DocumentCode
575910
Title
Synergetic use of TerraSAR-X and Radarsat-2 time series data for identification and characterization of grassland types - a case study in Southern Bavaria, Germany
Author
Metz, Annekatrin ; Schmitt, Andreas ; Esch, Thomas ; Reinartz, Peter ; Klonus, Sascha ; Ehlers, Manfred
Author_Institution
Inst. for Geoinf. & Remote Sensing, Univ. of Osnabruck, Osnabruck, Germany
fYear
2012
fDate
22-27 July 2012
Firstpage
3560
Lastpage
3563
Abstract
In the context of global change, alteration of landscapes and loss of biodiversity, the monitoring of habitats, vegetation types and their changes have become extraordinary important. In this paper, first results from a study that analyses the differentiability of NATURA2000 habitats and HNV grassland with imaging radar data are presented. Therefore, Kennaugh elements derived from TerraSAR-X and Radarsat-2 dual pol (VV/VH) time series data are used, both separately and in combination, to model the distribution of these classes with the Maximum-Entropy principle. The preliminary results show that the multi-frequency approach enables - compared to single frequency analyses - a finer differentiation between scatterers in the size of 3-6 cm (e.g. 7120, 7230 and HNV grassland).
Keywords
maximum entropy methods; radar imaging; remote sensing by radar; synthetic aperture radar; time series; vegetation; vegetation mapping; Germany; HNV grassland; Kennaugh elements; NATURA2000 habitats; Radarsat-2 time series data; Southern Bavaria; TerraSAR-X time series data; biodiversity; differentiability; grassland types; imaging radar data; landscapes; maximum-entropy principle; single frequency analyses; synergetic use; Biomedical optical imaging; Data models; Monitoring; Optical imaging; Remote sensing; Time series analysis; Vegetation mapping; Maximum-Entropy; Radarsat-2; TerraSAR-X; grassland; polarimetry;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location
Munich
ISSN
2153-6996
Print_ISBN
978-1-4673-1160-1
Electronic_ISBN
2153-6996
Type
conf
DOI
10.1109/IGARSS.2012.6350649
Filename
6350649
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