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Subpixel Land Cover Mapping Using Multiscale Spatial Dependence
Chen, Yuehong1; Ge, Yong2; Chen, Yu3; Jin, Yan2; An, Ru1
2018-09-01
Source PublicationIEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
ISSN0196-2892
Volume56Issue:9Pages:5097-5106
Corresponding AuthorChen, Yuehong(chenyh@lreis.ac.cn)
AbstractThis paper proposes a new subpixel mapping (SPM) method based on multiscale spatial dependence (MSD). At the beginning, it adopts object-based and pixel-based soft classifications to generate the class proportions within each object and each pixel, respectively. Then, the object-scale spatial dependence of land cover classes is extracted from the class proportions of objects, and the combined spatial dependence at both pixel scale and subpixel scale is obtained from the class proportions of pixels. Furthermore, these spatial dependences are fused as the MSD for each subpixel. Last, a linear optimization model on each object is built to determine where the land cover classes spatially distribute within each mixed object at subpixel scales. Three experiments on two synthetic images and a real remote sensing image are carried out to evaluate the effectiveness of MSD. The experimental results show that MSD performed better than four existing SPM methods by generating less isolated classified pixels than those generated by three pixel-based SPM methods and more land cover local details than that generated by an object-based SPM method. Hence, MSD provides a valuable solution to producing land cover maps at subpixel scales.
KeywordMixed object multiscale spatial dependence (MSD) remotely sensed imagery subpixel mapping (SPM)
DOI10.1109/TGRS.2018.2808410
WOS KeywordMARKOV-RANDOM-FIELD ; REMOTELY-SENSED IMAGERY ; SENSING IMAGERY ; NEURAL-NETWORK ; SUPERRESOLUTION ; ALGORITHM ; INFORMATION ; IDENTIFICATION ; CONSTRAINTS ; INUNDATION
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[41701376] ; National Natural Science Foundation of China[41725006] ; Natural Science Foundation of Jiangsu province[BK20170866] ; Key Program of Chinese Academy of Sciences[ZDRW-ZS-2016-6-3-4] ; Fundamental Research Funds for the Central Universities[2017B11714] ; China Postdoctoral Science Foundation[2016M600356] ; State Key Laboratory of Resources and Environmental Information System
Funding OrganizationNational Natural Science Foundation of China ; Natural Science Foundation of Jiangsu province ; Key Program of Chinese Academy of Sciences ; Fundamental Research Funds for the Central Universities ; China Postdoctoral Science Foundation ; State Key Laboratory of Resources and Environmental Information System
WOS Research AreaGeochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
WOS SubjectGeochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology
WOS IDWOS:000443147600009
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
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Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/54373
Collection中国科学院地理科学与资源研究所
Corresponding AuthorChen, Yuehong
Affiliation1.Hohai Univ, Sch Earth Sci & Engn, Nanjing 210098, Jiangsu, Peoples R China
2.Univ Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
3.Nanjing Normal Univ, Sch Geog Sci, Nanjing 210023, Jiangsu, Peoples R China
Recommended Citation
GB/T 7714
Chen, Yuehong,Ge, Yong,Chen, Yu,et al. Subpixel Land Cover Mapping Using Multiscale Spatial Dependence[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2018,56(9):5097-5106.
APA Chen, Yuehong,Ge, Yong,Chen, Yu,Jin, Yan,&An, Ru.(2018).Subpixel Land Cover Mapping Using Multiscale Spatial Dependence.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,56(9),5097-5106.
MLA Chen, Yuehong,et al."Subpixel Land Cover Mapping Using Multiscale Spatial Dependence".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 56.9(2018):5097-5106.
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