Citizen science in support of remote sensing research

Remote sensing has much to gain from citizen sensing. This is particularly evident in relation to the provision of ground reference data for use in the training and testing stages of supervised image classification analyses used to generate thematic maps from remotely sensed data. Citizens are able to provide data over large geographical areas inexpensively, addressing potential problems connected with ground data samples and authoritative good practices. The great potential of citizen sensing is, however, constrained by concerns, notably with the quality of the data generated. This paper provides an overview of some of the key issues in citizen sensing to support thematic mapping from remote sensing. It highlights especially some of the ways that citizen sensing can aid remote sensing studies as a source of ground reference data.