Intelligent purification of natural resource element change polygons driven by remote sensing spatiotemporal knowledge graphs
Peer-Reviewed Publication
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With the rapid development of natural resource element change monitoring technology based on remote sensing imagery, improving the accuracy of change polygons and reducing false alarms have become key research topics. Professor Li Yansheng and his team at the School of Remote Sensing and Information Engineering, Wuhan University, proposed an intelligent purification method for natural resource element change polygons based on a remote sensing spatiotemporal knowledge graph. This method effectively reduces false alarm rates while ensuring a high recall rate, thus significantly improving the efficiency of natural resource monitoring. The related research results were published in the Journal of Geo-Information Science.
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