Cloud-Sourcing: Using an Online Labor Force to Detect Clouds and Cloud Shadows in Landsat Images

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dc.contributor.authorYu, Lingen
dc.contributor.authorBall, Sheryl B.en
dc.contributor.authorBlinn, Christine E.en
dc.contributor.authorMoeltner, Klausen
dc.contributor.authorPeery, Sethen
dc.contributor.authorThomas, Valerie A.en
dc.contributor.authorWynne, Randolph H.en
dc.contributor.departmentAgricultural and Applied Economicsen
dc.contributor.departmentEconomicsen
dc.contributor.departmentForest Resources and Environmental Conservationen
dc.date.accessioned2017-09-20T18:21:41Zen
dc.date.available2017-09-20T18:21:41Zen
dc.date.issued2015-02-26en
dc.date.updated2017-09-20T18:21:41Zen
dc.description.abstractWe recruit an online labor force through Amazon.com’s Mechanical Turk platform to identify clouds and cloud shadows in Landsat satellite images. We find that a large group of workers can be mobilized quickly and relatively inexpensively. Our results indicate that workers’ accuracy is insensitive to wage, but deteriorates with the complexity of images and with time-on-task. In most instances, human interpretation of cloud impacted area using a majority rule was more accurate than an automated algorithm (Fmask) commonly used to identify clouds and cloud shadows. However, cirrus-impacted pixels were better identified by Fmask than by human interpreters. Crowd-sourced interpretation of cloud impacted pixels appears to be a promising means by which to augment or potentially validate fully automated algorithms.en
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationYu, L.; Ball, S.B.; Blinn, C.E.; Moeltner, K.; Peery, S.; Thomas, V.A.; Wynne, R.H. Cloud-Sourcing: Using an Online Labor Force to Detect Clouds and Cloud Shadows in Landsat Images. Remote Sens. 2015, 7, 2334-2351.en
dc.identifier.doihttps://doi.org/10.3390/rs70302334en
dc.identifier.urihttp://hdl.handle.net/10919/79232en
dc.language.isoenen
dc.publisherMDPIen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectcloud interpretationen
dc.subjectsatellite imagesen
dc.subjectMechanical Turken
dc.subjecteconomic experimenten
dc.titleCloud-Sourcing: Using an Online Labor Force to Detect Clouds and Cloud Shadows in Landsat Imagesen
dc.title.serialRemote Sensingen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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