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Recently, a citizen science project called ForestWatchers [1] was launched in order to involve the citizens without experience in the monitoring of deforestation. Through a Web interface, volunteers from around the world are invited to review MODIS images of forest regions. Considering the large area worldwide covered by tropical forest, it is essential to use a fast classifier that meets a double objective: the pixel mapping into two classes (’Forest’ and ’Non-forest’) and the selection of pixels to be sent to volunteers for inspection. This project investigates the use the deforestation pattern classification in the Brazilian Amazon using MODIS images. Deforestation maps were generated from various sizes, from different areas of the state of Rondonia. The results were validated with the results of PRODES project, which annually evaluates deforestation in the Brazilian Amazon.

Image Classification using Neural Networks and Random Forest for a Citizen Science Project