Thirty years’ spatio-temporal evolution of desertification degrees and driving factors in Turpan–Hami Basin, Xinjiang, China

Abstract

Turpan-Hami (Tuha) Basin is in an extremely arid area, surrounded by mountains and desert with sparse vegetation. It has experienced serious desertification over the past 30 years, resulting in ecological environment and socio-economic issues. To reveal the temporal and spatial evolutions of desertification degrees in Tuha Basin, we first constructed an evaluation system for the desertification degree classification using vegetation and soil-related indices; then long-time series Landsat 5 TM/ Landsat8 OLI images and a C5.0 decision tree (DT) model were used to monitor large-scale desertification from 1990 to 2020. We applied a geographic detector to discover the driving forces between desertification changes and natural and human factors. The results demonstrated that the severe desertification (SD) accounted for the largest desertification degree, and the transitions of various desertification degrees mainly occurred between extremely severe desertification (ESD) and SD, which were considered the most active degrees. Only 9.4 % of Tuha Basin showed an expansion trend in desertification degree, with the most significant expansion occurred in 1990–1995. The proportion of 13.6 % desertification showed a reversion trend, with the most significant reversion occurred in 1995–2010. The main driving factors affecting the evolution of desertification degrees were precipitation and temperature, with the average q value higher than 0.95. Human activity factors such as year-end cropland area and population also impacted the patterns of desertification degree, with the q values of 0.9 and 0.7, respectively. The interactive detection enhanced the driving forces and the interaction between precipitation and other factors played a leading role in desertification degree changes. The results provide scientific data and a basis for desertification control and ecological protection in arid areas.

Keywords

• Desertification degree classification
• Decision tree model
• Remote sensing
• Geographic detector