基于AI遥感解译的生态环保督察要素智能识别提取模型OA

To address the pain points such as the wide regional coverage,strong concealment of problems,and high diffi-culty of manual screening in ecological and environmental protection inspection work,this paper combined high-resolution remote sensing image data with artificial intelligence(AI)remote sensing interpretation technology.Relying on the machine learning module of Supermap iDesktopX and deep learning algorithms of convolutional neural networks,an intelligent identi-fication and extraction model was constructed,covering five categories of inspection elements:construction sites,sand and gravel yards,mixing stations,domestic waste,and construction waste.By taking Miyun District and Yanqing District of Beijing as pilot areas,this model was applied to carry out the automatic identification and extraction of the five categories of inspection elements.The results show that the constructed identification model for these five categories can all efficiently and accurately identify various inspection clues within the target areas,and the identification accuracy meets the expected stan-dards.This research provides an innovative technical means for ecological and environmental protection inspection work and provides theoretical support and practical reference for the popularization and application of AI remote sensing interpretation technology in the field of ecological and environmental protection.