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An automatic approach for land-change detection and land updates based on integrated NDVI timing analysis and the CVAPS method with GEE support
Hu, Yunfeng1,2; Dong, Yu1,2; Batunacun1,3
2018-12-01
Source PublicationISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
ISSN0924-2716
Volume146Pages:347-359
Corresponding AuthorHu, Yunfeng(huyf@lreis.ac.cn)
AbstractLand-use/land-cover information is the basis of global-change research and regional governmental management. Automatic approaches are always required to update land maps for large-scale areas, and change detection techniques are the most important component of land-updating methods. Previous research has confirmed that simple change detection based on Landsat images from two different years with two different phenophases yields unsatisfactory results and may induce many misclassifications and pseudo-change identifications because of the phenological differences between remote sensing images. With the support of the Google Earth Engine (GEE), we propose a land-use/land-cover type discrimination method based on a classification and regression tree (CART), apply change-vector analysis in posterior probability space (CVAPS) and the best histogram maximum entropy method for change detection, and further improve the accuracy of the land-updating results in combination with NDVI timing analysis, which indicates the annual growth of ground vegetation. In the case study, we select western China as the research area and obtain a 2014 land map based on the ESA GlobCover 2009 dataset. The results confirm that the accuracy of the land-renewal results based on the CART-CVAPS-NDVI method reach 78.6-88.2%, which is 4-10% higher than that of the CART-CVPAS method without NDVI timing analysis. The CART-CVAPS-NDVI method has more detailed and accurate resolutions for land-change detection.
KeywordAutomatic update Change detection Land use/land cover Time-series analysis
DOI10.1016/j.isprsjprs.2018.10.008
WOS KeywordCHANGE-VECTOR ANALYSIS ; COVER CLASSIFICATION ; SURFACE REFLECTANCE ; ALGORITHMS ; GLOBCOVER ; MACHINE ; TRENDS ; SPACE ; MODIS
Indexed BySCI
Language英语
Funding ProjectNational Key Research and Development Program of China[2016YFB0501502] ; National Key Research and Development Program of China[2016YFC0503701] ; Strategic Priority Research Program[XDA19040301] ; Strategic Priority Research Program[XDA20010202] ; Key Project of High Resolution Earth Observation Systems[00-Y30B14-9001-14/16]
Funding OrganizationNational Key Research and Development Program of China ; Strategic Priority Research Program ; Key Project of High Resolution Earth Observation Systems
WOS Research AreaPhysical Geography ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS SubjectGeography, Physical ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS IDWOS:000453499400026
PublisherELSEVIER SCIENCE BV
Citation statistics
Cited Times:5[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/51364
Collection中国科学院地理科学与资源研究所
Corresponding AuthorHu, Yunfeng
Affiliation1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
2.Univ Chinese Acad Sci, Beijing 101408, Peoples R China
3.Leibniz Ctr Agr Landscape Res, Eberswalder Str 84, D-15374 Muncheberg, Germany
Recommended Citation
GB/T 7714
Hu, Yunfeng,Dong, Yu,Batunacun. An automatic approach for land-change detection and land updates based on integrated NDVI timing analysis and the CVAPS method with GEE support[J]. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,2018,146:347-359.
APA Hu, Yunfeng,Dong, Yu,&Batunacun.(2018).An automatic approach for land-change detection and land updates based on integrated NDVI timing analysis and the CVAPS method with GEE support.ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,146,347-359.
MLA Hu, Yunfeng,et al."An automatic approach for land-change detection and land updates based on integrated NDVI timing analysis and the CVAPS method with GEE support".ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING 146(2018):347-359.
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