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A Semiempirical Approach for Decomposition of Remotely Sensed Leaf Area Index Into Overstory and Understory Components Over Russian Forests., , , , , , , and . IEEE Trans. Geosci. Remote. Sens., (2023)Use of data from the VEGETATION instrument for global environmental monitoring: some lessons from the GLC 2000 and the GBA 2000 projects., , , , , , , , , and 1 other author(s). IGARSS, page 576-578. IEEE, (2003)Climate, vegetation phenology and forest fires in Siberia., , , , , , , and . IGARSS, page 3843-3846. IEEE, (2007)Estimation of Boreal Forest Growing Stock Volume in Russia from Sentinel-2 MSI and Land Cover Classification., , , , and . Remote. Sens., 13 (21): 4483 (2021)A Unified Cropland Layer at 250 m for Global Agriculture Monitoring., , , , , , , , , and 6 other author(s). Data, 1 (1): 3 (2016)Usage Experience and Capabilities of the VEGA-Science System., , , , , , , , , and 1 other author(s). Remote. Sens., 14 (1): 77 (2022)Utility of Leaf Area Index for Monitoring Phenology of Russian Forests., , , , and . Remote. Sens., 15 (22): 5419 (November 2023)Roadside collection of training data for cropland mapping is viable when environmental and management gradients are surveyed., , , , , , , , , and 3 other author(s). Int. J. Appl. Earth Obs. Geoinformation, (2019)Assessment and monitoring of Siberian forest resources in the framework of the EU-Russia ZAPÁS project., , , , , , , and . IGARSS, page 7208-7211. IEEE, (2012)