Spatio-Temporal Dynamics of LULC in the Kolkata Metropolitan Area (2016–2024): Insights from Landsat and MODIS Geospatial Data
Ayan Chakraborty
Department of Geography, Savitribai Phule Pune University, India.
Shubham Limaye
Department of Geography, Savitribai Phule Pune University, India.
Atreya Paul *
Department of Geography, Bidhannagar Govt. College, India.
*Author to whom correspondence should be addressed.
Abstract
Aims: This study explores the dynamics of Land Use and Land Cover (LULC) and their thermal impacts within the Kolkata Metropolitan Area (KMA) from 2016 to 2024, utilizing data from Landsat 8 and MODIS. LULC maps generated through Support Vector Machine (SVM) classification indicate an increase in barren and transitional surfaces, accompanied by a decline in forested, developed, and aquatic zones.
Methodology: Biophysical indices, including NDVI, NDBI, and NDWI, were analyzed to assess vegetation levels, impervious surfaces, and the presence of water. The NDVI remained stable due to greening initiatives in peri-urban areas, while the NDBI exhibited an increase corresponding to the growth of impervious surfaces.
Results: Spectral analysis revealed a rise in NDWI values, indicating an intensification of water presence in fewer water bodies. MODIS-derived Land Surface Temperature (LST) maps reveal a regional thermal increase, particularly in areas characterized by high Normalized Difference Built-up Index (NDBI) and low Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) values. Correlation analyses indicate strong relationships: a positive correlation between NDBI and LST, and a negative correlation between NDVI/NDWI and LST. This highlights the influence of surface materials and land cover on urban warming. The study validates remote sensing as an effective tool for environmental monitoring and underscores the importance of urban land transitions in exacerbating climatic stress. The findings provide spatial evidence to support sustainable land management practices and enhance urban climate resilience.
Keywords: Spectral analysis, metropolitan agglomeration, spectral concentration, urban governance, climate resilience