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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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Main Authors: Chindo, Musa Muhammad, Hashim, Mazlan, Rasib, Abd. Wahid
Format: Conference or Workshop Item
Language:English
Published: 2023
Subjects:
H Social Sciences (General)
Online Access:http://eprints.utm.my/108294/1/MazlanHashim2023_ChallengesofInSARDEMDerivationwithSentinel.pdf
http://eprints.utm.my/108294/
http://dx.doi.org/10.5194/isprs-archives-XLVIII-4-W6-2022-93-2023
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spelling my.utm.1082942024-10-22T08:05:10Z http://eprints.utm.my/108294/ Challenges of InSAR DEM derivation with Sentinel-1 SAR in densely vegetated humid tropical environment Chindo, Musa Muhammad Hashim, Mazlan Rasib, Abd. Wahid H Social Sciences (General) 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. 2023-02-06 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.utm.my/108294/1/MazlanHashim2023_ChallengesofInSARDEMDerivationwithSentinel.pdf Chindo, Musa Muhammad and Hashim, Mazlan and Rasib, Abd. Wahid (2023) Challenges of InSAR DEM derivation with Sentinel-1 SAR in densely vegetated humid tropical environment. In: 2022 Geoinformation Week: Broadening Geospatial Science and Technology, 14 November 2022 - 17 November 2022, Virtual, UTM Johor Bahru, Johor, Malaysia. http://dx.doi.org/10.5194/isprs-archives-XLVIII-4-W6-2022-93-2023
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic H Social Sciences (General)
spellingShingle H Social Sciences (General)
Chindo, Musa Muhammad
Hashim, Mazlan
Rasib, Abd. Wahid
Challenges of InSAR DEM derivation with Sentinel-1 SAR in densely vegetated humid tropical environment
description 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.
format Conference or Workshop Item
author Chindo, Musa Muhammad
Hashim, Mazlan
Rasib, Abd. Wahid
author_facet Chindo, Musa Muhammad
Hashim, Mazlan
Rasib, Abd. Wahid
author_sort Chindo, Musa Muhammad
title Challenges of InSAR DEM derivation with Sentinel-1 SAR in densely vegetated humid tropical environment
title_short Challenges of InSAR DEM derivation with Sentinel-1 SAR in densely vegetated humid tropical environment
title_full Challenges of InSAR DEM derivation with Sentinel-1 SAR in densely vegetated humid tropical environment
title_fullStr Challenges of InSAR DEM derivation with Sentinel-1 SAR in densely vegetated humid tropical environment
title_full_unstemmed Challenges of InSAR DEM derivation with Sentinel-1 SAR in densely vegetated humid tropical environment
title_sort challenges of insar dem derivation with sentinel-1 sar in densely vegetated humid tropical environment
publishDate 2023
url http://eprints.utm.my/108294/1/MazlanHashim2023_ChallengesofInSARDEMDerivationwithSentinel.pdf
http://eprints.utm.my/108294/
http://dx.doi.org/10.5194/isprs-archives-XLVIII-4-W6-2022-93-2023
_version_ 1814043644174270464
score 13.211869

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