The use of SAR offset tracking for detecting sand dune movement in Sudan
Mahmoud, Ahmed Mutasim Abdalla; Novellino, Alessandro; Hussain, Ekbal; Marsh, Stuart; Psimoulis, Panagiotis; Smith, Martin. 2020 The use of SAR offset tracking for detecting sand dune movement in Sudan. Remote Sensing, 12 (20), 3410. 10.3390/rs12203410
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Abstract/Summary
Sand movement is one of the main environmental hazards in Northern Sudan that threaten livelihood and rural communities. This paper investigates for the first time the use of the Synthetic Aperture Radar (SAR) offset tracking technique for detecting sand movement in Northern Sudan, and distinguishes the impact of the movement influencing factors: wind speed/direction, vegetation and topography. High-resolution images from the Sentinel-1 satellite were used for the generation of displacement maps. Three different dune fields with different characteristics were investigated for a study period between 4 June and 14 October 2017 (133 days). Dune field 1 is vegetated and near a built-up area, dune field 2 is in an open environment with sand dunes overlaying rocky substrate, and dune field 3 is located near mountains. The cumulative east displacement over the study period was 1.8 m, −1.1 m and 4.8 m for the three dune fields, respectively, while the cumulative north displacement was 0.7 m, 2.9 m and 4.2 m. Large movement is detected in the non-vegetated dune fields, with an average dune velocity of 0.18 m/d, while the vegetated dune field had a velocity of 0.09 m/d, which emphasizes the fact that vegetation is an effective stabiliser of dune movement. The pixel offset results showed a positive correlation between the wind speed/direction and the dune movement. In addition to vegetation, topography also played a major role in diverting the direction of the blown sand mainly near the edges to the mountains and the vegetation barriers. This technique showed high competency in monitoring the movement of sand dunes, in addition to identifying areas exposed to large sand drifting as a risk mapping technique.
Item Type: | Publication - Article |
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Digital Object Identifier (DOI): | 10.3390/rs12203410 |
ISSN: | 2072-4292 |
Date made live: | 17 Nov 2020 13:39 +0 (UTC) |
URI: | https://nora.nerc.ac.uk/id/eprint/528967 |
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