Research progress and prospects of remote sensing classification of urban vegetation

Urban vegetation is an important part of the urban environment, and remote sensing classification of urban vegetation is an important way to monitor and analyze urban green space. By sorting the research progress of remote sensing classification of urban vegetation at home and abroad, we started fro...

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Bibliographic Details
Main Authors: MENG Qingyan, DU Hongyu, WANG Liping, ZHANG Linlin, WU Jiahao, KANG Jiaqi
Format: Article
Language:English
Published: Zhejiang University Press 2024-04-01
Series:浙江大学学报. 农业与生命科学版
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Online Access:https://www.academax.com/doi/10.3785/j.issn.1008-9209.2023.10.071
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Summary:Urban vegetation is an important part of the urban environment, and remote sensing classification of urban vegetation is an important way to monitor and analyze urban green space. By sorting the research progress of remote sensing classification of urban vegetation at home and abroad, we started from two aspects of remote sensing data sources and classification methods, and analyzed the current problems and development trends in this field, in order to provide references for urban green space research. First, the applications of optical data, light detection and ranging (LiDAR) data and ground sensing data in the remote sensing classification of urban vegetation were summarized, and the advantages and disadvantages of different data sources were analyzed in depth. Second, the characteristics of classification methods applied in the remote sensing classification of urban vegetation were summarized through the study of three classification methods, including threshold segmentation, machine learning, and deep learning. Finally, the existing problems and future development directions in the remote sensing classification of urban vegetation were proposed.
ISSN:1008-9209
2097-5155