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Carcereri, Daniel and Rizzoli, Paola and Ienco, Dino and Bruzzone, Lorenzo (2024) A country-level deep-learning approach for canopy height estimation from TanDEM-X InSAR data. In: Proceedings of the European Conference on Synthetic Aperture Radar, EUSAR. European Conference on Synthetic Aperture Radar (EUSAR), 2024-04-23 - 2024-04-26, Munich, Germany. ISSN 2197-4403.
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| Item URL in elib: | https://elib.dlr.de/197678/ | ||||||||||||||||||||
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| Document Type: | Conference or Workshop Item (Speech) | ||||||||||||||||||||
| Title: | A country-level deep-learning approach for canopy height estimation from TanDEM-X InSAR data | ||||||||||||||||||||
| Authors: |
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| Date: | 2024 | ||||||||||||||||||||
| Journal or Publication Title: | Proceedings of the European Conference on Synthetic Aperture Radar, EUSAR | ||||||||||||||||||||
| Refereed publication: | Yes | ||||||||||||||||||||
| Open Access: | Yes | ||||||||||||||||||||
| Gold Open Access: | No | ||||||||||||||||||||
| In SCOPUS: | Yes | ||||||||||||||||||||
| In ISI Web of Science: | No | ||||||||||||||||||||
| ISSN: | 2197-4403 | ||||||||||||||||||||
| Status: | Published | ||||||||||||||||||||
| Keywords: | bistatic coherence, convolutional neural network, deep learning, forest height, synthetic aperture radar, synthetic aperture radar interferometry, TanDEM-X | ||||||||||||||||||||
| Event Title: | European Conference on Synthetic Aperture Radar (EUSAR) | ||||||||||||||||||||
| Event Location: | Munich, Germany | ||||||||||||||||||||
| Event Type: | international Conference | ||||||||||||||||||||
| Event Start Date: | 23 April 2024 | ||||||||||||||||||||
| Event End Date: | 26 April 2024 | ||||||||||||||||||||
| Organizer: | VDE | ||||||||||||||||||||
| HGF - Research field: | Aeronautics, Space and Transport | ||||||||||||||||||||
| HGF - Program: | Space | ||||||||||||||||||||
| HGF - Program Themes: | Earth Observation | ||||||||||||||||||||
| DLR - Research area: | Raumfahrt | ||||||||||||||||||||
| DLR - Program: | R EO - Earth Observation | ||||||||||||||||||||
| DLR - Research theme (Project): | R - AI4SAR | ||||||||||||||||||||
| Location: | Oberpfaffenhofen | ||||||||||||||||||||
| Institutes and Institutions: | Microwaves and Radar Institute Microwaves and Radar Institute > Spaceborne SAR Systems | ||||||||||||||||||||
| Deposited By: | Carcereri, Daniel | ||||||||||||||||||||
| Deposited On: | 09 Oct 2023 08:41 | ||||||||||||||||||||
| Last Modified: | 30 Jan 2025 17:42 |
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