| 1 | Semantically enriched crop type classification and linked earth observation data to support the common agricultural policy monitoring | 2020 | 27 | |
| 2 | Assessing the added value of Sentinel-1 PolSAR data for crop classification | 2022 | 19 | |
| 3 | A Scalable Machine Learning Pipeline for Paddy Rice Classification Using Multi-Temporal Sentinel Data | 2021 | 19 | |
| 4 | A scalable machine learning pipeline for paddy rice classification using multi-temporal sentinel data | 2021 | 19 | |
| 5 | Evaluating digital agriculture recommendations with causal inference | 2023 | 15 | |
| 6 | Evaluating Digital Agriculture Recommendations with Causal Inference | 2022 | 15 | |
| 7 | Towards space-to-ground data availability for agriculture monitoring | 2022 | 11 | |
| 8 | Scalable distributed random forest classification for paddy rice mapping | 2020 | 11 | |
| 9 | Scalable distributed random forest classification for paddy rice mapping Asian conference on remote sensing ACRS 2019 | 2019 | 11 | |
| 10 | Fuzzy clustering for the within-season estimation of cotton phenology | 2022 | 10 | |
| 11 | A Sentinel based agriculture monitoring scheme for the control of the CAP and food security | 2021 | 9 | |
| 12 | A sentinel based agriculture monitoring scheme for the control of the cap and food security | 2020 | 9 | |
| 13 | Recurrent U-Net based dynamic paddy rice mapping in South Korea with enhanced data compatibility to support agricultural decision making | 2023 | 6 | |
| 14 | Evaluating digital tools for sustainable agriculture using causal inference | 2022 | 6 | |
| 15 | Datacap: A satellite datacube and crowdsourced street-level images for the monitoring of the common agricultural policy | 2022 | 5 | |
| 16 | A data cube of big satellite image time-series for agriculture monitoring | 2022 | 5 | |
| 17 | Towards Space-to-Ground Data Availability for Agriculture Monitoring | 2022 | 5 | |
| 18 | Semi-supervised phenology estimation in cotton parcels with sentinel-2 time-series | 2021 | 5 | |
| 19 | A Data Cube of Big Satellite Image Time-Series for Agriculture Monitoring | 2022 | 4 | |
| 20 | Towards Global Crop Maps with Transfer Learning | 2022 | 4 | |
| 21 | Towards global crop maps with transfer learning | 2022 | 4 | |
| 22 | Semi-Supervised Phenology Estimation in Cotton Parcels with Sentinel-2 Time-Series | 2021 | 3 | |
| 23 | Fast Fusion of Sentinel-2 and Sentinel-3 Time Series over Rangelands | 2024 | 2 | |
| 24 | Assessing the Added Value of Sentinel-1 PolSAR Data for Crop Classification | 2022 | 2 | |
| 25 | Evaluating Digital Tools for Sustainable Agriculture using Causal Inference | 2022 | 1 | |
| 26 | Cloud gap-filling with deep learning for improved grassland monitoring | 2024 | 0 | |
| 27 | Deep Learning for Event Detection on Grasslands | 2021 | 0 | |
| 28 | Paddyr rice mapping based on multi-temporal sentinel-1 and sentinel-2 data in a high performance data analytics environment | 2021 | 0 | |
| 29 | A Novel Approach on Smart Farming: Combining Past, Present and Future EO, Climatic and NWP datasets Towards an Integrated Crop Monitoring, Risk-Assessment and Yield Forecasting … | 2020 | 0 | |
| 30 | SCALABLE DISTRIBUTED RANDOM FOREST CLASSIFICATION FOR PADDY RICE MAPPING ASIAN CONFERENCE ON REMOTE SENSING ACRS 2019 | -1 | 0 | |