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- Read more about Hansen, M.C., Wang, L., Song, X.-P., Tyukavina, A., Turubanova, S., Potapov, P.V., & Stehman, S.V. (2020). The fate of tropical forest fragments. Science Advances, 6, eaax8574
- Read more about Huang, N., Wang, L., Song, X.-P., Black, T.A., Jassal, R.S., Myneni, R.B., (2020). Spatial and temporal variations in global soil respiration and their relationships with climate and land cover. Science Advances, 6, eabb8508
- Read more about Tong, X., Brandt, M., Yue, Y., Ciais, P., Rudbeck Jepsen, M., Penuelas, J., Wigneron, J.P., Xiao, X., Song, X.P.. (2020). Forest management in southern China generates short term extensive carbon sequestration. Nat Commun, 11, 129
- Read more about Cropper, M., Cui, R., Guttikunda, S., Hultman, N., Jawahar, P., Park, Y., Yao, X., & Song, X.-P. (2021). The mortality impacts of current and planned coal-fired power plants in India. Proceedings of the National Academy of Sciences, 118, e2017936118
- Read more about Potapov, P., Turubanova, S., Hansen, M.C., Tyukavina, A., Zalles, V., Khan, A., Song, X.-P., Pickens, A., Shen, Q., & Cortez, J. (2021). Global maps of cropland extent and change show accelerated cropland expansion in the twenty-first century. Nature Food
- Read more about Song, X.-P., Hansen, M.C., Potapov, P.V., Adusei, B., Pickering, J., Adami, M., Lima, A., Zalles, V., Stehman, S.V., (2021). Massive soybean expansion in South America since 2000 and implications for conservation. Nature Sustainability, 4, 784-792
- Read more about Song, X.-P., Huang, W., Hansen, M.C., & Potapov, P. (2021). An evaluation of Landsat, Sentinel-2, Sentinel-1 and MODIS data for crop type mapping. Science of Remote Sensing, 3, 100018
- Read more about Li, X.-Y., Li, X., Fan, Z., Mi, L., Kandakji, T., Song, Z., Li, D., & Song, X.-P. (2022). Civil war hinders crop production and threatens food security in Syria. Nature Food, 3, 38-46
- Read more about Song, X.-P., Li, H., Potapov, P., & Hansen, M.C. (2022). Annual 30 m soybean yield mapping in Brazil using long-term satellite observations, climate data and machine learning. Agricultural and Forest Meteorology, 326, 109186
