Since the early 2000s, crowdsourced analysis of satellite and aerial imagery has been tested as a way to rapidly determine areas with building damage after major disasters. Compared to traditional field-based damage assessments, crowdsourcing initiatives rapidly process extensive data over a large spatial extent and can inform many important emergency response and recovery decisions.
As a collaborative project between the Stanford Urban Resilience Inititative, Heidelberg University, The World Bank, and Humanitarian OpenStreetMap Team, we tested test three approaches to crowdsourcing post-earthquake building damage using 50cm resolution satellite imagery from the 2010 Haiti earthquake. We also interviewed disaster responders about how they might use this information after a disaster.
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Through interviews and a questionnaire with damage information users and providers, this paper characterizes six post-disaster tasks that rely on building damage data and the factors, such as trust and sharing barriers, that shape its use.
Factors affecting earthquake responders’ building damage information needs and use
An overview of the development of using remote sensing for crowdsourcec building damage assessment and an evaluation of the uses of this information.
The Development and Uses of Crowdsourced Building Damage Information based on Remote-Sensing
Comparing three approaches to crowdsource building damage information using satellite imagery after a disaster.
Crowd-sourced remote assessments of regional-scale post-disaster damage
Using the 2015 Gorkha earthquake as a case study, this paper examines the types and purposes of post-disaster damage assessments and argues they should be tailored to the diverse, evolving information needs of different users.
Post-Disaster Damage Assessments as Catalysts for Recovery: A Look at Assessments Conducted in the Wake of the 2015 Gorkha, Nepal, Earthquake
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