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<p>A quantitative assessment of Land Use and Land Cover (LULC) dynamics and their impact on surface thermal behavior is crucial for sustainable land management in ecologically sensitive regions. This research uses multi-temporal Landsat-8 imagery from 2014 to 2025 to investigate LULC changes, vegetation dynamics, and LST fluctuations in Pathanamthitta district, Kerala, India. Supervised classification based on the Maximum Likelihood algorithm was implemented within a Geographic Information System (GIS) framework to describe five LULC classes, such as water body, forest, agricultural land, bare soil, and built-up areas. Classification performance was evaluated using confusion matrices, yielding overall accuracies of 90.01% (2014) and 85.36% (2025), with Cohen’s Kappa coefficients of 0.82 and 0.79, indicating substantial agreement. The results reveal a significant expansion of built-up areas, primarily due to conversion from agricultural land, forest, and bare soil, reflecting accelerated urbanisation. Although forest remains the dominant land cover, localised reductions were observed. The Normalised Difference Vegetative Index (NDVI) revealed consistent vegetative health, with values ranging from − 0.04 to 0.53 in 2014 and − 0.04 to 0.52 in 2025, showing largely stable vegetation health. Landsat-8 thermal infrared data shows a consistent warming trend across the area, with maximum LST rising from 36.23&#xa0;°C in 2014 to 39.65&#xa0;°C in 2025 and minimum LST rising from 11.59 to 13.94. Spatial correlation analysis reveals that NDVI and LST have a statistically significant moderate inverse relationship, indicating a cooling impact of vegetation. The integrated LULC–NDVI–LST framework provides valuable insights for climate-responsive land-use planning, urban growth management, and ecosystem conservation.</p>

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Spatio-temporal Quantitative Analysis of Land Use/Land Cover Changes and Land Surface Temperature in a Revenue District of Kerala, India, Using Multi-temporal Satellite Imagery

  • 期刊论文

  • 发表日期：

    2026年7月7日

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  • P. S. Hitha,
  • M. K. Sheeja

摘要

A quantitative assessment of Land Use and Land Cover (LULC) dynamics and their impact on surface thermal behavior is crucial for sustainable land management in ecologically sensitive regions. This research uses multi-temporal Landsat-8 imagery from 2014 to 2025 to investigate LULC changes, vegetation dynamics, and LST fluctuations in Pathanamthitta district, Kerala, India. Supervised classification based on the Maximum Likelihood algorithm was implemented within a Geographic Information System (GIS) framework to describe five LULC classes, such as water body, forest, agricultural land, bare soil, and built-up areas. Classification performance was evaluated using confusion matrices, yielding overall accuracies of 90.01% (2014) and 85.36% (2025), with Cohen’s Kappa coefficients of 0.82 and 0.79, indicating substantial agreement. The results reveal a significant expansion of built-up areas, primarily due to conversion from agricultural land, forest, and bare soil, reflecting accelerated urbanisation. Although forest remains the dominant land cover, localised reductions were observed. The Normalised Difference Vegetative Index (NDVI) revealed consistent vegetative health, with values ranging from − 0.04 to 0.53 in 2014 and − 0.04 to 0.52 in 2025, showing largely stable vegetation health. Landsat-8 thermal infrared data shows a consistent warming trend across the area, with maximum LST rising from 36.23 °C in 2014 to 39.65 °C in 2025 and minimum LST rising from 11.59 to 13.94. Spatial correlation analysis reveals that NDVI and LST have a statistically significant moderate inverse relationship, indicating a cooling impact of vegetation. The integrated LULC–NDVI–LST framework provides valuable insights for climate-responsive land-use planning, urban growth management, and ecosystem conservation.