Monitoring erosion in tropical savannas from C-band radar coherence

被引:11
|
作者
Castellazzi, Pascal [1 ]
Khan, Sana [2 ]
Walker, Simon J. [3 ]
Bartley, Rebecca [4 ]
Wilkinson, Scott N. [3 ]
Normand, Jonathan C. L. [5 ]
机构
[1] CSIRO, Deep Earth imaging FSP, Environm, Waite Rd, Urrbrae, SA 5064, Australia
[2] CSIRO, Environm, 1 James Cook Dr, Douglas, Qld 4814, Australia
[3] CSIRO, Environm, GPO Box 1700, Canberra, ACT 2600, Australia
[4] CSIRO, Environm, GPO Box 2583, Brisbane, Qld 4001, Australia
[5] Univ Southern Calif, Viterbi Sch Engn, Los Angeles, CA USA
关键词
Geomorphic change detection; Deposition; River management; Radar interferometry; InSAR; Australia; GULLY EROSION; SEDIMENT; IMPACTS; MANAGEMENT;
D O I
10.1016/j.rse.2023.113546
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Increased erosion related to climate and/or land cover change has adverse impacts on terrestrial and aquatic ecosystems. Mapping of erosion hotspots improves our ability to identify and potentially remediate the most active erosion sources. The topical savannas of the Great Barrier Reef catchments, in northeast Australia, are generating excessive sediment yields, primarily from gully erosion. To reduce the adverse impacts on marine ecosystems, there is an urgent need to identify priority erosion hotspots and implement mitigation measures. While repeat airborne LiDAR surveys allow subtle topographic change detection, they are cost-intensive for catchment-scale applications and their applicability is constrained by data avalability and detection treshold of ground level change. In contrast, satellite-based radar imagery can allow large scale tracking of geomorphic change at high temporal resolution. Here we apply a new method based on Sentinel-1 C-band radar images and Coherence Change Detection (CCD), where large stacks of interferometric coherence images are subdivided with rain gauge time-series for separation of erosion-rich and erosion-free coherence information. After correcting the former with the latter, the resulting corrected coherence maps are compared with differential elevation models derived from multitemporal LiDAR, regional scale gully delineation maps, maps of gullying potential and in-situ field verification. Our results demonstrate the promising potential of this technique in detecting gully erosion hotspots. The coherence loss indicating erosion/deposition is well detected in wide gully morphologies, however, the line-of-sight angle does not allow penetration into narrow linear gullies. Further, CCD detects sheetwash or rill erosion occurring in areas identified as at risk of gully expansion, which is commonly below detection threshold for multitemporal LiDAR datasets. When used with LiDAR-derived geomorphic change mapping and gullying potential maps, CCD allows identification of gully erosion dynamics and forecasting gully evolution and creation, which is critical for supporting mitigation measures.
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页数:20
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