{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T03:50:12Z","timestamp":1771905012447,"version":"3.50.1"},"reference-count":21,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2016,9,14]],"date-time":"2016-09-14T00:00:00Z","timestamp":1473811200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Remote sensing (RS) images play a significant role in disaster emergency response. Web2.0 changes the way data are created, making it possible for the public to participate in scientific issues. In this paper, an experiment is designed to evaluate the reliability of crowdsourcing buildings collapse assessment in the early time after an earthquake based on aerial remote sensing image. The procedure of RS data pre-processing and crowdsourcing data collection is presented. A probabilistic model including maximum likelihood estimation (MLE), Bayes\u2019 theorem and expectation-maximization (EM) algorithm are applied to quantitatively estimate the individual error-rate and \u201cground truth\u201d according to multiple participants\u2019 assessment results. An experimental area of Yushu earthquake is provided to present the results contributed by participants. Following the results, some discussion is provided regarding accuracy and variation among participants. The features of buildings labeled as the same damage type are found highly consistent. This suggests that the building damage assessment contributed by crowdsourcing can be treated as reliable samples. This study shows potential for a rapid building collapse assessment through crowdsourcing and quantitatively inferring \u201cground truth\u201d according to crowdsourcing data in the early time after the earthquake based on aerial remote sensing image.<\/jats:p>","DOI":"10.3390\/rs8090759","type":"journal-article","created":{"date-parts":[[2016,9,14]],"date-time":"2016-09-14T10:45:00Z","timestamp":1473849900000},"page":"759","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":36,"title":["Crowdsourcing Rapid Assessment of Collapsed Buildings Early after the Earthquake Based on Aerial Remote Sensing Image: A Case Study of Yushu Earthquake"],"prefix":"10.3390","volume":"8","author":[{"given":"Shuai","family":"Xie","sequence":"first","affiliation":[{"name":"Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Jianbo","family":"Duan","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China"}]},{"given":"Shibin","family":"Liu","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China"}]},{"given":"Qin","family":"Dai","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China"}]},{"given":"Wei","family":"Liu","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China"}]},{"given":"Yong","family":"Ma","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0659-4025","authenticated-orcid":false,"given":"Rui","family":"Guo","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China"}]},{"given":"Caihong","family":"Ma","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China"}]}],"member":"1968","published-online":{"date-parts":[[2016,9,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1553","DOI":"10.1193\/121812EQS350M","article-title":"Assessment of seismic building vulnerability from space","volume":"30","author":"Tyagunov","year":"2014","journal-title":"Earthq. 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