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Intelligent mapping of ecological restoration elements in abandoned open-pit mines based on UAV remote sensing 认领 引用
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作者 Wei Wang Rui Guo +1 位作者 Guangqi Chen Xiaotian Wang 《Intelligent Geoengineering》 2025年第4期236-250,共15页
The ecological degradation caused by open-pit activities has become a major challenge in resource-rich regions of China.Traditional methods for identifying ecological restoration elements in abandoned mines based prim... The ecological degradation caused by open-pit activities has become a major challenge in resource-rich regions of China.Traditional methods for identifying ecological restoration elements in abandoned mines based primarily on manual interpretation,which are time-consuming and lack scalability.This study proposes an intelligent mapping framework that integrates UAV-based remote sensing data with deep learning-based semantic segmentation to automatically extract key restoration elements in abandoned open-pit mines.High-resolution RGB imagery and topographic derivatives were acquired for a mining area in Lingqiu County,Shanxi Province.A specialized four-channel dataset was constructed to enhance model performance,and three semantic segmentation models(U-Net,DeepLab v3+,and PAN)were evaluated.Results show that the PAN model with an EfficientNet-B4 backbone achieves the best performance,yielding a mean accuracy of 82.41%,recall of 80.38%,F1-score of 80.29%,and IoU of 67.46%.The proposed method effectively distinguishes between tailings slopes,tailings platform,open-pit areas,and natural zones,even in scenarios where spectral similarity limits traditional classification.This study demonstrates the feasibility and efficiency of applying deep learning to UAV remote sensing for mine ecological restoration.The proposed framework provides a scalable and practical solution for supporting high-resolution restoration planning in complex mining environments. 展开更多
关键词 Open-pit mine Ecological restoration Semantic segmentation Intelligent mapping
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Data Logic Structure and Key Technologies on Intelligent High-precision Map 认领 引用 被引量：17
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作者 Jingnan LIU Jiao ZHAN +2 位作者 Chi GUO Tingting LEI Ying LI 《Journal of Geodesy and Geoinformation Science》 2020年第3期1-17,共17页
Taking autonomous driving and driverless as the research object,we discuss and define intelligent high-precision map.Intelligent high-precision map is considered as a key link of future travel,a carrier of real-time p... Taking autonomous driving and driverless as the research object,we discuss and define intelligent high-precision map.Intelligent high-precision map is considered as a key link of future travel,a carrier of real-time perception of traffic resources in the entire space-time range,and the criterion for the operation and control of the whole process of the vehicle.As a new form of map,it has distinctive features in terms of cartography theory and application requirements compared with traditional navigation electronic maps.Thus,it is necessary to analyze and discuss its key features and problems to promote the development of research and application of intelligent high-precision map.Accordingly,we propose an information transmission model based on the cartography theory and combine the wheeled robot’s control flow in practical application.Next,we put forward the data logic structure of intelligent high-precision map,and analyze its application in autonomous driving.Then,we summarize the computing mode of“Crowdsourcing+Edge-Cloud Collaborative Computing”,and carry out key technical analysis on how to improve the quality of crowdsourced data.We also analyze the effective application scenarios of intelligent high-precision map in the future.Finally,we present some thoughts and suggestions for the future development of this field. 展开更多
关键词 intelligent high-precision map information transmission model data logic structure user model computing mode edge-cloud collaboration
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