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<p>Understanding the relationship between land use/land cover (LULC) changes and land surface temperature (LST) is essential for effective environmental planning and climate adaptation strategies. This study investigates the spatiotemporal dynamics of LULC and its impact on LST in the Mahananda River Basin, India, from 1994 to 2024 using geospatial analysis.&#xa0;The Landsat images were classified into six LULC classes using the Random Forest (RF) algorithm, and the Kappa coefficient was used for accuracy assessment. LST was extracted using the thermal bands of Landsat and validated using in situ data. Subsequently, vegetation and surface indices, NDVI, NDWI, and NDBSI, were developed to explore their relationships with LST using correlation and regression analysis.&#xa0;Results indicate that urban areas increased from 7.82% (1994) to 17.45% (2024), while vegetation and agricultural lands decreased by 6.34% and 8.11%, respectively. At the same time, mean LST rose from 27.14&#xa0;°C (1994) to 32.67&#xa0;°C (2024), with urban and bare surfaces having the highest LST (&gt; 34&#xa0;°C), as compared to vegetated areas (&lt; 29&#xa0;°C). LST showed a strong positive correlation with NDBSI (<i>r</i> = 0.74), affirming the thermal influence of built-up surfaces, whereas NDVI (<i>r</i> = − 0.68) and NDWI (<i>r</i> = − 0.61) exhibit high negative correlations, validating the cooling influence of vegetation and water. Anomalies occurred in 2014 when NDWI registered a weaker correlation as a result of seasonal variation.&#xa0;The findings indicate that rapid urbanization and land degradation amplify the urban heat island effect. This research suggests adopting green infrastructure, maintaining vegetative cover, and encouraging integrated land use planning to reduce surface temperatures and make the Mahananda River Basin environmentally sustainable.</p>

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Spatiotemporal dynamics of land use transitions and surface thermal patterns in the Mahananda river basin

  • 期刊论文

  • 发表日期：

    2025年12月30日

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  • Payel Bhuin,
  • Kiran Yarrakula

摘要

Understanding the relationship between land use/land cover (LULC) changes and land surface temperature (LST) is essential for effective environmental planning and climate adaptation strategies. This study investigates the spatiotemporal dynamics of LULC and its impact on LST in the Mahananda River Basin, India, from 1994 to 2024 using geospatial analysis. The Landsat images were classified into six LULC classes using the Random Forest (RF) algorithm, and the Kappa coefficient was used for accuracy assessment. LST was extracted using the thermal bands of Landsat and validated using in situ data. Subsequently, vegetation and surface indices, NDVI, NDWI, and NDBSI, were developed to explore their relationships with LST using correlation and regression analysis. Results indicate that urban areas increased from 7.82% (1994) to 17.45% (2024), while vegetation and agricultural lands decreased by 6.34% and 8.11%, respectively. At the same time, mean LST rose from 27.14 °C (1994) to 32.67 °C (2024), with urban and bare surfaces having the highest LST (> 34 °C), as compared to vegetated areas (< 29 °C). LST showed a strong positive correlation with NDBSI (r = 0.74), affirming the thermal influence of built-up surfaces, whereas NDVI (r = − 0.68) and NDWI (r = − 0.61) exhibit high negative correlations, validating the cooling influence of vegetation and water. Anomalies occurred in 2014 when NDWI registered a weaker correlation as a result of seasonal variation. The findings indicate that rapid urbanization and land degradation amplify the urban heat island effect. This research suggests adopting green infrastructure, maintaining vegetative cover, and encouraging integrated land use planning to reduce surface temperatures and make the Mahananda River Basin environmentally sustainable.