This application relates to a method and
system for monitoring soil and
water conservation using a combination of UAV low-altitude
remote sensing and ground-based measurements. The method includes: acquiring
remote sensing images, meteorological data, and ground-based measured data of a target area; fusing the features of the
remote sensing images, meteorological data, and ground-based measured data to obtain comprehensive target features; filtering the comprehensive target features using a
feature selector to obtain key comprehensive features; and analyzing the key comprehensive features based on a
hybrid architecture integrating GCN and TCN to obtain soil
erosion prediction results. Specifically, the GCN module in the
hybrid architecture is used to mine spatial correlations between geographical areas, while the TCN module is used to capture the temporal nonlinear changes in soil
erosion. This approach ensures both spatial accuracy of the prediction results and
temporal continuity, improving the accuracy and reliability of soil
erosion prediction and providing more scientific
technical support for soil and
water conservation planning and ecological restoration decisions.