Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/99977
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dc.contributorDepartment of Land Surveying and Geo-Informatics-
dc.creatorAli, Een_US
dc.creatorXu, Wen_US
dc.creatorDing, Xen_US
dc.date.accessioned2023-07-26T05:49:35Z-
dc.date.available2023-07-26T05:49:35Z-
dc.identifier.urihttp://hdl.handle.net/10397/99977-
dc.language.isoenen_US
dc.publisherMDPIen_US
dc.rights© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication Ali E, Xu W, Ding X. Spatiotemporal Variability of Dune Velocities and Corresponding Uncertainties, Detected from Optical Image Matching in the North Sinai Sand Sea, Egypt. Remote Sensing. 2021; 13(18):3694 is available at https://doi.org/10.3390/rs13183694.en_US
dc.subjectDune dynamicsen_US
dc.subjectDune velocityen_US
dc.subjectFeature trackingen_US
dc.subjectLandsat-8en_US
dc.subjectSentinel-2en_US
dc.subjectCOSI-Corren_US
dc.subjectFusionen_US
dc.subjectUncertaintyen_US
dc.subjectWind regimesen_US
dc.titleSpatiotemporal variability of dune velocities and corresponding uncertainties, detected from optical image matching in the North Sinai Sand Sea, Egypten_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume13en_US
dc.identifier.issue18en_US
dc.identifier.doi10.3390/rs13183694en_US
dcterms.abstractUnderstanding the relationship between climatic conditions and dune ecosystems requires the large-scale monitoring of spatiotemporal patterns of dune velocities. Due to their large extent and remoteness, dune fields are ideal for remote sensing techniques. Dune velocities in the Sand Sea North Sinai are characterized by large spatial and temporal variability. To this end, a total of 265 pairs from four Landsat-8 images from April 2013 to April 2018 were automatically matched with the COSI Corr engine to determine the dune velocities. These pairs were selected so that differences in the solar angles were small and spanned at least one year. This helps to reduce shadowing in the deformation fields and the error budget in converting displacements to annual velocities. To improve spatial coverage and reduce measurement uncertainty, the fusion of individual offset maps is considered feasible. We compared the performance of two methods (i.e., inversion and temporal median fusion) in performing the fusion of individual velocities, and the two methods showed good agreement. The fusion of individual velocities allowed us to estimate the final velocities for about 98.8% of the dune areas. Our results suggest that the magnitudes and directions of dune migration at Sand Sea are spatially and temporally variable. The geometric mean of the active features associated with 12 regions in the Sand Sea ranged from 1.65 m/y to 3.52 m/y, with median directions from 56.19◦ to 173.11◦ . The stable regions allowed us to estimate the 95% confidence intervals of the final velocities and extend these calculations to the dune targets. The median uncertainties were 0.10 m/y and 0.25 m/y for the stable and moving targets, respectively. We estimated the coherence of the final velocity vector, which can be considered as an indicator of the homogeneity of migration directions between the offset maps. We compared the final Landsat-8 velocities with those from Sentinel-2 to validate the results and found a good agreement in the magnitudes and directions. The process of selecting high-quality pairs and then fusing the individual maps showed a high performance in terms of spatial coverage and reliability of the extracted velocities.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationRemote sensing, Sept 2021, v. 13, no. 18, 3694en_US
dcterms.isPartOfRemote sensingen_US
dcterms.issued2021-09-
dc.identifier.scopus2-s2.0-85115185892-
dc.identifier.eissn2072-4292en_US
dc.identifier.artn3694en_US
dc.description.validate202307 bcch-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOS-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextHong Kong Special Administrative Region; Innovative Technology Fund; U.S. Geological Survey; European Space Agency; National Natural Science Foundation of China; Hong Kong Polytechnic University; Research Institute for Sustainable Urban Development, Hong Kong Polytechnic University; National Key Research and Development Program of Chinaen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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