干旱区生态环境知识资源中心(Arid): Quantifying the spatio-temporal patterns of dune migration near Minqin Oasis in northwestern China with time series of Landsat-8 and Sentinel-2 observations

Arid

DOI	10.1016/j.rse.2019.111498
	Quantifying the spatio-temporal patterns of dune migration near Minqin Oasis in northwestern China with time series of Landsat-8 and Sentinel-2 observations
	Ding, Chao 1; Zhang, Lu 1; Liao, Mingsheng 1; Feng, Guangcai 2; Dong, Jie 3; Ao, Meng 1; Yu, Yanghai 1
通讯作者	Liao, Mingsheng
来源期刊	REMOTE SENSING OF ENVIRONMENT
ISSN	0034-4257
EISSN	1879-0704
出版年	2020
卷号	236
英文摘要	Investigation of the spatio-temporal patterns of dune migration in a large-scale area with optical remote sensing techniques can help us to better understand aeolian phenomena and mitigate sand-dust disasters. With the rapid growth in data volume, extracting more accurate dune displacement time series and rates from optical observations has become possible; however, the method is not yet fully fledged. To address this issue, we propose an extended algorithm for the mature optical imagery cross-correlation (OICC) technique based on Landsat-8 (L8) and Sentinel-2 (S2) acquisitions. The main innovative points of this algorithm are: 1) the proposed pairing strategy for the OICC processing; 2) the modularized post-processing procedures for noise removal; and 3) the introduction of singular value decomposition (SVD) time-series inversion of the redundant optical observations to quantify the dune migration. To test the effectiveness of this algorithm, it was applied in the study of dune migration near Minqin Oasis in northwestern China, using enriched L8 and S2 images collected between April 2013 and April 2018. Compared with the original OICC results in stable areas, the post-processing and inversion of the proposed algorithm reduce the uncertainty by around 22-35% and 3-5% for L8, 29-48% and 5-12% for S2, respectively. The cross-comparison between the L8- and S2-derived displacement time series shows high consistency, and presents a lower uncertainty than the result of the traditional no-inversion method. Furthermore, the derived displacement rates show spatial patterns that are similar to those of the manually digitized results obtained with historical Google (TM) Earth (GE) images. These comparisons show the advantage of the proposed algorithm in automatically and accurately quantifying dune migration. Taking into account these measurements, the spatio-temporal evolution patterns of dune migration in the study area were analyzed. From the spatial perspective, the sand dunes move along a northwest-southeast axis with four detected transport pathways. Our research also shows that around 1087.7 km(2) of dune fields present an active status. The active sand dunes are currently encroaching on around 155.5 km(2) and 4.4 km(2) of land each year outside and inside the oasis, respectively, representing a problem of rapid desertification. Temporally, the displacement time series along the dominant migration direction appears as seasonal variations that are seemly consistent with the changes in local atmospheric conditions. The proposed algorithm provides a new perspective to investigate the spatio-temporal evolution of dune migration with medium-resolution L8 and S2 optical datasets.
英文关键词	Optical imagery cross-correlation Landsat-8 Sentinel-2 Time-series inversion Minqin oasis Dune migration Spatio-temporal evolution
类型	Article
语种	英语
国家	Peoples R China
收录类别	SCI-E
WOS记录号	WOS:000502894400015
WOS关键词	SAND DUNE ; WESTERN DESERT ; GLACIER MOTION ; DUST STORMS ; AREA ; DESERTIFICATION ; EARTHQUAKE ; MOVEMENTS ; TRANSPORT ; ALGORITHM
WOS类目	Environmental Sciences ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology
EI主题词	2020-01-01
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/312201
作者单位	1.Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Hubei, Peoples R China; 2.Cent S Univ, Sch Geosci & Infophys, Changsha 410083, Hunan, Peoples R China; 3.Wuhan Univ, Sch Remote Sensing & Informat Engn, Wuhan 430079, Hubei, Peoples R China
推荐引用方式 GB/T 7714	Ding, Chao,Zhang, Lu,Liao, Mingsheng,et al. Quantifying the spatio-temporal patterns of dune migration near Minqin Oasis in northwestern China with time series of Landsat-8 and Sentinel-2 observations[J],2020,236.
APA	Ding, Chao.,Zhang, Lu.,Liao, Mingsheng.,Feng, Guangcai.,Dong, Jie.,...&Yu, Yanghai.(2020).Quantifying the spatio-temporal patterns of dune migration near Minqin Oasis in northwestern China with time series of Landsat-8 and Sentinel-2 observations.REMOTE SENSING OF ENVIRONMENT,236.
MLA	Ding, Chao,et al."Quantifying the spatio-temporal patterns of dune migration near Minqin Oasis in northwestern China with time series of Landsat-8 and Sentinel-2 observations".REMOTE SENSING OF ENVIRONMENT 236(2020).