Principal Investigator: Matthew Hansen Co Investigators: Peter Potapov Sponsor: Gordon and Betty Moore Foundation Time Period: 2016 to 2018 Researchers: Bernard AduseiXiao-Peng SongViviana ZallesAndrés Hernández Serna Abstract Long-term earth observation data, specifically Landsat imagery, offer the possibility of quantifying deforestation rates and the resultant land uses that replace cleared natural forests. Our ability to track the evolution of human economic activity on tropical forest landscapes has improved due to recent advances in 1) data policies making Landsat data freely available, 2) advanced high performance computing and 3) methods for accurate processing and characterization of land cover and land use. The most consistent record of Landsat imagery starts in the early 1980s with the Landsat 4 and 5 Thematic Mapper sensors through the currently operating Landsat 7 Enhanced Thematic Mapper Plus and Landsat 8 Operational Land Imager. The main objective of the proposed activity is to map South American agricultural evolution by commodity during this period of data collection. As cropland, pasture and forestry land uses expand, natural land covers or antecedent agricultural or other land uses, are converted. Accurate measurement of the spatio-temporal trends of these conversions is a critical input to analyses of domestic and international commodity flows and their respective drivers. Starting in ~1985, we will map natural land cover and human land use at a 30m spatial resolution on an annual basis. Natural land covers will include themes such as humid tropical forest, dry tropical forest and woodland, and grasslands. Wetland status will also be defined as a generic overlay. For human land use, we will focus on commodity croplands including soybean and other crops, pasture for beef production, forestry, and palm oil. Land associated with each commodity will be characterized and a matrix of conversion covering the from-to dynamics created for the 30+ year study period. Near doubling of Brazil’s cropland area since 2000 Related Publications: Song, X.-P., Hansen, M.C., Potapov, P., Adusei, B., Pickering, J., Adami, M., Lima, A., Zalles, V., Stehman, S.V., Di Bella, C.M., Cecilia, C.M., Copati, E.J., Fernandes, L.B., Hernandez-Serna, A., Jantz, S.M., Pickens, A.H., Turubanova, S., Tyukavina A. (2021). Massive soybean expansion in South America since 2000 and implications for conservation. Nature Sustainability, 4, 784–792 Zalles, V., Hansen, M.C., Potapov, P.V., Stehman, S.V., Tyukavina, A., Pickens, A., Song, X.P., Adusei, B., Okpa, C., Aguilar, R. and John, N. (2019) Near doubling of Brazil’s intensive row crop area since 2000. Proceedings of the National Academy of Sciences, 116 (2) 428-435. King, L., Adusei, B., Stehman, S.V., Potapov, P.V., Song, X.P., Krylov, A., Di Bella, C., Loveland, T.R., Johnson, D.M., Hansen, M.C. (2017) A multi-resolution approach to national-scale cultivated area estimation of soybean. Remote Sensing of Environment, vol. 195, pp. 13-29. Tyukavina, A., Hansen, M.C., Potapov, P.V., Stehman, S.V., Smith-Rodriguez, K., Okpa, C., Aguilar, R. (2017) Types and rates of forest disturbance in Brazilian Legal Amazon, 2000–2013. Science Advances, vol. 3, no. 4 Related Projects: Advancing Methods for Global Crop Area Estimation Agricultural Information Systems Project Building Provincial Capacity for Crop Estimation and Forecasting in Pakistan Agricultural Monitoring in Tanazania and Uganda for Food Security Global Cropland Extent