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Meteosat Land Surface Temperature Climate Data Record: Achievable Accuracy and Potential Uncertainties.

, , , , , , , , , and . Remote. Sens., 7 (10): 13139-13156 (2015)

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Quantifying solar radiation at the earth surface with meteorological and satellite data.. University of Twente Faculty of Geo-Information and Earth Observation (ITC), P.O. Box 217, 7500 AE Enschede, The Netherlands, (January 2014)Cloud Detection with Historical Geostationary Satellite Sensors for Climate Applications., , , , , , and . Remote. Sens., 11 (9): 1052 (2019)Meteosat Land Surface Temperature Climate Data Record: Achievable Accuracy and Potential Uncertainties., , , , , , , , , and . Remote. Sens., 7 (10): 13139-13156 (2015)An auto-calibration procedure for empirical solar radiation models., , , and . Environ. Model. Softw., (2013)Performance Assessment of the COMET Cloud Fractional Cover Climatology across Meteosat Generations., , , , and . Remote Sensing, 10 (5): 804 (2018)Multi-temporal phenological indices derived from time series Sentinel-1 images to country-wide crop classification., , , , , , , , , and 1 other author(s). Int. J. Appl. Earth Obs. Geoinformation, (2022)Calibration of solar radiation models for Europe using Meteosat Second Generation and weather station data, , and . Agricultural and Forest Meteorology, (July 2013)The Impact of Time Difference between Satellite Overpass and Ground Observation on Cloud Cover Performance Statistics., , , and . Remote Sensing, 6 (12): 12866-12884 (2014)A comparison of data sources for creating a long-term time series of daily gridded solar radiation for Europe, , and . Solar Energy, (January 2014)Integration of Sentinel-3 and MODIS Vegetation Indices with ERA-5 Agro-Meteorological Indicators for Operational Crop Yield Forecasting., , , , , , , and . Remote. Sens., 14 (5): 1238 (2022)