been a noticeable shift in the landscape, characterized by positive and negative changes. The greenery area has increased by about 16.65 hectares from 2000 to 2022 because awareness of environmental conservation has inspired initiatives to preserve and restore Hanthana's natural beauty. Reforestation and sustainable land management practices have helped revive certain areas, promote biodiversity, and strengthen ecosystem resilience. However, rapid urbanization and unchecked development have exerted pressure on Hanthana's green spaces. It was also observed that deforestation, driven by agricultural expansion, infrastructure projects, and illegal logging, has led to the loss of vital habitats and ecological degradation. As a result of these anthropogenic activities, the total greenery area of Hanthana has decreased by approximately 415.98 hectares between 2000 and 2022. The evolution of Hanthana's greenery over the past two decades highlights the urgent need for comprehensive conservation strategies that balance development aspirations with environmental stewardship. Understanding these dynamics is essential for assessing the impacts of land use changes on soil fertility, water quality, and ecosystem resilience in the study area, promoting sustainable land use practices, and preserving ecological integrity. Declarations Author Contribution Shashini Bandara: Data Curation, Conceptualization Formal Analysis, Methodology, Software, Original draft Writing; Ashvin Wickramasooriya: Supervisor, Corresponding Author, Conceptualization, Methodology, Software, Investigation, Writing - Review & Editing. Funding Decleration There is no funding sources for this research. References Aguilar, R. et al. 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A Preliminary Study on the Relationship between Arthropod Diversity and Vegetation Diversity in Four Contrasting Ecosystems in Hanthana Mountain Range of Sri Lanka, during the Post-Monsoon Dry Season. Scientifica. https://doi.org/10.1155/2023/7608236. (accessed on 20 July 2024). 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-6066362","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":423110819,"identity":"d8d23d7a-efb1-44b3-9084-718f7aeacea3","order_by":0,"name":"Ashvin 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2","display":"","copyAsset":false,"role":"figure","size":22890,"visible":true,"origin":"","legend":"\u003cp\u003eThis study has a few main steps, including data collection, data analysis using ArcGIS software, and verification of land use changes in 2022 compared to 2000.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6066362/v1/4dc2906a53e7059c7825eb76.jpg"},{"id":77568526,"identity":"a9e740da-40b1-423d-99f9-d48b6a571d1e","added_by":"auto","created_at":"2025-03-03 07:57:39","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":66144,"visible":true,"origin":"","legend":"\u003cp\u003eLand use classification map of Lower Hanthana area in 2000.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6066362/v1/3cf254edb987750cd8d2101e.jpg"},{"id":77566981,"identity":"691d41d1-f429-4e66-ac50-909016d0eafc","added_by":"auto","created_at":"2025-03-03 07:41:39","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":84870,"visible":true,"origin":"","legend":"\u003cp\u003eLand use classification map of Lower Hanthana area in 2022.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6066362/v1/79c9bde090aac1ddd9e33997.jpg"},{"id":77567199,"identity":"8c217bd2-07ea-4951-b982-efacfc6e64dd","added_by":"auto","created_at":"2025-03-03 07:49:39","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":101078,"visible":true,"origin":"","legend":"\u003cp\u003eThe transformation of land use types in the Lower Hanthana area from 2000 to 2022.\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6066362/v1/fffa0b20cefab5a0f73bb9b8.jpg"},{"id":77566986,"identity":"b89ae5ee-5f2c-47f4-837c-3fec84bb7f9e","added_by":"auto","created_at":"2025-03-03 07:41:39","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":33151,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of area extent of Green cover, Built up area, and Bare land in 2000 and 2022.\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6066362/v1/8ad2b5162ba42220b82b2134.jpg"},{"id":77567201,"identity":"6dfe94fc-8d48-4a96-9042-5b3112c2fc20","added_by":"auto","created_at":"2025-03-03 07:49:39","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":19247,"visible":true,"origin":"","legend":"\u003cp\u003eLand use change in the study area as a percentage from 2000 to 2022.\u003c/p\u003e","description":"","filename":"7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6066362/v1/ea9aeb53526e2cd45408e298.jpg"},{"id":77570510,"identity":"68bbe4de-1120-4dbf-8bdd-118be711fe5e","added_by":"auto","created_at":"2025-03-03 08:13:39","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":33774,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of Land use change as a percentage compared to the total study area in 2000 (a) and 2022 (b).\u003c/p\u003e","description":"","filename":"8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6066362/v1/76ae9ee40cbae3159997d7f8.jpg"},{"id":81146996,"identity":"eb83b41b-6aa9-4254-8275-bc5b25e70174","added_by":"auto","created_at":"2025-04-22 18:23:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1021678,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6066362/v1/3fa51f3e-5f33-45c2-b30a-24a38dfca31e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eAnalysis of Greenery Cover Change in Lower Hanthana in Sri Lanka for two decades\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe Hanthana mountain range in Central Sri Lanka is a bastion of biodiversity, captivating locals and travelers with its serene landscapes and diverse ecosystems [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. From its aquatic environments to broad-leaved wet forests and Pinus plantations, the range hosts a rich array of arthropod populations intricately linked to its verdant surroundings [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Hanthana is a habitat for various flora and fauna, contributing to biodiversity conservation, promoting sustainable practices, and enhancing environmental awareness. The upper Hanthana area is a bastion of untouched wilderness, preserving its natural heritage in isolation [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The lower Hanthana area is located very close to the Kandy city area, and this positioning ensures frequent interaction with human presence and development. Therefore, challenges such as urbanization and industrial development threaten these natural resources within the lower Hanthana area.\u003c/p\u003e \u003cp\u003eHuman-related events, such as inappropriate forest management, encroachment of forest land, and overharvesting in the lower Hanthana area, also contribute to biodiversity loss and vegetation degradation [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e],[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e],[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e],[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. vegetation loss in that area brings environmental problems such as climate change, urban heat islands, temperature increase, lack of evapotranspiration, loss of shade, and decreased vegetation [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In Kolkata, urban development has drastically reduced green cover to just 5%, far below the recommended 15% for Indian metros, and Over 5,000 trees were lost in a single year due to construction and unauthorized activities, contributing to a significant increase in carbon emissions [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. similarly, within the Hanthana lower area, during the British colonial period, significant deforestation occurred to make way for plantations of tea, coffee, and rubber [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBut In recent years, efforts have been made to restore the degraded lands of Hanthana, such as the \"Regreen Hantana\" project, led by the University of Peradeniya in collaboration with the Forest Department of Sri Lanka and local communities. Despite these restoration efforts, the lower Hanthana area continues to experience significant human encroachment, leading to changes in land use and vegetation cover. Therefore, this research paper aims to analyze the patterns of vegetation change in this region from 2000 to 2022 and offers valuable insights into sustainable land management and conservation practices within the Hanthana region and on a broader scale.\u003c/p\u003e"},{"header":"2. Study Area","content":"\u003cp\u003eThe Lower Hanthana area (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) is within the Kandy District, Central Province of Sri Lanka, and lies within the southern limits of the Kandy Municipal Council (KMC). It is part of the Hanthana mountain range, a renowned landscape in Sri Lanka, with its rolling hills and rich biodiversity. Lower Hanthana's terrain is predominantly hilly, with altitudes ranging from 500 m to 700 m above sea level. Lower Hanthana experiences a tropical monsoon climate with an annual rainfall of 2,000 mm to 3,500 mm and the average annual temperature is around 24\u0026deg;C to 26\u0026deg;C, with cooler temperatures in higher elevations [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Historically, Lower Hanthana has been known for its dense green cover, consisting of small patches of secondary forests and shrublands, especially in steeper and less accessible areas, a mix of fruit trees, ornamental plants, and crops on residential lands and Reforestation initiatives, including fast-growing species like eucalyptus and mahogany [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e "},{"header":"3. Materials and Methodology","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Materials\u003c/h2\u003e \u003cp\u003eIn this study, Landsat 7 and Landsat 8 satellite images, sourced from the USGS EarthExplorer website [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], spanning the period from 2000 to 2022, serve as the foundational data for assessing land use and land cover changes. These images provide valuable multispectral data, enabling a detailed analysis of various land cover types and their transformations over time. To validate the accuracy of land cover classifications derived from the Landsat imagery, Google Earth Pro [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] is employed. Its historical imagery tool allows for an in-depth comparison of significant land cover changes between 2000 and 2022. With its high-resolution imagery and interactive features, Google Earth Pro facilitates verification against real-world observations.\u003c/p\u003e \u003cp\u003eThe study utilizes ArcGIS and ArcGIS Pro to process and analyze satellite imagery and calculate land use change metrics. These Geographic Information System (GIS) tools are critical for conducting spatial analysis, performing land cover classifications, and generating visualizations of the study area. Additionally, Microsoft Excel organizes data, performs statistical analyses, and creates charts and graphs to communicate findings effectively. By integrating these software tools and platforms, the study adopts a comprehensive approach to assess land use and land cover changes, encompassing data acquisition, processing, analysis, and result visualization.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Methodology\u003c/h2\u003e \u003cp\u003eThe methodology employed in the study can be delineated into several sequential steps, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Initially, a meticulous comparison was conducted among various sources, including satellite images, which were downloaded by USGS EarthExplorer [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], Google Earth Pro images [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] (2000 \u0026amp; 2022), and maps of the Department of Survey [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], Sri Lanka, within the study area, which promptly revealed significant changes in land utilization patterns. Subsequently, an exhaustive review of pertinent literature about the Hanthana region ensued, encompassing methodologies and techniques for analyzing land use changes, as well as applications of geoinformatics. A comprehensive compilation of pertinent data and materials from diverse institutes and websites was undertaken.\u003c/p\u003e \u003cp\u003eThe methodology's core involved data analysis, which utilized a widely recognized image analysis technique, specifically the unsupervised classification within the ArcGIS software framework. The outcomes of this analysis were meticulously reclassified for both the years 2000 and 2022, facilitating a comparative assessment of land use extents over time in the Hanthana lower area. This comparative analysis elucidated the variations in green cover between the specified years. Lastly, the findings were synthesized and presented comprehensively through tables and graphics, enhancing the clarity and accessibility of the results for stakeholders and readers alike.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e3.2.1. Data Collection\u003c/h2\u003e \u003cp\u003eFor this research, we collected data by obtaining Landsat satellite images from the USGS EarthExplorer website [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] for 2000 and 2022. We chose Landsat satellite imagery because of its consistent coverage, multispectral capabilities, and historical archive, which allowed us to analyze land cover and land use dynamics over time. The images were downloaded in digital format with a spatial resolution of 30 meters, ensuring a detailed representation of land surface features. After obtaining the Landsat imagery, a series of preprocessing steps were taken to improve the quality and usability of the data. These steps included radiometric calibration, atmospheric correction, and geometric correction to account for sensor artifacts, atmospheric interference, and geometric distortions. Standardizing the imagery across both periods prepared the data to accurately compare and analyze land use change.\u003c/p\u003e \u003cp\u003eFollowing the preprocessing phase, we used ArcGIS software to conduct unsupervised classification on the Landsat images. Using the reclassify tool, we classified the images into different land cover categories: vegetation, Built-up areas, and bare lands. We trained the classification algorithm with known reference data to ensure accurate delineation of land cover features within the study area. To ensure the accuracy of the classification results, we utilized a combination of remote sensing data, ground truth data, and existing land cover maps. Google Earth Pro software was employed to visually interpret and compare the classified land cover maps with high-resolution satellite imagery. This process helped us identify any discrepancies and improve the classification accuracy.\u003c/p\u003e \u003cp\u003eSubsequently, the resulting land cover classifications were combined using ArcGIS software to generate composite datasets for both periods. These datasets were the basis for calculating land use change metrics for each land cover category, such as area change, percentage change, and spatial distribution indices. This data collection process involved a systematic approach to acquiring, preprocessing, and analyzing Landsat satellite imagery to assess land use change dynamics over time. The research achieved comprehensive insights into land use change dynamics by integrating remote sensing data and GIS analysis techniques.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e3.2.2. Data Analysis\u003c/h2\u003e \u003cp\u003eThe data analysis process commenced by utilizing ArcGIS software to delineate the boundary of the Hanthana Lower area. Initially, the shapefile of the study area boundary was imported, and spatial analysis tools were employed to precisely define the region's extent. This boundary-setting phase constrained subsequent analyses and interpretations to the specified geographical area, ensuring precision and representativeness by considering relevant geographic features, administrative boundaries, and topographic characteristics. Once the boundary of the Hanthana Lower area was established, Landsat satellite images from 2000 and 2022 were amalgamated using the Composite Bands tool within ArcGIS. This fusion produced yearly single, multispectral composite images, enhancing visual interpretation and land cover analysis. The extract by Mask tool was then utilized to trim the composited Landsat images to the boundary shapefile, facilitating focused analysis by isolating image pixels within the delineated boundary.\u003c/p\u003e \u003cp\u003eEfficient utilization of the Extract by Mask tool enabled the subsetting of satellite images to match the spatial extent of the Hanthana Lower region, enabling precise analysis of land cover and land use dynamics over specific periods. Three land use classes, green cover, built-up areas, and bare land, were identified to examine changes in green cover from 2000 to 2022, focusing on understanding dynamics relative to other land use types.\u003c/p\u003e \u003cp\u003eUnsupervised classification was performed on the Landsat satellite images for 2000 and 2022 using ArcGIS software. This involved categorizing pixels into three distinct land cover classes within the study area: Vegetation, built-up, and bare land areas. The next step involved reclassifying the classified satellite images using the Reclassify tool within ArcGIS to combine the two classified raster images of 2000 and 2022 to analyze land use change dynamics over time. Subsequently, a new raster dataset was generated using the \"combine\" tool to incorporate information on land cover categories in the 2000 and 2022 images. In the final analysis stage, \"land use change metrics\" were calculated using Microsoft Excel to quantify changes in various land cover categories for the years 2000 and 2022 in hectares. Graphical representations were created in Microsoft Excel to illustrate changes in these areas separately for each year, providing valuable insights into environmental change and informing land management strategies and conservation efforts in the study area.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"4. Results","content":"\u003cp\u003e \u003cb\u003e4.1 Land use dynamics of Lower Hanthana Area from 2000 to 2022 based on the classified maps\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe analysis of land use changes in the Lower Hanthana area, illustrated by two maps generated through unsupervised classification using ArcGIS software, reveals significant transformations in the landscape over the past two decades (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). These maps, depicting land cover in 2000 and 2022, provide compelling visual evidence of substantial alterations in vegetation cover, urbanization, and bare land distribution. The land use map 2000 showcases the Lower Hanthana area as predominantly covered in lush vegetation, reflecting its status as a green corridor rich in biodiversity. The landscape was dominated by vast forests, woodlands, and other vegetation, highlighting the area's natural ecological wealth. Urban areas were relatively sparse, limited to established settlements and villages with minimal encroachment into the surrounding greenery. Bare land, representing regions devoid of vegetation, was minimal, indicating a landscape largely undisturbed by significant human intervention or land development activities.\u003c/p\u003e \u003cp\u003eIn contrast, the land use map of 2022 presents a markedly different scenario, characterized by significant shifts in land cover patterns. The once-dominant vegetation cover has experienced substantial decline, which is evident in the fragmentation and reduction of forested areas. Urbanization has emerged as a dominant feature, with the proliferation of built-up areas, residential zones, and infrastructure networks sprawling across the landscape. This expansion of urban settlements underscores the encroachment of human activities into previously undisturbed natural habitats, leading to habitat fragmentation and biodiversity loss.\u003c/p\u003e \u003cp\u003eAdditionally, the prevalence of bare land has increased significantly, indicating the conversion of vegetated areas into non-vegetated land cover types, likely attributed to agricultural expansion, deforestation, and land degradation processes. The combined raster map, derived from the reclassification of the 2000 and 2022 Classified images and generated using the combined tool in ArcGIS, offers a comprehensive overview of the land use change dynamics observed in the Lower Hanthana area over the past two decades. The map delineates areas of both loss and gain in vegetative biomass, indicating changes in forest cover, woodland distribution, and vegetated landscapes over the study period (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eUrbanized areas are prominently visible, illustrating the expansion of built-up environments, infrastructure networks, and human settlement footprints across the landscape. Bare land patches indicate regions devoid of vegetation cover, reflecting land use changes driven by agricultural expansion, deforestation, or land degradation processes. Transition zones between different land cover classes are apparent, highlighting areas where land use changes are particularly dynamic or pronounced. The insights obtained from the combined raster map provide valuable information for land managers, policymakers, and researchers. These insights help us understand the spatial patterns of land use change and their implications for ecosystem health, biodiversity conservation, and sustainable development within the study area.\u003c/p\u003e \u003cp\u003e \u003cb\u003e4.2 Land use dynamics of Lower Hanthana Area from 2000 to 2022 based on the attribute values\u003c/b\u003e \u003c/p\u003e\u003cp\u003eA comparison of attribute values in classified images revealed significant changes in land use patterns between 2000 and 2022. The study analyzed pixel changes within the area using attribute table values from classified satellite images. Based on the land use classification for the year 2000, a substantial change was observed in the green cover, where 4,622 pixels (415.98 hectares) transitioned into built-up areas by 2022. In contrast, a significant portion of the vegetative cover recorded in 2000 has remained intact, with 4,714 pixels (424.25 hectares) retaining their green state up to 2022. However, a notable amount of vegetation was converted into barren land during this period, accounting for 2,155 pixels (193.97 hectares), potentially indicating a decline in the region's environmental condition.\u003c/p\u003e \u003cp\u003eOn the other hand, the urbanized areas of the region have experienced a slight increase in greenery, with an additional 93 pixels (8.28 hectares) of green coverage recorded between 2000 and 2022. This suggests a modest improvement in green coverage within these zones. Nonetheless, the expansion of built-up areas has been significant; however, 2,133 pixels (192.07 hectares) remained unaffected even in 2022 and continue to exist in their original state. Bare land areas in 2000 also changed, with notable conversions into built-up areas and green cover.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e\u0026nbsp; \u0026nbsp;Land use types in the Lower Hanthana area either remained the same or shifted to other land use types between 2000 and 2022, measured in hectares\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"384\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" colspan=\"2\" valign=\"top\" style=\"width: 12.4477%;\"\u003e\n \u003cp\u003e2000\u003c/p\u003e\n \u003cp\u003e(Hectares)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 28.2208%;\"\u003e\n \u003cp\u003e2022 (Hectares)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"\" valign=\"top\" style=\"width: 12.1051%;\"\u003e\n \u003cp\u003eGreen Cover\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 13.4754%;\"\u003e\n \u003cp\u003eBuilt-up area\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" colspan=\"2\" style=\"width: 0.0091%;\"\u003e\n \u003cp\u003eBare Land\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 13.247%;\"\u003e\n \u003cp\u003eGreen Cover\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6.2809%;\"\u003e\n \u003cp\u003e424.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 14.2748%;\"\u003e\n \u003cp\u003e415.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 9.1359%;\"\u003e\n \u003cp\u003e193.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 13.247%;\"\u003e\n \u003cp\u003eBuilt up area\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6.2809%;\"\u003e\n \u003cp\u003e8.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 14.2748%;\"\u003e\n \u003cp\u003e192.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 9.1359%;\"\u003e\n \u003cp\u003e8.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 13.247%;\"\u003e\n \u003cp\u003eBare Land\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6.2809%;\"\u003e\n \u003cp\u003e8.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 14.2748%;\"\u003e\n \u003cp\u003e34.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 9.1359%;\"\u003e\n \u003cp\u003e25.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 13.247%;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6.2809%;\"\u003e\n \u003cp\u003e440.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 14.2748%;\"\u003e\n \u003cp\u003e642.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 9.1359%;\"\u003e\n \u003cp\u003e228.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\u003cp\u003eThe study's results were further analyzed by converting pixel counts to area measurements, considering the Landsat satellite images' spatial resolution.\u003c/p\u003e \u003cp\u003eThe analysis revealed substantial changes in green cover from 2000 to 2022, with 415.98 hectares transitioning into built-up areas, highlighting the rapid pace of urbanization. However, some green spaces were preserved, with 424.25 hectares maintaining their vegetative state. Conversely, converting green cover to barren land, totaling 193.95 hectares, raises concerns about the region's ecological degradation and habitat loss (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). These findings offer valuable insights into land use change patterns in the Hanthana Lower Area and comparable landscapes. They underscore the importance of implementing sustainable land management practices to balance urban development with environmental conservation efforts.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"5. Discussion","content":"\u003cp\u003eThe analysis of land use change metrics, derived from attribute values of two classified satellite images spanning 22 years, reveals the shifting landscape dynamics in the study area. The comparison between land use types in 2000 and 2022 revealed significant transformations in vegetation, built-up areas, and bare lands. Accordingly, the green cover area experienced a decrease of 57% over the two decades, indicating significant loss within the vegetative landscape. In contrast, built-up areas and bare lands witnessed remarkable increases of 208% and 234%, respectively, highlighting the rapid urbanization and expansion of non-vegetated areas within the region (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLand use Change Metrics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLand use type\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eArea (Hectares)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eChange Percentage (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eArea Description\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003ePercentage of each land use type based on its area (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2000\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2000\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGreen cover\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1034.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e440.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-57.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLoss\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e78.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e33.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBuilt-up Area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e208.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e642.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e207.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e48.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBare land\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e228.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAdditionally, examining land use percentages for the total area in both years highlights the significance of these changes. These changes are substantial and require our attention to ensure the sustainability of our environment. The land use change metrics show that 2000 green cover dominated the landscape, accounting for 79% of the total area, while built-up areas and bare lands constituted 16% and 5%, respectively. However, by 2022, there was a notable shift in land use composition, with built-up areas comprising the largest portion at 49%, followed by green cover at 34% and bare lands at 17% (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). These findings underscore the urgent need for sustainable land management strategies to mitigate the adverse impacts of urbanization on green spaces and ecological systems in the study area and similar landscapes.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe findings of this study highlight the extent and direction of vegetation cover change, urbanization, and bare land expansion between different land cover classes. Over the two decades, green cover in the Lower Hanthana area decreased by 57%, indicating rapid ecological degradation and habitat fragmentation. Concurrently, built-up areas expanded by over 208%, reflecting urbanization driven by population growth and economic activities. The increase in bare land, by 234%, further emphasizes the region's vulnerability to soil erosion and loss of vegetation. These dynamics underscore the critical need for sustainable land management practices to mitigate these adverse impacts. For instance, reforestation initiatives and preserving remaining green spaces could enhance ecological resilience and combat the adverse effects of urban sprawl. Integrating green infrastructure, such as urban parks and corridors, into future development plans could help balance human needs with environmental conservation. The results also demonstrate the importance of monitoring land use changes through GIS and remote sensing tools, as these technologies provide actionable insights for policymakers and stakeholders. By adopting these measures, the Lower Hanthana area can serve as a model for sustainable development, ensuring ecological integrity and improving the quality of life for future generations.\u003c/p\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eThe findings of this study highlight the extent and direction of vegetation cover change, urbanization, and bare land patches between different land cover classes. The transformation of Hanthana's greenery from 2000 to 2022 reflects a complex interplay of environmental, social, and economic factors. Over this period, there has been a noticeable shift in the landscape, characterized by positive and negative changes. The greenery area has increased by about 16.65 hectares from 2000 to 2022 because awareness of environmental conservation has inspired initiatives to preserve and restore Hanthana's natural beauty. Reforestation and sustainable land management practices have helped revive certain areas, promote biodiversity, and strengthen ecosystem resilience. However, rapid urbanization and unchecked development have exerted pressure on Hanthana's green spaces. It was also observed that deforestation, driven by agricultural expansion, infrastructure projects, and illegal logging, has led to the loss of vital habitats and ecological degradation. As a result of these anthropogenic activities, the total greenery area of Hanthana has decreased by approximately 415.98 hectares between 2000 and 2022. The evolution of Hanthana's greenery over the past two decades highlights the urgent need for comprehensive conservation strategies that balance development aspirations with environmental stewardship. Understanding these dynamics is essential for assessing the impacts of land use changes on soil fertility, water quality, and ecosystem resilience in the study area, promoting sustainable land use practices, and preserving ecological integrity.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eShashini Bandara: Data Curation, Conceptualization Formal Analysis, Methodology, Software, Original draft Writing; Ashvin Wickramasooriya: Supervisor, Corresponding Author, Conceptualization, Methodology, Software, Investigation, Writing - Review \u0026amp; Editing.\u003c/p\u003e\u003cp\u003eFunding Decleration\u003c/p\u003e\u003cp\u003eThere is no funding sources for this research.\u003c/p\u003e "},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAguilar, R. \u003cem\u003eet al.\u003c/em\u003e (\u003cstrong\u003e2018\u003c/strong\u003e) \u0026lsquo;Unprecedented plant species loss after a decade in fragmented subtropical chaco serrano forests\u0026rsquo;, \u003cem\u003ePLoS ONE\u003c/em\u003e, 13(11), pp. 1\u0026ndash;15. 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Scientifica. https://doi.org/10.1155/2023/7608236. (accessed on 20 July 2024).\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":"","lastPublishedDoi":"10.21203/rs.3.rs-6066362/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6066362/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe Hanthana mountain range, nestled in Kandy, Sri Lanka, has long been celebrated for its breath-taking hiking trails. However, recent years have seen a concerning decline in vegetation across its lower reaches, triggering environmental degradation. A comprehensive study has been initiated, employing a two-phase methodology to tackle this issue. In the initial phase, advanced unsupervised classification techniques were applied using ArcGIS software on satellite imagery from 2000 to 2022. Moving on to the second phase, \"Land-use change metrics\" within Microsoft Excel were harnessed to precisely quantify alterations in vegetation cover alongside changes in other crucial land-use categories such as urban expanses, barren terrain, and green cover. These meticulous assessments, conducted regarding percentage shifts and hectares impacted, offer invaluable insights into the magnitude of biodiversity decline, developmental encroachments, soil erosion patterns, air quality deterioration, and overall environmental distress prevalent in the lower Hanthana area. The results reveal significant land use changes between 2000 and 2022, with green cover declining by 57%, built-up areas increasing by 208%, and bare land expanding by 234%. These shifts indicate rapid urbanization and ecological degradation, leading to habitat fragmentation and biodiversity loss. The findings emphasize the need for sustainable land management strategies, including reforestation and green infrastructure, to mitigate environmental impacts and balance development with conservation.\u003c/p\u003e","manuscriptTitle":"Analysis of Greenery Cover Change in Lower Hanthana in Sri Lanka for two decades","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-03 07:41:34","doi":"10.21203/rs.3.rs-6066362/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":"d18818ce-9bc0-49c9-ae97-2eff09805804","owner":[],"postedDate":"March 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-04-22T18:23:07+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-03 07:41:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6066362","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6066362","identity":"rs-6066362","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}