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Subpixel Land Cover Mapping Using Multiscale Spatial Dependence

文献类型：期刊论文

作者Chen, Yuehong1; Ge, Yong2; Chen, Yu3; Jin, Yan2; An, Ru1
刊名IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
出版日期2018-09-01
卷号56期号:9页码:5097-5106
关键词Mixed object multiscale spatial dependence (MSD) remotely sensed imagery subpixel mapping (SPM)
ISSN号0196-2892
DOI10.1109/TGRS.2018.2808410
通讯作者Chen, Yuehong(chenyh@lreis.ac.cn)
英文摘要This 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.
WOS关键词MARKOV-RANDOM-FIELD ; REMOTELY-SENSED IMAGERY ; SENSING IMAGERY ; NEURAL-NETWORK ; SUPERRESOLUTION ; ALGORITHM ; INFORMATION ; IDENTIFICATION ; CONSTRAINTS ; INUNDATION
资助项目National 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
WOS研究方向Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
语种英语
WOS记录号WOS:000443147600009
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
资助机构National 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
源URL[http://ir.igsnrr.ac.cn/handle/311030/54372]  
专题中国科学院地理科学与资源研究所
通讯作者Chen, Yuehong
作者单位1.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
推荐引用方式
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.

入库方式： OAI收割

来源：地理科学与资源研究所

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