Robin van der Schalie
According to our database1,
Robin van der Schalie
authored at least 16 papers
between 2016 and 2024.
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Bibliography
2024
VODCA v2: Multi-sensor, multi-frequency vegetation optical depth data for long-term canopy dynamics and biomass monitoring.
Dataset, January, 2024
2023
Solutions for the commercialization challenges of Horizon Europe and earth observation consortia: co-creation, innovation, decision-making, tech-transfer, and sustainability actions.
Electron. Commer. Res., September, 2023
2022
Toward the Removal of Model Dependency in Soil Moisture Climate Data Records by Using an $L$-Band Scaling Reference.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022
Towards Consistent Soil Moisture Records from China's FengYun-3 Microwave Observations.
Remote. Sens., 2022
2021
L-Band Soil Moisture Retrievals Using Microwave Based Temperature and Filtering. Towards Model-Independent Climate Data Records.
Remote. Sens., 2021
Towards the Removal of Model Bias from ESA CCI SM by Using an L-Band Scaling Reference.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021
2020
Reconciling Flagging Strategies for Multi-Sensor Satellite Soil Moisture Climate Data Records.
Remote. Sens., 2020
2019
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019
2018
The Effect of Three Different Data Fusion Approaches on the Quality of Soil Moisture Retrievals from Multiple Passive Microwave Sensors.
Remote. Sens., 2018
Assessing the relationship between microwave vegetation optical depth and gross primary production.
Int. J. Appl. Earth Obs. Geoinformation, 2018
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018
Statistical Merging of Active and Passive Microwave Observations Into Long-Term Soil Moisture Climate Data Records.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018
2017
The Evaluation of Single-Sensor Surface Soil Moisture Anomalies over the Mainland of the People's Republic of China.
Remote. Sens., 2017
2016
Long Term Global Surface Soil Moisture Fields Using an SMOS-Trained Neural Network Applied to AMSR-E Data.
Remote. Sens., 2016
Int. J. Appl. Earth Obs. Geoinformation, 2016