| On the derivation of volume decorrelation from TanDEM-X bistatic coherence P Rizzoli, L Dell’Amore, JL Bueso-Bello, N Gollin, D Carcereri, M Martone IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2022 | 22 | 2022 |
| Deep learning for mapping tropical forests with TanDEM-X bistatic InSAR data JL Bueso-Bello, D Carcereri, M Martone, C González, P Posovszky, ... Remote Sensing 14 (16), 3981, 2022 | 11 | 2022 |
| A deep learning framework for the estimation of forest height from bistatic TanDEM-X data D Carcereri, P Rizzoli, D Ienco, L Bruzzone IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 | 8 | 2023 |
| Identification of non-photosynthetic vegetation areas in Sentinel-2 satellite image time series YT Solano-Correa, D Carcereri, F Bovolo, L Bruzzone Image and Signal Processing for Remote Sensing XXV 11155, 304-312, 2019 | 7 | 2019 |
| Advances in automatic InSAR-derived TanDEM-X DEM editing C Gonzalez, JLB Bello, N Gollin, D Carcereri, P Rizzoli, M Zink EUSAR 2022; 14th European Conference on Synthetic Aperture Radar, 1-6, 2022 | 2 | 2022 |
| Large scale forest parameter estimation through a deep learning-based fusion of sentinel-2 and tandem-x data D Carcereri, P Rizzoli, D Ienco, JL Bueso-Bello, C González, S Puliti, ... IGARSS 2022-2022 IEEE International Geoscience and Remote Sensing Symposium …, 2022 | 2 | 2022 |
| Potential of deep learning for forest height estimation from TanDEM-X bistatic InSAR data D Carcereri, P Rizzoli, D Ienco, L Bruzzone IGARSS 2023-2023 IEEE International Geoscience and Remote Sensing Symposium …, 2023 | 1 | 2023 |
| Large-scale precise mapping of agricultural fields in sentinel-2 satellite image time series YT Solano-Correa, D Carcereri, F Bovolo, L Bruzzone IGARSS 2020-2020 IEEE International Geoscience and Remote Sensing Symposium …, 2020 | 1 | 2020 |
| Generation of country-scale canopy height maps over Gabon using deep learning and TanDEM-X InSAR data D Carcereri, P Rizzoli, L Dell’Amore, JL Bueso-Bello, D Ienco, L Bruzzone Remote Sensing of Environment 311, 114270, 2024 | | 2024 |
| A Deep Learning Study on the Retrieval of Forest Parameters from Spaceborne Earth Observation Sensors D Carcereri Università degli studi di Trento, 2024 | | 2024 |
| Forest Mapping with Tandem-X Insar Data and Self-Supervised Learning JL Bueso-Bello, B Chauvel, D Carcereri, R Hänsch, P Rizzoli IGARSS 2024-2024 IEEE International Geoscience and Remote Sensing Symposium …, 2024 | | 2024 |
| Country-Scale Mapping of Forest Parameters Using Deep Learning and Tandem-X Insar Data D Carcereri, P Rizzoli, L Dell’Amore, JL Bueso-Bello, D Ienco, L Bruzzone IGARSS 2024-2024 IEEE International Geoscience and Remote Sensing Symposium …, 2024 | | 2024 |
| Deep Learning-based Approaches for Forest Mapping with TanDEM-X Interferometric Data JL Bueso-Bello, B Chauvel, D Carcereri, R Haensch, P Rizzoli EUSAR 2024; 15th European Conference on Synthetic Aperture Radar, 972-977, 2024 | | 2024 |
| A country-level deep-learning approach for canopy height estimation from TanDEM-X InSAR data D Carcereri, P Rizzoli, D Ienco, L Bruzzone EUSAR 2024; 15th European Conference on Synthetic Aperture Radar, 960-965, 2024 | | 2024 |
| Applications and challenges of deep learning approaches for forest height estimation from InSAR products D Carcereri, P Rizzoli, D Ienco, L Bruzzone | | 2023 |
| Sentinel-1 and TanDEM-X InSAR Coherence for Monitoring Forests Using Deep Learning P Rizzoli, R Dal Molin, D Carcereri, JL Bueso-Bello IGARSS 2023-2023 IEEE International Geoscience and Remote Sensing Symposium …, 2023 | | 2023 |
| Monitoring Forest Degradation in the Amazon Basin with Tandem-X High-Resolution Images and Deep Learning Techniques JL Bueso-Bello, R Dal Molin, D Carcereri, P Posovszky, C González, ... IGARSS 2023-2023 IEEE International Geoscience and Remote Sensing Symposium …, 2023 | | 2023 |
| A Deep Learning Approach for Forest Height Estimation using TanDEM-X D Carcereri, P Rizzoli, D Ienco, L Bruzzone Journal of Selected Topics in Applied Earth Observations and Remote Sensing …, 2023 | | 2023 |
| Forest Mapping with TanDEM-X and Deep Learning Approaches JL Bueso Bello, B Chauvel, D Carcereri, P Posovszky, C Gonzalez, ... | | 2023 |
| Deep Learning for forest height estimation from InSAR data: potential and challenges using TanDEM-X and Sentinel-1 data D Carcereri, P Rizzoli, D Ienco, L Bruzzone | | 2023 |
Paola RizzoliGerman Aerospace Center - DLR在 dlr.de 的电子邮件经过验证
