CHALLENGES OF INSAR DEM DERIVATION WITH SENTINEL-1 SAR IN DENSELY VEGETATED HUMID TROPICAL ENVIRONMENT

Since the launch of the Sentinel-1 Synthetic Aperture Radar (SAR) in 2014 by the European Space Agency (ESA), there has been renewed interest in SAR data for various application, including DEM derivation with SAR Interferometry (InSAR) technique. However, the success of the InSAR technique in derivi...

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Hauptverfasser: Chindo, M. M., Hashim, M., Rasib, A. W.
Format: Tagungsbericht
Sprache:eng
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Zusammenfassung:Since the launch of the Sentinel-1 Synthetic Aperture Radar (SAR) in 2014 by the European Space Agency (ESA), there has been renewed interest in SAR data for various application, including DEM derivation with SAR Interferometry (InSAR) technique. However, the success of the InSAR technique in deriving DEM with Sentinel-1 SAR which has been largely acknowledged in sparsely vegetated regions, remains controversial in the densely vegetated environment due to certain challenges, which have rarely been reported. The aim of this study is to highlight some of the obstacles of InSAR DEM derivation with Sentinel-1 SAR over densely vegetated humid tropical environment. Suitable Sentinel-1 image pairs over part of Johor, Peninsular Malaysia, determined in terms of perpendicular and temporal baselines using the Alaska Satellite Facility (ASF) online baseline computation tool, were downloaded from the ASF archive and processed accordingly using the Sentinel Application Platform (SNAP). Difficulty in acquiring suitable image pairs, phase decorrelation and poor coherence, and unwrapping problems are some of the encountered challenges of InSAR DEM derivation with Sentinel-1 SAR in the densely vegetated humid tropics reported in this study. This study shall provide to the geoscientific community insights on InSAR DEM derivation with Sentinel-1 SAR in densely vegetated environments and initiate discussion on the technique’s promise in such environments.
ISSN:2194-9034
1682-1750
2194-9034
DOI:10.5194/isprs-archives-XLVIII-4-W6-2022-93-2023