The karst landforms in the southwest region of China make vegetation coverage susceptible to changes. Clearly understanding the spatiotemporal patterns of vegetation evolution is of great significance for ecological civilization construction and promoting green development in the region. The kernel normalized difference vegetation index (kNDVI) has overcome the "non-linearity" characteristic of NDVI, allowing for a more precise representation of vegetation growth status compared to NDVI. Hence, this paper utilizes Landsat data on the Google Earth Engine platform to retrieve kNDVI from 1990 to 2023. Subsequently, the Theil-Sen slope estimation method and Mann-Kendall test are applied to explore the spatiotemporal evolution patterns of vegetation, while the Hurst index is used to forecast the future trends of vegetation change. The results indicate that: (1) the overall vegetation in the study area has improved, with an increase slope of 0.0057. (2) the area with significant increases account for the majority, approximately 85.21%, suggesting an overall positive trend in the spatial distribution of vegetation in the study area. (3) the northeastern part of the study area and the central part of Guangdong are experiencing a slight but sustainable decrease, yet the future vegetation change is expected to be characterized mainly by significant and sustainable increases. The results of this study can provide scientific theoretical support for strengthening ecological environment protection and governance.
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