This study explores the performance of GEOCAN, a remote-sensing and crowdsourcing platform for assessing earthquake damage, by using geo-referenced ground-based damage assessments. This paper discusses methods for the application of remote sensing in post-earthquake damage assessment and reports on a GEOCAN crowd-sourcing study following the 22 February 2011 Christchurch event and its validation using field studies. It describes the principal data sets used, discusses in detail the problems of validation, and considers the extent of omission and commission errors. It is clear that although commission errors in the GEOCAN damage estimation are low, the omission error is significant (64%); the extent of these and the causal factors are analyzed with a decision model. The results show that the image-based analysis in this case does not reproduce the spatial pattern or magnitude of the damage impact. Finally, recommendations to improve the performance of GEOCAN in subsequent deployments are made.
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