气候变化领域集成服务门户(CCPortal): Low-cost UAV surveys of hurricane damage in Dominica: automated processing with co-registration of pre-hurricane imagery for change analysis

CCPortal

DOI	10.1007/s11069-020-03893-1
	Low-cost UAV surveys of hurricane damage in Dominica: automated processing with co-registration of pre-hurricane imagery for change analysis
	Schaefer M.; Teeuw R.; Day S.; Zekkos D.; Weber P.; Meredith T.; van Westen C.J.
发表日期	2020
ISSN	0921030X
起始页码	755
结束页码	784
卷号	101 期号:3
英文摘要	In 2017, hurricane Maria caused unprecedented damage and fatalities on the Caribbean island of Dominica. In order to ‘build back better’ and to learn from the processes causing the damage, it is important to quickly document, evaluate and map changes, both in Dominica and in other high-risk countries. This paper presents an innovative and relatively low-cost and rapid workflow for accurately quantifying geomorphological changes in the aftermath of a natural disaster. We used unmanned aerial vehicle (UAV) surveys to collect aerial imagery from 44 hurricane-affected key sites on Dominica. We processed the imagery using structure from motion (SfM) as well as a purpose-built Python script for automated processing, enabling rapid data turnaround. We also compared the data to an earlier UAV survey undertaken shortly before hurricane Maria and established ways to co-register the imagery, in order to provide accurate change detection data sets. Consequently, our approach has had to differ considerably from the previous studies that have assessed the accuracy of UAV-derived data in relatively undisturbed settings. This study therefore provides an original contribution to UAV-based research, outlining a robust aerial methodology that is potentially of great value to post-disaster damage surveys and geomorphological change analysis. Our findings can be used (1) to utilise UAV in post-disaster change assessments; (2) to establish ground control points that enable before-and-after change analysis; and (3) to provide baseline data reference points in areas that might undergo future change. We recommend that countries which are at high risk from natural disasters develop capacity for low-cost UAV surveys, building teams that can create pre-disaster baseline surveys, respond within a few hours of a local disaster event and provide aerial photography of use for the damage assessments carried out by local and incoming disaster response teams. © 2020, The Author(s).
关键词	Change analysis Damage assessment Disaster response Hurricane Image co-registration Structure from motion (SfM)UAV
英文关键词	aerial photography; data set; geomorphology; hurricane; image analysis; imagery; natural disaster; quantitative analysis; unmanned vehicle; Dominica; Leeward Islands [Lesser Antilles]
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/205926
作者单位	School of the Environment, Geography and Geosciences, University of Portsmouth, Buckingham Building, Lion Terrace, Portsmouth, PO1 3HE, United Kingdom; School of the Environment, Geography and Geosciences, University of Portsmouth, Burnaby Building, Burnaby Road, Portsmouth, PO1 3QL, United Kingdom; Faculty of Maths and Physical Sciences, Institute for Risk and Disaster Reduction, University College London, London, United Kingdom; Department of Civil and Environmental Engineering, University of California at Berkeley, Davis Hall, Berkeley, CA 94556, United States; Faculty of Creative and Cultural Industries, University of Portsmouth, Eldon Building, Winston Churchill Avenue, Portsmouth, PO1 2DJ, United Kingdom; Department of Earth Systems Analysis, University of Twente, Enschede, Netherlands
推荐引用方式 GB/T 7714	Schaefer M.,Teeuw R.,Day S.,et al. Low-cost UAV surveys of hurricane damage in Dominica: automated processing with co-registration of pre-hurricane imagery for change analysis[J],2020,101(3).
APA	Schaefer M..,Teeuw R..,Day S..,Zekkos D..,Weber P..,...&van Westen C.J..(2020).Low-cost UAV surveys of hurricane damage in Dominica: automated processing with co-registration of pre-hurricane imagery for change analysis.Natural Hazards,101(3).
MLA	Schaefer M.,et al."Low-cost UAV surveys of hurricane damage in Dominica: automated processing with co-registration of pre-hurricane imagery for change analysis".Natural Hazards 101.3(2020).