ASSESSMENT OF BUILDINGS AND ELECTRICAL FACILITIES DAMAGED BY FLOOD AND EARTHQUAKE FROM SATELLITE IMAGERY
Natural disasters cause considerable losses to people’s lives and property. Satellite images can provide crucial information of the affected areas for the first time, conducive to relieving the people in disaster and reducing the economic loss. However, the traditional satellite image analysis metho...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2022-04-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLVI-3-W1-2022/133/2022/isprs-archives-XLVI-3-W1-2022-133-2022.pdf |
| _version_ | 1817988783996403712 |
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| author | Y. Ma F. Zhou G. Wen H. Gen R. Huang G. Liu L. Pei |
| author_facet | Y. Ma F. Zhou G. Wen H. Gen R. Huang G. Liu L. Pei |
| author_sort | Y. Ma |
| collection | DOAJ |
| description | Natural disasters cause considerable losses to people’s lives and property. Satellite images can provide crucial information of the affected areas for the first time, conducive to relieving the people in disaster and reducing the economic loss. However, the traditional satellite image analysis method based on manual processing drains workforce and material resources, which slowed the government’s response to the disaster. Aiming at the natural disasters like floods and earthquakes that often happen in the south of China, we propose a dual-stage damage assessment method based on LEDNet and ResNet. Our method detects the changes between the satellite images captured before and after a disaster of the same area, segments the buildings, and evaluates the damage level of affected buildings. In addition, we calculate influence maps based on the damage scale to the building and estimate the damage situation for electrical facilities. We used images related to earthquakes and floods in the xBD dataset to train the network model. Moreover, qualitative and quantitative evaluations demonstrated that our method has higher accuracy than the xBD baseline. |
| first_indexed | 2024-04-14T00:38:45Z |
| format | Article |
| id | doaj.art-7574dec8de3242afa4069f36a7e05c71 |
| institution | Directory Open Access Journal |
| issn | 1682-1750 2194-9034 |
| language | English |
| last_indexed | 2024-04-14T00:38:45Z |
| publishDate | 2022-04-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-7574dec8de3242afa4069f36a7e05c712022-12-22T02:22:16ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342022-04-01XLVI-3-W1-202213314010.5194/isprs-archives-XLVI-3-W1-2022-133-2022ASSESSMENT OF BUILDINGS AND ELECTRICAL FACILITIES DAMAGED BY FLOOD AND EARTHQUAKE FROM SATELLITE IMAGERYY. Ma0F. Zhou1G. Wen2H. Gen3R. Huang4G. Liu5L. Pei6Electric Power Research Institute, Yunnan Power Grid Company ltd., Kunming, ChinaElectric Power Research Institute, Yunnan Power Grid Company ltd., Kunming, ChinaElectric Power Research Institute, Yunnan Power Grid Company ltd., Kunming, ChinaElectric Power Research Institute, Yunnan Power Grid Company ltd., Kunming, ChinaElectric Power Research Institute, Yunnan Power Grid Company ltd., Kunming, ChinaSchool of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, ChinaSchool of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, ChinaNatural disasters cause considerable losses to people’s lives and property. Satellite images can provide crucial information of the affected areas for the first time, conducive to relieving the people in disaster and reducing the economic loss. However, the traditional satellite image analysis method based on manual processing drains workforce and material resources, which slowed the government’s response to the disaster. Aiming at the natural disasters like floods and earthquakes that often happen in the south of China, we propose a dual-stage damage assessment method based on LEDNet and ResNet. Our method detects the changes between the satellite images captured before and after a disaster of the same area, segments the buildings, and evaluates the damage level of affected buildings. In addition, we calculate influence maps based on the damage scale to the building and estimate the damage situation for electrical facilities. We used images related to earthquakes and floods in the xBD dataset to train the network model. Moreover, qualitative and quantitative evaluations demonstrated that our method has higher accuracy than the xBD baseline.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLVI-3-W1-2022/133/2022/isprs-archives-XLVI-3-W1-2022-133-2022.pdf |
| spellingShingle | Y. Ma F. Zhou G. Wen H. Gen R. Huang G. Liu L. Pei ASSESSMENT OF BUILDINGS AND ELECTRICAL FACILITIES DAMAGED BY FLOOD AND EARTHQUAKE FROM SATELLITE IMAGERY The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | ASSESSMENT OF BUILDINGS AND ELECTRICAL FACILITIES DAMAGED BY FLOOD AND EARTHQUAKE FROM SATELLITE IMAGERY |
| title_full | ASSESSMENT OF BUILDINGS AND ELECTRICAL FACILITIES DAMAGED BY FLOOD AND EARTHQUAKE FROM SATELLITE IMAGERY |
| title_fullStr | ASSESSMENT OF BUILDINGS AND ELECTRICAL FACILITIES DAMAGED BY FLOOD AND EARTHQUAKE FROM SATELLITE IMAGERY |
| title_full_unstemmed | ASSESSMENT OF BUILDINGS AND ELECTRICAL FACILITIES DAMAGED BY FLOOD AND EARTHQUAKE FROM SATELLITE IMAGERY |
| title_short | ASSESSMENT OF BUILDINGS AND ELECTRICAL FACILITIES DAMAGED BY FLOOD AND EARTHQUAKE FROM SATELLITE IMAGERY |
| title_sort | assessment of buildings and electrical facilities damaged by flood and earthquake from satellite imagery |
| url | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLVI-3-W1-2022/133/2022/isprs-archives-XLVI-3-W1-2022-133-2022.pdf |
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