Measurement(s) wetness of soil Technology Type(s) machine learning Factor Type(s) soil layer • temporal interval • geographic location Sample Characteristic - Environment soil Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.1479051
Soil moisture mapping at a regional scale is commonplace since these data are required in many appli...
This study investigates the estimation of daily SSM using eight optimised ML algorithms and ten ense...
Annual soil moisture estimates are useful to characterize trends in the climate system, in the capac...
We use physics-informed machine learning to generate a global, long-term, spatially continuous high ...
Although soil moisture is a key factor of hydrologic and climate applications, global continuous hi...
The work presented looks at methods to model field measured spatio-temporal variations of soil moist...
This study presents machine learning-based approaches for understanding and predicting plot-scale so...
This study presents machine learning-based approaches for understanding and predicting plot-scale so...
The Committee on Earth Observation Satellites (CEOS) Land Product Validation (LPV) subgroup has been...
Summarization: The European Space Agency (ESA), through the Climate Change Initiative (CCI), is curr...
The work presented looks at methods to model field measured spatio-temporal variations of soil moist...
Soil moisture is one of the essential climate variables, and it controls the water, carbon, and ener...
SoMo.ml-EU provides high-resolution (0.1°) daily soil moisture data generated from machine learning ...
If given the correct remotely sensed information, machine learning can accurately describe soil mois...
SoMo.ml-EU provides high-resolution (0.1°) daily soil moisture data generated from machine learning ...
Soil moisture mapping at a regional scale is commonplace since these data are required in many appli...
This study investigates the estimation of daily SSM using eight optimised ML algorithms and ten ense...
Annual soil moisture estimates are useful to characterize trends in the climate system, in the capac...
We use physics-informed machine learning to generate a global, long-term, spatially continuous high ...
Although soil moisture is a key factor of hydrologic and climate applications, global continuous hi...
The work presented looks at methods to model field measured spatio-temporal variations of soil moist...
This study presents machine learning-based approaches for understanding and predicting plot-scale so...
This study presents machine learning-based approaches for understanding and predicting plot-scale so...
The Committee on Earth Observation Satellites (CEOS) Land Product Validation (LPV) subgroup has been...
Summarization: The European Space Agency (ESA), through the Climate Change Initiative (CCI), is curr...
The work presented looks at methods to model field measured spatio-temporal variations of soil moist...
Soil moisture is one of the essential climate variables, and it controls the water, carbon, and ener...
SoMo.ml-EU provides high-resolution (0.1°) daily soil moisture data generated from machine learning ...
If given the correct remotely sensed information, machine learning can accurately describe soil mois...
SoMo.ml-EU provides high-resolution (0.1°) daily soil moisture data generated from machine learning ...
Soil moisture mapping at a regional scale is commonplace since these data are required in many appli...
This study investigates the estimation of daily SSM using eight optimised ML algorithms and ten ense...
Annual soil moisture estimates are useful to characterize trends in the climate system, in the capac...