High-Precision DEM Reconstruction and Vegetation Cover Classification Inversion Based on Beijing-3 Stereo Imagery

Digital elevation models (DEMs) and vegetation cover (FVC) are critical foundational data for ecological and environmental monitoring and land-use management; however, the application of domestically produced commercial high-resolution optical satellite stereo imagery for high-precision DEM construction and vegetation parameter inversion in areas with complex topography still requires further exploration. This study focuses on the hilly area in the northeastern part of Kunming City, Yunnan Province, and utilizes tri-view stereo imagery from the Beijing-3 (BJ3-N2) satellite to conduct research on DEM reconstruction, topographic correction, image fusion, and vegetation cover inversion. DEM products were generated by matching multiple sets of panchromatic and multispectral stereo imagery, and their accuracy was verified using ICESat-2 ATL08 laser altimetry data. The results indicate that DEMs generated from panchromatic imagery exhibit higher accuracy than those from multispectral imagery; among them, the PAN-0103 DEM demonstrated the best overall performance, with a global RMSE of 3.42 m. Topographic slope and land cover type were found to have significant effects on DEM accuracy. A terrain-constrained Gram–Schmidt fusion model was constructed based on the optimal DEM to generate the fused image MP-01, which had a spectral angle (SAM) of 3.2° and a band correlation coefficient (CC) of 0.92. Further, by integrating field RTK plot data, an improved pixel binary model was constructed to perform FVC inversion. The results showed that the Mahalanobis distance classification method yielded the best classification performance, with a model inversion RMSE of 0.074—a 41.7% reduction compared to the traditional fixed-end element model. The study demonstrates that the high-resolution stereo imagery from Beijing-3 can effectively support the refined construction of DEMs and quantitative monitoring of vegetation cover in complex hilly areas and can provide a technical reference for the application of domestically produced commercial remote sensing satellites in the field of ecological monitoring.