Locally adaptive super-resolution waterline mapping with MODIS imagery

doi:10.1080/2150704X.2016.1219460

CORC > 合肥物质科学研究院 > 中国科学院合肥物质科学研究院 > 应用技术研究所

	Locally adaptive super-resolution waterline mapping with MODIS imagery
	Li, Wenbo 1; Zhang, Xiuhua 2; Ling, Feng 3; Zheng, Dongbo 3
刊名	REMOTE SENSING LETTERS
	2016
卷号	7 期号:12 页码:1121-1130
DOI	10.1080/2150704X.2016.1219460
文献子类	Article
英文摘要	Mapping inland water bodies is important for relevant research fields and water resource management. Satellite remote sensing is a routine approach, and various remotely sensed images have been applied to map waterlines. MODerate-resolution Imaging Spectroradiometer (MODIS) images have advantages for waterline mapping in large areas, thanks to its wide scan width and high frequent revisiting period; however, the spatial resolution of MODIS images is too coarse to map waterlines accurately. In this article, a super-resolution mapping (SRM) model was proposed for fine spatial resolution waterline mapping with MODIS images. The proposed SRM model was directly applied in the MODIS band 2 images, which have a fine spatial resolution and a high spectral separability between water and land. In order to further take account of the spatial heterogeneity of endmembers, the reflectance values of water and land were locally calculated for each coarse resolution pixel. The proposed SRM model was assessed in two study areas located in the Tibetan Plateau, China and Wisconsin, United States, including water bodies with different areas and boundary shapes. The results showed that the accuracy values of the proposed SRM model using local endmembers were higher than those of hard classification and the SRM model using average endmembers, showing the effectiveness of the proposed model in fine spatial resolution waterline mapping with MODIS imagery.
WOS关键词	REMOTE-SENSING IMAGERY ; WETLAND INUNDATION ; RESOLUTION ; FLOODPLAIN ; ALGORITHM ; SCALE ; TM
WOS研究方向	Remote Sensing ; Imaging Science & Photographic Technology
语种	英语
WOS记录号	WOS:000383873900002
资助机构	National Natural Science Foundation of China(61305039) ; National Natural Science Foundation of China(61305039) ; National Natural Science Foundation of China(61305039) ; National Natural Science Foundation of China(61305039) ; National Key Technologies Research and Development Program of China(2016YFB0502604) ; National Key Technologies Research and Development Program of China(2016YFB0502604) ; National Key Technologies Research and Development Program of China(2016YFB0502604) ; National Key Technologies Research and Development Program of China(2016YFB0502604) ; Distinguished Young Scientist Grant of the Chinese Academy of Sciences ; Distinguished Young Scientist Grant of the Chinese Academy of Sciences ; Distinguished Young Scientist Grant of the Chinese Academy of Sciences ; Distinguished Young Scientist Grant of the Chinese Academy of Sciences ; National Natural Science Foundation of China(61305039) ; National Natural Science Foundation of China(61305039) ; National Natural Science Foundation of China(61305039) ; National Natural Science Foundation of China(61305039) ; National Key Technologies Research and Development Program of China(2016YFB0502604) ; National Key Technologies Research and Development Program of China(2016YFB0502604) ; National Key Technologies Research and Development Program of China(2016YFB0502604) ; National Key Technologies Research and Development Program of China(2016YFB0502604) ; Distinguished Young Scientist Grant of the Chinese Academy of Sciences ; Distinguished Young Scientist Grant of the Chinese Academy of Sciences ; Distinguished Young Scientist Grant of the Chinese Academy of Sciences ; Distinguished Young Scientist Grant of the Chinese Academy of Sciences
内容类型	期刊论文
源URL	[http://ir.hfcas.ac.cn:8080/handle/334002/24324]
专题	合肥物质科学研究院_应用技术研究所
作者单位	1.Chinese Acad Sci, Hefei Inst Phys Sci, Inst Technol Innovat, Hefei, Anhui, Peoples R China 2.Wuhan Inst Technol, Wuhan, Peoples R China 3.Chinese Acad Sci, Inst Geodesy & Geophys, Wuhan 430077, Peoples R China
推荐引用方式 GB/T 7714	Li, Wenbo,Zhang, Xiuhua,Ling, Feng,et al. Locally adaptive super-resolution waterline mapping with MODIS imagery[J]. REMOTE SENSING LETTERS,2016,7(12):1121-1130.
APA	Li, Wenbo,Zhang, Xiuhua,Ling, Feng,&Zheng, Dongbo.(2016).Locally adaptive super-resolution waterline mapping with MODIS imagery.REMOTE SENSING LETTERS,7(12),1121-1130.
MLA	Li, Wenbo,et al."Locally adaptive super-resolution waterline mapping with MODIS imagery".REMOTE SENSING LETTERS 7.12(2016):1121-1130.