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The current study assesses how Land Surface Temperatures (LST) vary seasonally throughout a varied landscape. The research examines a connection between LST and the Normalized Difference Vegetation index (NDVI), a remote sensing indicator. These indices have been very helpful a variety of fields, including hydrology, forestry, urban planning, and agriculture. However, they still have issues like atmospheric interference, saturation in heavily vegetated areas, and trouble classifying mixed land cover. Remote sensing data indicate that the maturing season, planting density, cover of vegetation, farming system, and research area all affect the indices’ values over the experimental period (2021–2023). In remote sensing, vegetation indices are essential instruments that allow for the monitoring and study of diverse environmental conditions across varied landscapes. In the selected research area, taluka Sillod, Dist. Chhatrapati Sambhajinagar, Maharashtra, India, Landsat 8 OLI (Operational Land Imager) and TIRS (Thermal Infrared Sensor) images were used for the summer, monsoon, and winter seasons, respectively, 2021, 2022, and 2023.

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Evaluating Seasonal Changes in Vegetation and LST Using NDVI in Sillod, Maharashtra

  • 会议论文

  • 发表日期：

    2026年

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  • Pratibha P. Dapke,
  • Samadhan M. Nagare,
  • Syed Ahteshamuddin Quadri,
  • Ramnath M. Gaikwad,
  • Manasi R. Baheti

摘要

The current study assesses how Land Surface Temperatures (LST) vary seasonally throughout a varied landscape. The research examines a connection between LST and the Normalized Difference Vegetation index (NDVI), a remote sensing indicator. These indices have been very helpful a variety of fields, including hydrology, forestry, urban planning, and agriculture. However, they still have issues like atmospheric interference, saturation in heavily vegetated areas, and trouble classifying mixed land cover. Remote sensing data indicate that the maturing season, planting density, cover of vegetation, farming system, and research area all affect the indices’ values over the experimental period (2021–2023). In remote sensing, vegetation indices are essential instruments that allow for the monitoring and study of diverse environmental conditions across varied landscapes. In the selected research area, taluka Sillod, Dist. Chhatrapati Sambhajinagar, Maharashtra, India, Landsat 8 OLI (Operational Land Imager) and TIRS (Thermal Infrared Sensor) images were used for the summer, monsoon, and winter seasons, respectively, 2021, 2022, and 2023.