Evaluation of Landsat 8 OLI imagery for unsupervised inland water extraction
Evaluation of Landsat 8 OLI imagery for unsupervised inland water extraction
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DOI：
10.1080/01431161.2016.1168948
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发表时间：
2016-04
影响因子：
3.4
通讯作者：
Huan Xie;Xin Luo;Xiong Xu;Haiyan Pan;X. Tong
中科院分区：
文献类型：
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作者：
Huan Xie;Xin Luo;Xiong Xu;Haiyan Pan;X. Tong
地球资源卫星8号的成功发射，延续了近40年来地球资源卫星系列对地观测的历史。与以前的大地卫星图像相比，随着波段数目的增加和光谱范围的改善，将有可能扩大新的大地卫星8号图像的应用。本研究的目的是探索水提取的基础上，新的陆地卫星8业务陆地成像仪（OLI）的图像。根据特定的内陆水域条件（清水，浊水，富营养化水），一些高度适应性的水指数进行评估，利用陆地卫星OLI图像的水提取。结果表明，在不同类型的水体中，清水最容易提取，平均准确率最高，达到97%。准确度最高的方法是阴影像素的自动水提取指数（AWEIsh），使用波段4和7的归一化差异水指数（NDWI 47），以及使用波段3和7的归一化差异水指数（NDWI 37），准确度分别为98.55%，95.50%和96.61%，分别对应于清水，浊水和富营养化水。通过对不同波段选择方法的分析，Landsat OLI的第7波段OLI 7（短波红外2，SWIR-2）在水体识别中表现出最好的性能。在将水分指数应用于水分提取时，采用了大津算法自动选择水分阈值。通过对大津算法和人工方法的大量实验，发现大津算法可以代替人工选择，并且具有选择用于水提取的准确阈值的能力。
ABSTRACT The successful launch of the Landsat 8 satellite continues the Earth observation of the Landsat series, which has been taking place for nearly 40 years. With the increase in the band number and the improved spectral range compared with the previous Landsat imagery, it will be possible to expand the application of the new Landsat 8 imagery. The purpose of this study is to explore water extraction based on the new Landsat 8 Operational Land Imager (OLI) imagery. According to the specific inland water conditions (clear water, turbid water, and eutrophic water), a number of highly adaptable water indices are assessed for water extraction using Landsat OLI imagery. The results show that clear water is the easiest to extract among the different types of waterbodies, with the highest average accuracy of 97%. The highest-accuracy methods are the automated water extraction index for shadow pixels (AWEIsh), the normalized difference water index using bands 4 and 7 (NDWI47), and the normalized difference water index using bands 3 and 7 (NDWI37), with accuracies of 98.55%, 95.50%, and 96.61%, corresponding to clear water, turbid water, and eutrophic water, respectively. Through the analysis of the different methods for optimal band selection, the seventh band OLI7 (shortwave infrared 2, SWIR-2) of Landsat OLI shows the best performance in water identification. When applying the water indices to water extraction, Otsu’s algorithm has been used to automatically select the water threshold. Using extensive experiments with Otsu’s algorithm and a manual method, it was found that Otsu’s algorithm can replace manual selection and has the ability to select an accurate threshold for water extraction.