Urban Building Change Detection in SAR Images Using Combined Differential Image and Residual U-Net Network
With the rapid development of urbanization in China, monitoring urban changes is of great significance to city management, urban planning, and cadastral map updating. Spaceborne synthetic aperture radar (SAR) sensors can capture a large area of radar images quickly with fine spatiotemporal resolutio...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-05-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/11/9/1091 |
| _version_ | 1798018656468205568 |
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| author | Lu Li Chao Wang Hong Zhang Bo Zhang Fan Wu |
| author_facet | Lu Li Chao Wang Hong Zhang Bo Zhang Fan Wu |
| author_sort | Lu Li |
| collection | DOAJ |
| description | With the rapid development of urbanization in China, monitoring urban changes is of great significance to city management, urban planning, and cadastral map updating. Spaceborne synthetic aperture radar (SAR) sensors can capture a large area of radar images quickly with fine spatiotemporal resolution and are not affected by weather conditions, making multi-temporal SAR images suitable for change detection. In this paper, a new urban building change detection method based on an improved difference image and residual U-Net network is proposed. In order to overcome the intensity compression problem of the traditional log-ratio method, the spatial distance and intensity similarity are combined to generate a weighting function to obtain a weighted difference image. By fusing the weighted difference image and the bitemporal original images, the three-channel color difference image is generated for building change detection. Due to the complexity of urban environments and the small scale of building changes, the residual U-Net network is used instead of fixed statistical models and the construction and classifier of the network are modified to distinguish between different building changes. Three scenes of Sentinel-1 interferometric wide swath data are used to validate the proposed method. The experimental results and comparative analysis show that our proposed method is effective for urban building change detection and is superior to the original U-Net and SVM method. |
| first_indexed | 2024-04-11T16:27:59Z |
| format | Article |
| id | doaj.art-54023721accc4247a1e548cbd08ecdd7 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-04-11T16:27:59Z |
| publishDate | 2019-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-54023721accc4247a1e548cbd08ecdd72022-12-22T04:14:07ZengMDPI AGRemote Sensing2072-42922019-05-01119109110.3390/rs11091091rs11091091Urban Building Change Detection in SAR Images Using Combined Differential Image and Residual U-Net NetworkLu Li0Chao Wang1Hong Zhang2Bo Zhang3Fan Wu4Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, ChinaKey Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, ChinaKey Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, ChinaKey Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, ChinaKey Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, ChinaWith the rapid development of urbanization in China, monitoring urban changes is of great significance to city management, urban planning, and cadastral map updating. Spaceborne synthetic aperture radar (SAR) sensors can capture a large area of radar images quickly with fine spatiotemporal resolution and are not affected by weather conditions, making multi-temporal SAR images suitable for change detection. In this paper, a new urban building change detection method based on an improved difference image and residual U-Net network is proposed. In order to overcome the intensity compression problem of the traditional log-ratio method, the spatial distance and intensity similarity are combined to generate a weighting function to obtain a weighted difference image. By fusing the weighted difference image and the bitemporal original images, the three-channel color difference image is generated for building change detection. Due to the complexity of urban environments and the small scale of building changes, the residual U-Net network is used instead of fixed statistical models and the construction and classifier of the network are modified to distinguish between different building changes. Three scenes of Sentinel-1 interferometric wide swath data are used to validate the proposed method. The experimental results and comparative analysis show that our proposed method is effective for urban building change detection and is superior to the original U-Net and SVM method.https://www.mdpi.com/2072-4292/11/9/1091weighted functioncolor difference imageurban building change detectionsynthetic aperture radar (SAR)residual U-Net |
| spellingShingle | Lu Li Chao Wang Hong Zhang Bo Zhang Fan Wu Urban Building Change Detection in SAR Images Using Combined Differential Image and Residual U-Net Network Remote Sensing weighted function color difference image urban building change detection synthetic aperture radar (SAR) residual U-Net |
| title | Urban Building Change Detection in SAR Images Using Combined Differential Image and Residual U-Net Network |
| title_full | Urban Building Change Detection in SAR Images Using Combined Differential Image and Residual U-Net Network |
| title_fullStr | Urban Building Change Detection in SAR Images Using Combined Differential Image and Residual U-Net Network |
| title_full_unstemmed | Urban Building Change Detection in SAR Images Using Combined Differential Image and Residual U-Net Network |
| title_short | Urban Building Change Detection in SAR Images Using Combined Differential Image and Residual U-Net Network |
| title_sort | urban building change detection in sar images using combined differential image and residual u net network |
| topic | weighted function color difference image urban building change detection synthetic aperture radar (SAR) residual U-Net |
| url | https://www.mdpi.com/2072-4292/11/9/1091 |
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