Tropical forests provide critical ecosystem services for climate and biodiversity and sustain the livelihoods of millions of people worldwide.  Yet, tropical forests also cover the last unexploited frontier lands that may be converted to agricultural production and so many tropical forest regions have become hotspots of land use change.  Perhaps the hottest of these spots for the past 40 years is the Brazilian Arc of Deforestation.  This region has been a focus of land development with large swaths of tropical forests converted to agriculture, including industrial commodity crops and pastures.  Degradation of forests by extensive selective logging and fires has accompanied the advance of the frontier and has resulted in significant impacts on ecosystem services.  While the deforestation and, to some extent, the agricultural use in the region are well quantified, the degradation of forests has been difficult to study.  In order to better understand this land use and land cover change hotspot, we propose to develop a multi-source land imaging approach to classify and map intact forests, second growth, forestry activities, and burned forests as well as agricultural and pastoral land uses. Our studies in the Brazilian Arc of Deforestation will combine multi-source land imaging — airborne lidar, commercial very high-resolution data, and moderate resolution optical and microwave data — with innovative machine learning algorithms for multi-data fusion classification. At the conclusion of the project, we will have classified maps of the region for at least eight annual intervals from 2007 through the present.  We will quantify the effects of distance from agricultural and pastoral land uses and time since forest conversion on the probability of forest degradation in the region and evaluate the impacts of forest degradation on the change in regional carbon stocks.  The importance of this research is underscored by the recent surge in deforestation in the Brazilian Amazon and associated forest degradation and fires.