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Climate change poses significant social, economic, and environmental challenges for farmers whose livelihoods depend on natural resources. Analyzing Land Use Land Cover (LULC) changes has proven to be an essential method for monitoring transformations across various temporal and spatial scales. The Normalized Difference Vegetation Index (NDVI) serves as a valuable remote sensing tool, effectively capturing vegetation patterns across diverse ecological regions and aiding in the study of phonological cycles. This research utilized remote sensing and Geographic Information System (GIS) techniques to analyze LULC changes over 34 years in Piyali sub-basin. Additionally, some questionnaires were conducted with local farmers to explore the relationship between climate change and NDVI. LULC maps based on NDVI for 1990, 2000, 2010 and 2024 were created using Arc GIS. Regression analysis (R2) was employed to examine the correlation between temperature and vegetation cover (NDVI). Findings revealed an increase in built-up areas from 2.25% to 9.70%, coupled with a decline in vegetation cover by 12% between 1991 and 2024. Mean NDVI values declined from 0.24 to 0.20 during this period. Survey responses indicated that 85% of farmers observed changes in climate, 70% noted agriculture affected by climate change and 81% reported climate changing due to deforestation. Regression analysis demonstrated a negative relationship between temperature and NDVI. This study highlights practical approaches and tools for local adaptation and sustainable governance of agricultural systems under changing climatic conditions, offering valuable insights for policymakers and urban planners in managing LULC at the local scale.

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Spatiotemporal Variation in Land Use Land Cover in Piyali River Sub-Basin in the Response to Local Climate Change Using Multispectral Remote Sensing Data

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  • 发表日期：

    2026年

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  • Suvendu Halder,
  • Satiprasad Sahoo,
  • Tumpa Hazra,
  • Anupam Debsarkar

摘要

Climate change poses significant social, economic, and environmental challenges for farmers whose livelihoods depend on natural resources. Analyzing Land Use Land Cover (LULC) changes has proven to be an essential method for monitoring transformations across various temporal and spatial scales. The Normalized Difference Vegetation Index (NDVI) serves as a valuable remote sensing tool, effectively capturing vegetation patterns across diverse ecological regions and aiding in the study of phonological cycles. This research utilized remote sensing and Geographic Information System (GIS) techniques to analyze LULC changes over 34 years in Piyali sub-basin. Additionally, some questionnaires were conducted with local farmers to explore the relationship between climate change and NDVI. LULC maps based on NDVI for 1990, 2000, 2010 and 2024 were created using Arc GIS. Regression analysis (R2) was employed to examine the correlation between temperature and vegetation cover (NDVI). Findings revealed an increase in built-up areas from 2.25% to 9.70%, coupled with a decline in vegetation cover by 12% between 1991 and 2024. Mean NDVI values declined from 0.24 to 0.20 during this period. Survey responses indicated that 85% of farmers observed changes in climate, 70% noted agriculture affected by climate change and 81% reported climate changing due to deforestation. Regression analysis demonstrated a negative relationship between temperature and NDVI. This study highlights practical approaches and tools for local adaptation and sustainable governance of agricultural systems under changing climatic conditions, offering valuable insights for policymakers and urban planners in managing LULC at the local scale.