气候变化领域集成服务门户(CCPortal): Building damage annotation on post-hurricane satellite imagery based on convolutional neural networks

CCPortal

DOI	10.1007/s11069-020-04133-2
	Building damage annotation on post-hurricane satellite imagery based on convolutional neural networks
	Cao Q.D.; Choe Y.
发表日期	2020
ISSN	0921030X
起始页码	3357
结束页码	3376
卷号	103 期号:3
英文摘要	After a hurricane, damage assessment is critical to emergency managers for efficient response and resource allocation. One way to gauge the damage extent is to quantify the number of flooded/damaged buildings, which is traditionally done by ground survey. This process can be labor-intensive and time-consuming. In this paper, we propose to improve the efficiency of building damage assessment by applying image classification algorithms to post-hurricane satellite imagery. At the known building coordinates (available from public data), we extract square-sized images from the satellite imagery to create training, validation, and test datasets. Each square-sized image contains a building to be classified as either ‘Flooded/Damaged’ (labeled by volunteers in a crowd-sourcing project) or ‘Undamaged’. We design and train a convolutional neural network from scratch and compare it with an existing neural network used widely for common object classification. We demonstrate the promise of our damage annotation model (over 97% accuracy) in the case study of building damage assessment in the Greater Houston area affected by 2017 Hurricane Harvey. © 2020, Springer Nature B.V.
关键词	Building Damage assessment Image classification Neural network Remote sensing
英文关键词	algorithm; artificial neural network; building; hurricane event; image classification; satellite imagery
语种	英语
来源期刊	Natural Hazards
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/205618
作者单位	Department of Industrial and Systems Engineering, University of Washington, 3900 E Stevens Way NE, Seattle, WA 98195, United States
推荐引用方式 GB/T 7714	Cao Q.D.,Choe Y.. Building damage annotation on post-hurricane satellite imagery based on convolutional neural networks[J],2020,103(3).
APA	Cao Q.D.,&Choe Y..(2020).Building damage annotation on post-hurricane satellite imagery based on convolutional neural networks.Natural Hazards,103(3).
MLA	Cao Q.D.,et al."Building damage annotation on post-hurricane satellite imagery based on convolutional neural networks".Natural Hazards 103.3(2020).