The Development and Uses of Crowdsourced Building Damage Information based on Remote-Sensing
Abstract/Contents
- Abstract
Crowdsourced analysis of satellite and aerial imagery has emerged as a new mechanism to assess post-disaster impact in the past decade. Compared to standard ground-based damage assessments, crowdsourcing initiatives rapidly process extensive data over a large spatial extent and can inform many important emergency response and recovery decisions. We test three approaches to crowdsourcing post-earthquake building damage using 50cm resolution satellite imagery from the 2010 Haiti earthquake. Approach 1 further develops the predominant building-level map-based assessment method that has been implemented in earlier crowdsourcing initiatives. Two novel area-based assessment approaches were also developed, where users rate the level of build-ing damage in an image (Approach 2) and compare building damage between two images (Approach 3). The results of the two area-based approaches show a trend between crowdsourced and "true" field damage severity, which can be improved by weighting high-performing volunteers. Alternative methods, including Bayesian updating and network analysis, are proposed to analyze the paired comparison data from Approach 3. However, Approach 1 did not reach completion, because of the time intensive nature of building-level assessments.
Parallel to the crowdsourcing tests, an extensive ’demand survey’ of interviews with post-disaster practitioners was conducted to develop a timeline of six key decisions that are dependent on post-earthquake building damage data. The resulting framework can guide future research concerning rapid damage estimates to address decision-makers’ specific, and cross-cutting needs. Considering the results of the crowdsourcing tests and the demand survey, area-based approaches are promising methods to crowdsource building damage, because of its user-simplicity and ability to address specific post-disaster decisions.
Description
Type of resource | text |
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Date created | December 2018 |
Creators/Contributors
Author | Loos, S | |
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Author | Barns, K | |
Author | Bhattacharjee, G | |
Author | Soden, R | |
Author | Herfort, B | |
Author | Eckle, M | |
Author | Giovando, C | |
Author | Girardot, B | |
Author | Deierlein, G | |
Author | Kiremidjian, A | |
Author | Baker, J | |
Author | Lallemant, D |
Subjects
Subject | post-disaster |
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Subject | damage estimation |
Subject | crowdsource |
Subject | Civil & Environmental Engineering |
Subject | Stanford School of Engineering |
Subject | Structural Engineering & Geomechanics |
Subject | Blume Earthquake Engineering Center |
Subject | Stanford Urban Resilience Initiative |
Subject | remote sensing |
Subject | building damage |
Genre | Technical report |
Bibliographic information
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- User agrees that, where applicable, content will not be used to identify or to otherwise infringe the privacy or confidentiality rights of individuals. Content distributed via the Stanford Digital Repository may be subject to additional license and use restrictions applied by the depositor.
- License
- This work is licensed under a Creative Commons Attribution 3.0 Unported license (CC BY).
Preferred citation
- Preferred Citation
- Loos, S and Barns, K and Bhattacharjee, G and Soden, R and Herfort, B and Eckle, M and Giovando, C and Girardot, B and Deierlein, G and Kiremidjian, A and Baker, J and Lallemant, D. (2018). The Development and Uses of Crowdsourced Building Damage Information based on Remote-Sensing. Blume Earthquake Engineering Center Technical Report 197. Stanford Digital Repository. Available at: https://purl.stanford.edu/bj915mt6570
Collection
John A. Blume Earthquake Engineering Center Technical Report Series
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- jabeec-email@stanford.edu
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