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This paper presents the exploration of Landsat images based on normalized difference vegetation index (NDVI) technique. By estimating their Normalized Difference Vegetation Index for surface area classification, land resources may be simply evaluated. This research aims to assess the NDVI technique to detect changes in the area's vegetation pattern and elimination of green covers over an 11-year period in Jaipur, the state capital of Rajasthan. The USGS Earth Explorer Landsat images of years 2012 and 2023 were used in the investigation. Through this study a significant decrease in vegetation cover was observed, as evidenced by the mean NDVI values declining from 0.1576 in 2012 to 0.1278 in 2023. This reduction may be attributed to increased urbanization, loss of green areas, and land degradation.The findings illustrate the need for sustainable urban forecast and natural resource management along with the effectiveness of NDVI based remote sensing in tracing ecological degradation.

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Monitoring of Land Degradation in Jaipur City Area Using Landsat Images by Estimating NDVI Index

  • 会议论文

  • 发表日期：

    2026年

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  • Nikhar Bhatnagar,
  • Sumit Srivastava,
  • Shally Vats

摘要

This paper presents the exploration of Landsat images based on normalized difference vegetation index (NDVI) technique. By estimating their Normalized Difference Vegetation Index for surface area classification, land resources may be simply evaluated. This research aims to assess the NDVI technique to detect changes in the area's vegetation pattern and elimination of green covers over an 11-year period in Jaipur, the state capital of Rajasthan. The USGS Earth Explorer Landsat images of years 2012 and 2023 were used in the investigation. Through this study a significant decrease in vegetation cover was observed, as evidenced by the mean NDVI values declining from 0.1576 in 2012 to 0.1278 in 2023. This reduction may be attributed to increased urbanization, loss of green areas, and land degradation.The findings illustrate the need for sustainable urban forecast and natural resource management along with the effectiveness of NDVI based remote sensing in tracing ecological degradation.