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| Advances in urban information extraction from high-resolution remote sensing imagery | |
| 作者姓名： | Jianya GONG Chun LIU Xin HUANG |
| 作者单位： | School of Remote Sensing and Information Engineering;State Key Laboratory of Information Engineering in Surveying |
| 基金项目： | supported by the National Natural Science Foundation of China(Grant Nos.41771360&41842035);the National Program for Support of Top-notch Young Professionals;the Hubei Provincial Natural Science Foundation of China(Grant No.2017CFA029);the National Key Research and Development Program of China(Grant No.2016YFB0501403);the Shenzhen Science and Technology Program(Grant No.JCYJ20180306170645080)。 |
| 摘 要： | The study of urban area is one of the hottest research topics in the field of remote sensing. With the accumulation of high-resolution(HR) remote sensing data and emerging of new satellite sensors, HR observation of urban areas has become increasingly possible, which provides us with more elaborate urban information. However, the strong heterogeneity in the spectral and spatial domain of HR imagery brings great challenges to urban remote sensing. In recent years, numerous approaches were proposed to deal with HR image interpretation over complex urban scenes, including a series of features from low level to high level, as well as state-of-the-art methods depicting not only the urban extent, but also the intra-urban variations. In this paper, we aim to summarize the major advances in HR urban remote sensing from the aspects of feature representation and information extraction. Moreover, the future trends are discussed from the perspectives of methodology, urban structure and pattern characterization, big data challenge, and global mapping. |
| 关 键 词： | HIGH-RESOLUTION URBAN REMOTE sensing FEATURE extraction LAND use/land COVER classification Change detection |
Advances in urban information extraction from high-resolution remote sensing imagery |
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| Jianya GONG,Chun LIU,Xin HUANG.Advances in urban information extraction from high-resolution remote sensing imagery[J].Science China Earth Sciences,2020,63(4):463-475. | |
| Authors: | Gong Jianya Liu Chun Huang Xin |
| Institution: | 1.School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, 430079, China ;2.State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, 430079, China ; |
| Abstract: | The study of urban area is one of the hottest research topics in the field of remote sensing. With the accumulation of high-resolution(HR) remote sensing data and emerging of new satellite sensors, HR observation of urban areas has become increasingly possible, which provides us with more elaborate urban information. However, the strong heterogeneity in the spectral and spatial domain of HR imagery brings great challenges to urban remote sensing. In recent years, numerous approaches were proposed to deal with HR image interpretation over complex urban scenes, including a series of features from low level to high level, as well as state-of-the-art methods depicting not only the urban extent, but also the intra-urban variations. In this paper, we aim to summarize the major advances in HR urban remote sensing from the aspects of feature representation and information extraction. Moreover, the future trends are discussed from the perspectives of methodology, urban structure and pattern characterization, big data challenge, and global mapping. |
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