IGSNRR OpenIR
Downscaling MODIS-derived water maps with high-precision topographic data in a shallow lake
Xiao, Fei1; Cheng, Weiming2; Zhu, Lingling3; Feng, Qi1; Du, Yun1
2018
Source PublicationINTERNATIONAL JOURNAL OF REMOTE SENSING
ISSN0143-1161
Volume39Issue:22Pages:7846-7860
Corresponding AuthorXiao, Fei(xiaof@whigg.ac.cn)
AbstractRemotely sensed imagery is the most efficient and widely used data source to monitor the water area changes. However, a trade-off always exists between temporal resolution and spatial resolution for satellite images. Taking the southern Dongting Lake as an example, this study was conducted to develop a method of down-scaling the Moderate Resolution Imaging Spectroradiometer (MODIS)-derived coarse spatial resolution water maps in shallow lakes with high-precision digital elevation model. The main principle of the method is to identify and adjust the horizontal location errors of the waterlines extracted from coarse-resolution data by analysing and modifying the elevation leaps using finer-scale topography information. Moving average filter was used to smooth the errors of waterlines caused by the geometric inaccuracies and classification uncertainties of the coarse data. The optimal local window size of the moving average filter was selected automatically using an exponential decay function model and a curvature algorithm for each pixel in the waterlines. In reference to Landsat Thematic Mapper data, the accuracy of the downscaling result is distinctly higher than that of the original MODIS normalized difference water index-derived water maps. The presented method is proved to be an effective tool for acquiring water maps of shallow lake with high spatio-temporal resolution using coarseor moderate-resolution satellite imagery and high-precision topographic data.
DOI10.1080/01431161.2018.1474529
WOS KeywordRESOLUTION DATA ; INDEX NDWI ; INUNDATION ; IMAGERY ; DISCHARGE ; AREAS ; MODEL ; SCALE ; BASIN ; NDVI
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[41271125] ; Science and Technology Support Program of Hubei Province[2015BCA288] ; Natural Science Foundation of Hubei Province[2016CFA087]
Funding OrganizationNational Natural Science Foundation of China ; Science and Technology Support Program of Hubei Province ; Natural Science Foundation of Hubei Province
WOS Research AreaRemote Sensing ; Imaging Science & Photographic Technology
WOS SubjectRemote Sensing ; Imaging Science & Photographic Technology
WOS IDWOS:000456452100028
PublisherTAYLOR & FRANCIS LTD
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/50464
Collection中国科学院地理科学与资源研究所
Corresponding AuthorXiao, Fei
Affiliation1.Chinese Acad Sci, Inst Geodesy & Geophys, Key Lab Environm & Disaster Monitoring & Evaluat, Wuhan 430077, Hubei, Peoples R China
2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China
3.Changjiang Water Resources Commiss, Bur Hydrol, Wuhan, Hubei, Peoples R China
Recommended Citation
GB/T 7714
Xiao, Fei,Cheng, Weiming,Zhu, Lingling,et al. Downscaling MODIS-derived water maps with high-precision topographic data in a shallow lake[J]. INTERNATIONAL JOURNAL OF REMOTE SENSING,2018,39(22):7846-7860.
APA Xiao, Fei,Cheng, Weiming,Zhu, Lingling,Feng, Qi,&Du, Yun.(2018).Downscaling MODIS-derived water maps with high-precision topographic data in a shallow lake.INTERNATIONAL JOURNAL OF REMOTE SENSING,39(22),7846-7860.
MLA Xiao, Fei,et al."Downscaling MODIS-derived water maps with high-precision topographic data in a shallow lake".INTERNATIONAL JOURNAL OF REMOTE SENSING 39.22(2018):7846-7860.
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