Spatiotemporal Evolution and Driving Factors of Karst Rocky Desertification in Guangxi, China, Under Climate Change and Human Activities - Jialei Su; Meiling Liu; Qin Yang; Xiangnan Liu; Zeyan Wu; Yanan Wen (Remote Sensing)
Guangxi is among China’s regions most severely affected by karst rocky desertification (KRD). Over the past two decades, global climate change and human activities have jointly led to significant changes in the extent and intensity of KRD in Guangxi. Given this context, it is crucial to comprehensively analyze the spatiotemporal evolution of KRD in Guangxi and its driving forces. This study proposed a novel three-dimensional feature space model for monitoring KRD in Guangxi. We then applied transition matrices, dynamic degree indices, and landscape metrics to analyze the spatiotemporal evolution of KRD. We also proposed a Spatiotemporal Interaction Intensity Index (STII) to quantify mutual influences among KRD patches. Finally, we used GeoDetector to analyze the driving factors of KRD. The results indicate the following: (1) The three-dimensional model showed high applicability for large-scale KRD monitoring, with an overall accuracy of 92.86%. (2) KRD in Guangxi exhibited an overall recovery–deterioration–recovery trend from 2000 to 2023. The main recovery phases were 2005–2015 and 2020–2023. During these phases, both severe and moderate KRD showed strong signals of recovery, including significant declines in area, number of patches, and Landscape Shape Index, along with persistently low STII values. In contrast, from 2015 to 2020, KRD predominantly deteriorated, primarily characterized by transitions from no KRD to potential KRD and from potential KRD to light KRD. (3) For severe KRD patches, the intensity of interaction required from neighboring patches to promote recovery exceeded that which led to deterioration, indicating the difficulty of reversing severe KRD. (4) Slope, land use, and elevation were the main drivers of KRD in Guangxi from 2000 to 2023. Erosive rainfall exhibited a higher explanatory power for KRD than average precipitation. Two-factor interactions significantly enhanced the driving forces of KRD. These findings provide a scientific basis for KRD management.