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TomoSense: A unique 3D dataset over temperate forest combining multi-frequency mono- and bi-static tomographic SAR with terrestrial, UAV and airborne lidar, and in-situ forest census

Stefano Tebaldini, Mauro Mariotti d’Alessandro, Lars M. H. Ulander, Patrik J. Bennet, Anders Gustavsson, Alex Coccia, Karlus A. C. de Macedo, Mathias Disney, Phil Wilkes, Hans-Joachim Spors, Nico Schumacher, Jan Hanuš, Jan Novotný, Benjamin Brede, Harm Bartholomeus, Alvaro Lau, Jens van der Zee, Martin Herold, Dirk Schuettemeyer, Klaus Scipal

2023Remote Sensing of Environment42 citationsDOIOpen Access PDF

Topics & Concepts

Remote sensingLidarTree canopySynthetic aperture radarCanopyEnvironmental scienceForest inventoryAerial surveyTemperate rainforestVegetation (pathology)Data setScale (ratio)Forest managementGeographyComputer scienceCartographyEcologyArtificial intelligenceEcosystemArchaeologyBiologyMedicinePathologyAgroforestryRemote Sensing and LiDAR ApplicationsSynthetic Aperture Radar (SAR) Applications and TechniquesLandslides and related hazards
TomoSense: A unique 3D dataset over temperate forest combining multi-frequency mono- and bi-static tomographic SAR with terrestrial, UAV and airborne lidar, and in-situ forest census | Litcius