气候变化领域集成服务门户(CCPortal): Open water detection in urban environments using high spatial resolution remote sensing imagery

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DOI	10.1016/j.rse.2020.111706
	Open water detection in urban environments using high spatial resolution remote sensing imagery
	Chen F.; Chen X.; Van de Voorde T.; Roberts D.; Jiang H.; Xu W.
发表日期	2020
ISSN	00344257
卷号	242
英文摘要	Commonly applied water indices such as the normalized difference water index (NDWI) and the modified normalized difference water index (MNDWI) were originally conceived for medium spatial resolution remote sensing images. In recent decades, high spatial resolution imagery has shown considerable potential for deriving accurate land cover maps of urban environments. Applying traditional water indices directly on this type of data, however, leads to severe misclassifications as there are many materials in urban areas that are confused with water. Furthermore, threshold parameters must generally be fine-tuned to obtain optimal results. In this paper, we propose a new open surface water detection method for urbanized areas. We suggest using inequality constraints as well as physical magnitude constraints to identify water from urban scenes. Our experimental results on spectral libraries and real high spatial resolution remote sensing images demonstrate that by using a set of suggested fixed threshold values, the proposed method outperforms or obtains comparable results with algorithms based on traditional water indices that need to be fine-tuned to obtain optimal results. When applied to the ASTER and ECOSTRESS spectral libraries, our method identified 3677 out of 3695 non-water spectra. By contrast, NDWI and MNDWI only identified 2934 and 2918 spectra. Results on three real hyperspectral images demonstrated that the proposed method successfully identified normal water bodies, meso-eutrophic water bodies, and most of the muddy water bodies in the scenes with F-measure values of 0.91, 0.94 and 0.82 for the three scenes. For surface glint and hyper-eutrophic water, our method was not as effective as could be expected. We observed that the commonly used threshold value of 0 for NDWI and MNDWI results in greater levels of confusion, with F-measures of 0.83, 0.64 and 0.64 (NDWI) and 0.77, 0.63 and 0.59 (MNDWI). The proposed method also achieves higher precision than the untuned NDWI and MNDWI with the same recall values. Next to numerical performance, the proposed method is also physically justified, easy-to implement, and computationally efficient, which suggests that it has potential to be applied in large scale water detection problem. © 2020 Elsevier Inc.
英文关键词	Open surface water; Remote sensing; Urban; Water index
语种	英语
scopus关键词	Constraint theory; Eutrophication; Image resolution; Libraries; Numerical methods; Spectroscopy; Surface waters; Urban planning; Computationally efficient; High spatial resolution; High spatial resolution imagery; Modified Normalized Difference Water Index (MNDWI); Normalized difference water index; Remote sensing imagery; Urban; Water index; Remote sensing; ASTER; detection method; land cover; NDVI; remote sensing; satellite imagery; spatial resolution; surface water; urban area; urban ecosystem
来源期刊	Remote Sensing of Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/179365
作者单位	School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, 611731, China; Center for Information Geoscience, University of Electronic Science and Technology of China, Chengdu, 611731, China; Department of Geography, Ghent University, Krijgslaan 281, S8, Ghent, 9000, Belgium; Department of Geography, Vrije Universiteit Brussel, Pleinlaan 2, Brussels, 1050, Belgium; Department of Geography, University of California, Santa Barbara, Santa Barbara, CA 93106, United States
推荐引用方式 GB/T 7714	Chen F.,Chen X.,Van de Voorde T.,et al. Open water detection in urban environments using high spatial resolution remote sensing imagery[J],2020,242.
APA	Chen F.,Chen X.,Van de Voorde T.,Roberts D.,Jiang H.,&Xu W..(2020).Open water detection in urban environments using high spatial resolution remote sensing imagery.Remote Sensing of Environment,242.
MLA	Chen F.,et al."Open water detection in urban environments using high spatial resolution remote sensing imagery".Remote Sensing of Environment 242(2020).