The distribution of forest-dominant tree species is crucial for ecosystem assessment. Remote sensing monitoring requires annual ground sample data, but consistent field surveys are challenging. This study addresses this by combining sample migration learning and machine learning for multi-year tree species classification in the Three Gorges Reservoir area in China. Using the continuous change detection and classification (CCDC) algorithm, sample data from 2023 were successfully migrated to 2018–2022, achieving high migration accuracy (${\mathrm{R}}^2$ = 0.8303, RMSE = 4.64). Based on migrated samples, random forest (RF), support vector machine (SVM), and extreme gradient boosting (XGB) algorithms classified forest tree species with overall accuracies above 70% and Kappa coefficients above 0.6. XGB. They outperformed other algorithms, with classification accuracy of over 80% and Kappa above 0.75 in almost all years. The final map indicates stable distribution from 2018 to 2023, with eucalyptus covering over 40% of the forest area, followed by horsetail pine, fir, cypress, and wetland pine.

The assessment of soil erosion in a region can provide an effective reference for local ecological environment management. The Yunnan–Guizhou Plateau54 is an important ecological security barrier in southwest China, owing to its unique climatic and environmental characteristics and superior natural resource endowment. The current research focus is the spatial analysis of a certain area. In this study, soil erosion in the Yunnan–Guizhou Plateau during 2000–2030 was analyzed and predicted from two aspects of structure and spatial layout by coupling several models. The report also analyzes the shift in the center of gravity of land use and analyzes the drivers of soil erosion, analyzing soil erosion by land use type. The study shows a decreasing trend in the soil erosion modulus from 2000 to 2020 from 1183.69 to 704.58 t·hm⁻²·a⁻¹, but it is expected to have an increasing trend in the future and will increase to 877.72 t·hm⁻²·a⁻¹. Analyzing the drivers of soil erosion allows for testing whether the factor affects the spatial distribution of the independent variable and to what extent it explains that dependent variable. This study showed that elevation had the highest explanatory power for soil erosion. Relatively high mountainous areas are often subject to greater soil erosion due to their steep topography, resulting in poorer vegetation cover. The north–south offset distance is greater than the east–west offset distance for forested land, water and unutilized land, and the east–west offset distance is greater than the north–south offset distance for cropland, grassland and built-up land in the Yunnan–Guizhou Plateau. The purpose of this study is to identify areas of serious soil erosion vulnerability in the Yunnan–Guizhou Plateau, and to analyze the driving factors affecting soil erosion vulnerability, so as to provide a basis for regional soil erosion management, and, at the same time, to provide a reference for the government to formulate soil and water conservation measures.