Production of a Global Forest/Non-Forest Map Utilizing TanDEM-X Interferometric SAR Data - Wecklich, Christopher; Martone, Michele; Rizzoli, Paola; Bueso-Bello, Jose Luis; Gonzalez, Carolina; Krieger, Gerhard (IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2017)
In this paper we describe the method that has been implemented to derive the forest/non-forest maps from TanDEM-X interferometric synthetic aperture radar (InSAR) data, globally acquired in stripmap single polarization (HH) mode. Among the several observables systematically provided by the TanDEM-X system, the volume decorrelation contribution, derived from the interferometric coherence, shows to be consistently sensitive to the particular land cover type, and is therefore used as an input data set for applying a classification method based on a fuzzy clustering algorithm. Since the considered InSAR quantity strongly depends on the geometric acquisition configuration, namely the incidence angle and the interferometric baseline, a multi-clustering classification approach is used. Once the Forest/NonForest classification for individual acquisitions is generated, overlapping acquisitions are mosaicked together to improve the resulting accuracy. The final step in the Forest/NonForest map production is to apply a binary Forest/Non-Forest decision and the decision threshold is found through comparison with similar data and statistical analysis. Verification and validation of the final product will be accomplished through comparison to other forest maps. In summary, this paper covers the processing and production status of the global TanDEM-X Forest/Non-Forest map which will be made available to the scientific community in 2017.
DLR Import::2019-04-03
Keywords: forest classification; SAR interferometry (InSAR); Synthetic aperture radar (SAR); TanDEM-X mission; volume decorrelation