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<p>Land degradation is a critical global issue with profound implications for ecosystem services and environmental stability. This study investigates land degradation and vegetation dynamics in a typical semi-arid region, Ningxia Hui Autonomous Region of China, using MODIS NDVI data and integrating climatic variables to assess their long-term impact on vegetation growth. The analysis reveals substantial vegetation improvement during 2001–2022, with 73.26% of the region showing significant annual greening and 75.45% during the growing season. The predictive analysis using the Hurst Exponent (<i>H</i>-values typically &gt; 0.5) reveals a strong and stable continuation of observed vegetation trends, with H-values suggesting sustained increases in vegetation cover. Multi-scale temporal analysis reveals scale-dependent climate-vegetation relationships at annual timescales, precipitation exhibits more spatially extensive correlations than temperature, highlighting its crucial role as the fundamental constraint in water-limited environments; however, monthly lag correlation analysis reveals both climate variables show strong correlations through distinct temporal mechanisms, with precipitation exhibiting predominantly synchronous responses (0-month lag) and temperature showing lagged responses (1-month lag), providing mechanistic insights into vegetation-climate coupling in managed semi-arid landscapes. While vegetation improvement was noted, a deeper assessment using the SDG Indicator 15.3.1 framework combining land cover change, vegetation productivity, and ecosystem carbon stocks provide a more detailed understanding. A comparison between baseline and recent data shows that, while 44.71% of the land initially demonstrated significant improvement at baseline, recent evaluations indicate a slight decline, with 15.39% of the land now classified as degraded. These findings suggest that, although restoration efforts have been effective in some areas, broader-scale improvements remain limited in study area. The most significant land cover changes were observed in artificial areas, reflecting the rapid urban expansion likely driven by population growth and industrial development. Additionally, significant negative trends were observed in wetlands and water bodies, highlighting the urgent need for immediate conservation efforts. These findings emphasize importance of adaptive land management strategies that account for seasonal vegetation dynamics, multi-scale climate-vegetation interactions, and long-term land degradation, particularly in global semi-arid regions facing urban expansion and water scarcity.</p>

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Assessing vegetation trends and land degradation in a typical semi-arid region: insights from the sustainable development goal 15.3.1 framework and remote sensing

  • 期刊论文

  • 发表日期：

    2026年6月24日

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  • Adeel Ahmad,
  • Ali Salem Al-Sakkaf,
  • Shawkat Ali,
  • Hidayat Ullah,
  • Barjeece Bashir,
  • Kashif Mahmood,
  • Jiahua Zhang

摘要

Land degradation is a critical global issue with profound implications for ecosystem services and environmental stability. This study investigates land degradation and vegetation dynamics in a typical semi-arid region, Ningxia Hui Autonomous Region of China, using MODIS NDVI data and integrating climatic variables to assess their long-term impact on vegetation growth. The analysis reveals substantial vegetation improvement during 2001–2022, with 73.26% of the region showing significant annual greening and 75.45% during the growing season. The predictive analysis using the Hurst Exponent (H-values typically > 0.5) reveals a strong and stable continuation of observed vegetation trends, with H-values suggesting sustained increases in vegetation cover. Multi-scale temporal analysis reveals scale-dependent climate-vegetation relationships at annual timescales, precipitation exhibits more spatially extensive correlations than temperature, highlighting its crucial role as the fundamental constraint in water-limited environments; however, monthly lag correlation analysis reveals both climate variables show strong correlations through distinct temporal mechanisms, with precipitation exhibiting predominantly synchronous responses (0-month lag) and temperature showing lagged responses (1-month lag), providing mechanistic insights into vegetation-climate coupling in managed semi-arid landscapes. While vegetation improvement was noted, a deeper assessment using the SDG Indicator 15.3.1 framework combining land cover change, vegetation productivity, and ecosystem carbon stocks provide a more detailed understanding. A comparison between baseline and recent data shows that, while 44.71% of the land initially demonstrated significant improvement at baseline, recent evaluations indicate a slight decline, with 15.39% of the land now classified as degraded. These findings suggest that, although restoration efforts have been effective in some areas, broader-scale improvements remain limited in study area. The most significant land cover changes were observed in artificial areas, reflecting the rapid urban expansion likely driven by population growth and industrial development. Additionally, significant negative trends were observed in wetlands and water bodies, highlighting the urgent need for immediate conservation efforts. These findings emphasize importance of adaptive land management strategies that account for seasonal vegetation dynamics, multi-scale climate-vegetation interactions, and long-term land degradation, particularly in global semi-arid regions facing urban expansion and water scarcity.