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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

Tebaldini, S., d'Alessandro, M. M., Ulander, L. M. H., Bennet, P., Gustavsson, A., Coccia, A., Macedo, K., Disney, M., Wilkes, P., Spors, H.-J., Schumacher, N., Hanuš, J., Novotný, J., Brede, B., Bartholomeus, H., Lau, A., van der Zee, J., Herold, M., Schuettemeyer, D., Scipal, K. (2023): 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. - Remote Sensing of Environment, 290, 113532.
https://doi.org/10.1016/j.rse.2023.113532

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 Creators:
Tebaldini, Stefano1, Author
d'Alessandro, Mauro Mariotti1, Author
Ulander, Lars M. H.1, Author
Bennet, Patrik1, Author
Gustavsson, Anders1, Author
Coccia, Alex1, Author
Macedo, Karlus1, Author
Disney, Mathias1, Author
Wilkes, Phil1, Author
Spors, Hans-Joachim1, Author
Schumacher, Nico1, Author
Hanuš, Jan1, Author
Novotný, Jan1, Author
Brede, Benjamin2, Author              
Bartholomeus, Harm1, Author
Lau, Alvaro1, Author
van der Zee, Jens1, Author
Herold, Martin2, Author              
Schuettemeyer, Dirk1, Author
Scipal, Klaus1, Author
Affiliations:
1External Organizations, ou_persistent22              
21.4 Remote Sensing, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum, ou_146028              

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Free keywords: Synthetic aperture radar (SAR)SAR tomographyBistatic radarP-bandL-bandForest vertical structureForest above ground biomassTerrestrial laser scanning (ALS)Forest census
 Abstract: 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.

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 Dates: 20232023
 Publication Status: Finally published
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1016/j.rse.2023.113532
GFZPOF: p4 T5 Future Landscapes
GFZPOFCCA: p4 CARF RemSens
OATYPE: Green Open Access
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Title: Remote Sensing of Environment
Source Genre: Journal, SCI, Scopus
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Pages: - Volume / Issue: 290 Sequence Number: 113532 Start / End Page: - Identifier: CoNE: https://gfzpublic.gfz-potsdam.de/cone/journals/resource/journals427
Publisher: Elsevier