Remote Sensing (May 2023)

Detection and Attribution of Greening and Land Degradation of Dryland Areas in China and America

  • Zheng Chen,
  • Jieyu Liu,
  • Xintong Hou,
  • Peiyi Fan,
  • Zhonghua Qian,
  • Li Li,
  • Zhisen Zhang,
  • Guolin Feng,
  • Bailian Li,
  • Guiquan Sun

DOI
https://doi.org/10.3390/rs15102688
Journal volume & issue
Vol. 15, no. 10
p. 2688

Abstract

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Global dryland areas are vulnerable to climate change and anthropogenic activities, making it essential to understand the primary drivers and quantify their effects on vegetation growth. In this study, we used the Time Series Segmented Residual Trends (TSS-RESTREND) method to attribute changes in vegetation to CO2, land use, climate change, and climate variability in Chinese and American dryland areas. Our analysis showed that both Chinese and American drylands have undergone a greening trend over the past four decades, with Chinese greening likely linked to climatic warming and humidification of Northwest China. Climate change was the dominant factor driving vegetation change in China, accounting for 48.3%, while CO2 fertilization was the dominant factor in American drylands, accounting for 47.9%. However, land use was the primary factor resulting in desertification in both regions. Regional analysis revealed the importance of understanding the drivers of vegetation change and land degradation in Chinese and American drylands to prevent desertification. These findings highlight the need for sustainable management practices that consider the complex interplay of climate change, land use, and vegetation growth in dryland areas.

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