A method for automatic mapping of the remote sensing monitoring results of national nature reserves based on ArcPy and map optimization
WANG Tixin1,2(), YANG Jinzhong1(), XING Yu1, WANG Kaijian1
1. China Aero Geophysical Survey and Remote Sensing Center for Natural Resources,Beijing 100083, China 2. School of Earth Science and Resources, China University of Geosciences(Beijing), Beijing 100083,China
Remote sensing monitoring in national-level nature reserves covers a land area of approximately 1.7 million km2. This process involves the delineation of numerous features that indicate variations in the nature reserves, requiring specialized expertise. As a result, ensuring the accuracy and normalization of mapping is challenging even using substantial human and material resources. This affects the quality and effectiveness of monitoring result applications and relevant services. To address this issue, employing geometric techniques like the Sutherland-Hodgman clipping algorithm based on the ArcPy package, along with the customized ArcToolbox tools for encapsulating automated mapping scripts, this study automatically extracted the information and images of features from a geographic database. Subsequently, this study automatically generated the distribution maps of features that reflected variations in national-level nature reserves. Over 50000 maps were plotted using the proposed method, with an accuracy of 100%. Practical application demonstrates that the automatic mapping for a single map can be completed within 29.06 s on average, significantly less than manual mapping. The proposed method can meet practical production needs, with the automated mapping scripts proving stable, reliable, and widely applicable. The proposed method can significantly enhance the efficiency of the applications of the monitoring results reflecting variations in the national-level nature reserves, holding great practical significance.
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WANG Tixin, YANG Jinzhong, XING Yu, WANG Kaijian. A method for automatic mapping of the remote sensing monitoring results of national nature reserves based on ArcPy and map optimization. Remote Sensing for Natural Resources, 2025, 37(1): 252-259.
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