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
Journal article, 2023
The TomoSense experiment was funded by the European Space Agency (ESA) to support research on remote sensing of forested areas by means of Synthetic Aperture Radar (SAR) data, with a special focus on the use of tomographic SAR (TomoSAR) to retrieve information about the vertical structure of the vegetation at different frequency bands. The illuminated scene is the temperate forest at the Eifel National Park, North-West Germany. Dominant species are beech and spruce trees. Forest height ranges roughly from 10 to 30 m, with peaks up to over 40 m. Forest Above Ground Biomass (AGB) ranges from 20 to 300 Mg/ha, with peaks up to over 400 Mg/ha. SAR data include P-, L-, and C-band surveys acquired by flying up to 30 trajectories in two headings to provide tomographic imaging capabilities. L- and C-band data were acquired by simultaneously flying two aircraft to gather bistatic data along different trajectories. The SAR dataset is complemented by 3D structural canopy measurements made via terrestrial laser scanning (TLS), Unoccupied Aerial Vehicle lidar (UAV-L) and airborne laser scanning (ALS), and in-situ forest census. This unique combination of SAR tomographic and multi-scale lidar data allows for direct comparison of canopy structural metrics across wavelength and scale, including vertical profiles of canopy wood and foliage density, and per-tree and plot-level above ground biomass (AGB). The resulting TomoSense data-set is free and openly available at ESA for any research purpose. The data-set includes ALS-derived maps of forest height and AGB, forest parameters at the level of single trees, TLS raw data, and plot-average TLS vertical profiles. The provided SAR data are coregistered, phase calibrated, and ground steered, to enable a direct implementation of any kind of interferometric or tomographic processing without having to deal with the subtleties of airborne SAR processing. Moreover, the data-base comprises SAR tomographic cubes representing forest scattering in 3D both in Radar and geographical coordinates, intended for use by non-Radar experts. For its unique features and completeness, the TomoSense data-set is intended to serve as an important basis for future research on microwave scattering from forested areas in the context of future Earth Observation missions.
Forest vertical structure
SAR tomography
Forest census
Synthetic aperture radar (SAR)
Bistatic radar
L-band
Terrestrial laser scanning (ALS)
Forest above ground biomass
P-band
Author
S. Tebaldini
Polytechnic University of Milan
Mauro Mariotti d'Alessandro
Polytechnic University of Milan
Lars Ulander
Swedish Defence Research Agency (FOI)
Chalmers, Space, Earth and Environment, Geoscience and Remote Sensing
Patrik Bennet
Chalmers, Space, Earth and Environment, Geoscience and Remote Sensing
A. Gustavsson
Swedish Defence Research Agency (FOI)
Alex Coccia
MetaSensing BV
Karlus Macedo
MetaSensing BV
Mathias Disney
University College London (UCL)
Phil Wilkes
University College London (UCL)
Hans Joachim Spors
Landesbetrieb Wald und Holz Nordrhein-Westfalen
Nico Schumacher
Landesbetrieb Wald und Holz Nordrhein-Westfalen
Jan Hanuš
Czech Academy of Sciences
Jan Novotný
Czech Academy of Sciences
Benjamin Brede
Wageningen University and Research
German Research Centre for Geosciences (GFZ)
Harm Bartholomeus
Wageningen University and Research
Alvaro Lau
Wageningen University and Research
Jens van der Zee
Wageningen University and Research
Martin Herold
Wageningen University and Research
German Research Centre for Geosciences (GFZ)
Dirk Schuettemeyer
European Space Agency (ESA)
Klaus Scipal
ESRIN - ESA Centre for Earth Observation
Remote Sensing of Environment
0034-4257 (ISSN)
Vol. 290 113532Tomosense: Technical Assistance for Airborne Measurements during the Tomographic Sensing Experiment
European Space Agency (ESA) (4000127285/19/NL/FF/gp), 2018-01-01 -- 2022-12-31.
Subject Categories (SSIF 2011)
Remote Sensing
Forest Science
Geophysics
DOI
10.1016/j.rse.2023.113532