干旱区生态环境知识资源中心(Arid): Improved optical image matching time series inversion approach for monitoring dune migration in North Sinai Sand Sea: Algorithm procedure, application, and validation

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DOI	10.1016/j.isprsjprs.2020.04.004
	Improved optical image matching time series inversion approach for monitoring dune migration in North Sinai Sand Sea: Algorithm procedure, application, and validation
	Ali, Eslam 1; Xu, Wenbin 2,3; Ding, Xiaoli 1
通讯作者	Xu, Wenbin
来源期刊	ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
ISSN	0924-2716
EISSN	1872-8235
出版年	2020
卷号	164 页码:106-124
英文摘要	Sand dune migration poses a potential threat to desert infrastructure, vegetation, and atmospheric conditions. Capturing the patterns of long-term dune migration is useful for predicting probable desertification issues and wind conditions across vast desert areas. In this study, we employed optical image matching and a singular value decomposition approach to estimate the rates of dune migration in the North Sinai Sand Sea using the free Landsat 8 and Sentinel-2 archives. Our optical image matching time-series selection and inversion (OPTSI) algorithm limited the difference in the solar illumination of correlated pairs to decrease shadows and seasonal variability. We found that the maximum annual dune migration rates were 9.4 m/a and 15.9 m/a for Landsat 8 and Sentinel-2 data, respectively, and the results of time-series analysis revealed the existence of seasonal variations in dune migration controlled by wind regimes. The directions of sand movement extracted from the mean velocity solution agreed strongly with each other and with the drift directions estimated using wind data from meteorological stations. We assessed the uncertainty of each solution based on the variance of stable areas. Our results showed that the proposed inversion decreased uncertainty by up to 25% and increased the spatial coverage by up to 20%. This algorithm is also promising for the retrieval of historical time series on the ground displacements of glaciers and slow-moving landslides employing free archives that provide high-frequency images.
英文关键词	Optical image matching COSI-Corr Automatic pairing selection Dune migration Time series inversion North Sinai Sand Sea
类型	Article
语种	英语
国家	Peoples R China
开放获取类型	hybrid
收录类别	SCI-E
WOS记录号	WOS:000535696600009
WOS关键词	SATELLITE IMAGES ; WESTERN DESERT ; DEFORMATION ; AREA ; VELOCITIES ; GLACIERS ; DYNAMICS ; MODEL ; CITY
WOS类目	Geography, Physical ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Physical Geography ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/319204
作者单位	1.Hong Kong Polytech Univ, Dept Land Surveying & Geoinformat, Kowloon, Hong Kong 999077, Peoples R China; 2.Cent South Univ, Sch Geosci & Infophys, Changsha 410083, Hunan, Peoples R China; 3.Cent South Univ, Minist Educ, Key Lab Metallogen Predict Nonferrous Met & Geol, Changsha 410083, Hunan, Peoples R China
推荐引用方式 GB/T 7714	Ali, Eslam,Xu, Wenbin,Ding, Xiaoli. Improved optical image matching time series inversion approach for monitoring dune migration in North Sinai Sand Sea: Algorithm procedure, application, and validation[J],2020,164:106-124.
APA	Ali, Eslam,Xu, Wenbin,&Ding, Xiaoli.(2020).Improved optical image matching time series inversion approach for monitoring dune migration in North Sinai Sand Sea: Algorithm procedure, application, and validation.ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,164,106-124.
MLA	Ali, Eslam,et al."Improved optical image matching time series inversion approach for monitoring dune migration in North Sinai Sand Sea: Algorithm procedure, application, and validation".ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING 164(2020):106-124.