The Global Forest/Non-Forest Classification Map from TanDEM-X Interferometric Data
Martone M, Rizzoli P, González C, Bueso-Bello JL, Zink M, Krieger G, Moreira A (2018)
Publication Type: Conference contribution
Publication year: 2018
Publisher: Institute of Electrical and Electronics Engineers Inc.
Edited Volumes: Proceedings of the European Conference on Synthetic Aperture Radar, EUSAR
Book Volume: 2018-June
Pages Range: 1--6
Conference Proceedings Title: European Conference on Synthetic Aperture Radar (EUSAR)
ISBN: 9783800746361
URI: https://elib.dlr.de/119645/
Abstract
In this paper we present the global Forest/Non-Forest Map derived from TanDEM-X bistatic interferometric synthetic aperture radar (InSAR) data. The global TanDEM-X dataset has been acquired in stripmap single HH polarization mode and covers a time span from 2011 up to 2016. The volume correlation factor (or volume decorrelation), γVol, derived from the interferometric coherence, quantifies the coherence loss due to multiple scattering within a volume, a mechanism which typically occurs in presence of vegetation. For this reason, the γVol has been used as main indicator for the identification of forested areas. Quicklook images, a multi-looked version of the original full-resolution data at a ground resolution of 50 m × 50 m, have been used as input for the generation of the global product. The mosaicking process of multiple acquisitions is discussed as well, together with the identification of additional information layers, such as urban areas or water bodies. The resulting global forest/non-forest map has been validated using external reference information, as well as with other existing classification maps, and an overall agreement typically exceeding 90% is observed. The global product presented in this paper is intended to be released to the scientific community for free download and usage.
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APA:
Martone, M., Rizzoli, P., González, C., Bueso-Bello, J.L., Zink, M., Krieger, G., & Moreira, A. (2018). The Global Forest/Non-Forest Classification Map from TanDEM-X Interferometric Data. In European Conference on Synthetic Aperture Radar (EUSAR) (pp. 1--6). Institute of Electrical and Electronics Engineers Inc..
MLA:
Martone, Michele, et al. "The Global Forest/Non-Forest Classification Map from TanDEM-X Interferometric Data." Proceedings of the 12th European Conference on Synthetic Aperture Radar, EUSAR 2018 Institute of Electrical and Electronics Engineers Inc., 2018. 1--6.
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