
Based on AI semantic segmentation and sub-meter satellite imagery, this method achieves refined, automated land cover classification by integrating multispectral, texture and topological features. It extracts spatial and attribute data of cultivated land, forest, water, construction land and wetlands for territorial spatial planning, land use survey and river‑lake disorder inspection.


Based on sub-meter remote sensing image data and integrated with AI intelligent land use classification algorithms, refined and intelligent classification of land use is completed, accurately dividing into 8 major categories and 25 subcategories including cultivated land, woodland, grassland, and construction land. This supports the acquisition of core information such as the area scale and spatial distribution of various types of land use, and provides accurate data support for scenarios such as regional territorial spatial planning compilation, refined land resource management, and dynamic monitoring of soil erosion.The figure shows the 2025 land use classification results of a region.
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