Storm surge damage interpretation by satellite imagery: case review

Xunan Liu, Yao Zhang (), Chenbin Liang, Yayu Yang, Wanru Huang, Ning Jia and Bo Cheng
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Xunan Liu: Ministry of Natural Resources
Yao Zhang: Ministry of Natural Resources
Chenbin Liang: Chinese Academy of Sciences
Yayu Yang: Ministry of Natural Resources
Wanru Huang: Ministry of Natural Resources
Ning Jia: Ministry of Natural Resources
Bo Cheng: Chinese Academy of Sciences

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2022, vol. 112, issue 1, No 15, 349-365

Abstract: Abstract Rapid response and restoration after storm surge events are critical for the resilient development of coastal areas. Remote sensing has become a practical tool for postdisaster impact assessment since the modern satellite era. This paper presents the methodology and case review of damage detection using high-resolution satellite imagery for vulnerable targets with limited accessibility on land or water during China’s recent typhoon landfalls. Multiple sources of remotely sensed data are acquired and processed in a broad geographic scope. The study demonstrates how storm damage may be explicitly revealed by interpreting the texture difference or reflectance spectrum contrast for various target types, including flotation facilities, green vegetation, sandy coast and coastal protections. The damage state in the same area may show rapid variations in space due to local differences in the shielding effectiveness with respect to the storm track. The technical features, advantages, and drawbacks of remote sensing applications to marine disaster assessment are discussed from a future perspective. The study results provide a comprehensive reference to better integrate satellite observations into postdisaster surveys, vulnerability analyses, and risk predictions for coastal communities that will withstand future marine hazards.

Keywords: Storm surge; Damage assessment; Remote sensing; NDVI; Texture extraction (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s11069-021-05184-9

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