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Collection of ground truth to validate remote sensing classification and/or detection algorithms is rarely accounted for due to the inaccessibility of the sites or the elevated costs of such operations. In this paper some of the opportunities behind crowdsourcing are explored through the description of a remote sensing project on water quality monitoring in Africa where the ground truth was collected involving and training people from local communities. Index Terms-water quality, crowd-sourcing.doi:10.1109/igarss.2013.6723695 dblp:conf/igarss/GuidaBK13 fatcat:3v2nogt7tfal7mbrp2q6trll2i