Crowdsourcing earthquake damage assessment using remote sensing imagery
| Autor: | Albert Yu-Min Lin, Stuart P. D. Gill, Marjorie Greene, Jay Berger, Shay Har-Noy, Charles K. Huyck, Luke Barrington, Shubharoop Ghosh |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2011 |
| Předmět: |
Government
Computer science business.industry lcsh:QC801-809 Surveys measurements and monitoring Instruments and techniques Seismic risk Seismology Data dissemination generation or miscellaneous lcsh:QC851-999 Crowdsourcing Rapid assessment lcsh:Geophysics. Cosmic physics Geophysics Work (electrical) Remote sensing (archaeology) Satellite imagery lcsh:Meteorology. Climatology Seismic risk business Natural disaster Remote sensing |
| Zdroj: | Annals of Geophysics, Vol 54, Iss 6 (2011) |
| ISSN: | 1593-5213 |
| Popis: | This paper describes the evolution of recent work on using crowdsourced analysis of remote sensing imagery, particularly high-resolution aerial imagery, to provide rapid, reliable assessments of damage caused by earthquakes and potentially other disasters. The initial effort examined online imagery taken after the 2008 Wenchuan, China, earthquake. A more recent response to the 2010 Haiti earthquake led to the formation of an international consortium: the Global Earth Observation Catastrophe Assessment Network (GEO-CAN). The success of GEO-CAN in contributing to the official damage assessments made by the Government of Haiti, the United Nations, and the World Bank led to further development of a web-based interface. A current initiative in Christchurch, New Zealand, is underway where remote sensing experts are analyzing satellite imagery, geotechnical engineers are marking liquefaction areas, and structural engineers are identifying building damage. The current site includes online training to improve the accuracy of the assessments and make it possible for even novice users to contribute to the crowdsourced solution. The paper discusses lessons learned from these initiatives and presents a way forward for using crowdsourced remote sensing as a tool for rapid assessment of damage caused by natural disasters around the world. |
| Databáze: | OpenAIRE |
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