Remote sensing and crowd-sourcing

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 crowd-sourcing 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.