Spatiotemporal Dynamics and Driving Forces of Desertification in Northwestern China

The arid region of Northwest China (ARNWC) faces severe desertification, posing a major threat to ecological sustainability and socio-economic development. However, systematic evaluation of desertification across the entire northwestern arid zone remains limited. To address the uncertainty caused by mixed pixels in sparsely vegetated drylands, this study innovatively integrates vegetation and soil indices to develop a robust machine learning-based system for classifying desertification levels in the ARNWC over three decades. In addition, the geographical detector method is employed to quantify the driving factors influencing desertification. The key findings are as follows: (1) Desertification expansion predominantly occurred between 1990 and 1995, followed by a gradual improvement from 1995 to 2020. Transitions between severe and moderate desertification were the most frequent, with approximately 15 × 10 4 km 2 shifting from severe to moderate desertification. (2) Physiographic factors were the primary drivers of changes in desertification level, followed by climatic factors. Fractional Vegetation Cover (FVC) had the strongest influence, with an average q -value of 0.72. (3) The explanatory power of the drivers increased significantly through interactions, with the combination of FVC and evaporation (EVA) showing the most pronounced effect. Overall, the methods and findings of this study provide critical insights for targeted desertification control and ecological restoration strategies in arid regions. Although this approach primarily captures desertification symptoms related to surface cover, it offers a valuable long-term perspective on surface cover dynamics.