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<p>This study evaluates long-term vegetation quality trends in Tiruppur Taluk from 1983 to 2023, using multi-spectral vegetation indices and machine learning algorithms with remote sensing techniques. Four key indices – normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), weighted vegetation index (WVI), and green modified vegetation index (GMVI) – were analyzed to assess changes over four decades. Results reveal a significant decline in very high-quality vegetation, with NDVI and SAVI dropping from over 37% in 1983 to ~5% in 2023, while WVI and GMVI showed more gradual decreases. Conversely, areas with low-quality vegetation increased, with NDVI rising from 7.50 to 33.72% and SAVI increasing from 5.60 to 31.31% during the same period. These trends indicate a substantial degradation in vegetation quality. The application of machine learning and remote sensing provided critical insights for understanding these changes, offering a foundation for improved environmental management and conservation strategies in Tiruppur Taluk.</p>

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Long-term vegetation quality assessment using multi-spectral vegetation indices: Analyzing trends from 1983 to 2023 for Tiruppur Taluk using machine learning algorithms and remote sensing techniques

  • 期刊论文

  • 发表日期：

    2025年6月25日

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  • K Kavitha,
  • P Sivaranjani,
  • K Gopalakrishnan

摘要

This study evaluates long-term vegetation quality trends in Tiruppur Taluk from 1983 to 2023, using multi-spectral vegetation indices and machine learning algorithms with remote sensing techniques. Four key indices – normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), weighted vegetation index (WVI), and green modified vegetation index (GMVI) – were analyzed to assess changes over four decades. Results reveal a significant decline in very high-quality vegetation, with NDVI and SAVI dropping from over 37% in 1983 to ~5% in 2023, while WVI and GMVI showed more gradual decreases. Conversely, areas with low-quality vegetation increased, with NDVI rising from 7.50 to 33.72% and SAVI increasing from 5.60 to 31.31% during the same period. These trends indicate a substantial degradation in vegetation quality. The application of machine learning and remote sensing provided critical insights for understanding these changes, offering a foundation for improved environmental management and conservation strategies in Tiruppur Taluk.