RSC4Earth
RSC4Earth
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Remote Sensing in Geo- and Ecosystem Research
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Remote Sensing Department at the UFZ
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Sebastian Semella
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Accuracy and Reproducibility of Laboratory Diffuse Reflectance Measurements with Portable VNIR and MIR Spectrometers for Predictive Soil Organic Carbon Modeling
A Machine Learning Framework for the Classification of Natura 2000 Habitat Types at Large Spatial Scales Using MODIS Surface Reflectance Data
Content of Soil Organic Carbon and Labile Fractions Depend on Local Combinations of Mineral-Phase Characteristics
Phosphorus Fractions and Speciation in Rural and Urban Calcareous Soils in the Semiarid Region of Sulaimani City, Kurdistan, Iraq
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