EVALUATION OF BURNT BUILDING DAMAGE USING SENTINEL-1 AND SENTINEL-2 DATA

被引:0
|
作者
Jung, Jungkyo [1 ]
Yun, Sang-Ho [1 ]
Xu, Jeri [2 ,3 ]
Xie, Boyi [2 ,3 ]
机构
[1] CALTECH, Jet Prop Lab, Pasadena, CA 91125 USA
[2] Swiss Re, Westlake Village, CA USA
[3] Swiss Re, Armonk, NY USA
关键词
Coherent change detection; Wildfire; Building damage; Normalized burn ratio; SAR; DECORRELATION; MODEL;
D O I
10.1109/IGARSS39084.2020.9324560
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Intensive wildfire is one of the catastrophic hazards threatening human life and the economy. In this study, we aim to detect building damage caused by the Camp Fire, which occurred in Paradise, California in 2018. We use multitemporal coherence based on C-band Sentinel-1 (SAR) and normalized burn ratio based on Sentinel-2 (multi-spectral) imagery. The results revealed that the multi-temporal coherence approach has the promising capability to map building damage but is not as accurate for detecting building damage under a vegetation canopy. Meanwhile, the normalized burn ratio (NBR) still provides meaningful damage maps independent of the canopy, however, the accuracy was slightly lower than the multi-temporal coherence approach for the buildings not covered by the canopy. Nonetheless, we observed that the multi-temporal coherence methods better classified the damage severity than the NBR method. Both methods can play a complementary role in responding to wildfire depending on the characteristics of the land cover.
引用
收藏
页码:6875 / 6878
页数:4
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