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Assessing methods of identifying open water bodies using Landsat 8 OLI imagery

机译:使用Landsat 8 OLI图像识别开放水域的评估方法

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摘要

Remote sensing is an effective technology for monitoring water resources. However, many methods in remote sensing imagery used to identify open bodies of water have often been shown to produce varying water body classification results for the same bodies of water. Therefore, it is necessary to have measures to assess these methods. In this study, we used datasets collected in the field to assess methods for identifying open water bodies using images from the Landsat 8 Operational Land Imager. From this, we clarified the difference in the performance between the use of spectral reflectance images and that of digital number (DN) value images for the classification of water bodies. The results showed that the normalized difference water index (NDWI), calculated using green and near-infrared bands (NDWIGreen/NIR) with reflectance, captured correct control points with an accuracy of greater than 95 % and was therefore the superior method. The result of a comparison in performance in terms of the NDWI between reflectance images and DN value images was consistent with their initial definitions. The NDWI indices calculated by the initial definitions yielded more reasonable results in the classification of water bodies. The optimized threshold, calibrated and validated by 737 field control points, generated water classification results with a higher confidence in this study. We think that it might be better to set the optimized threshold of NDWIGreen/NIR to -0.05 instead of the value of zero used in many studies. However, more optimized thresholds for other regions need to be calibrated and confirmed if data are available. Our results indicated that NDWI methods are more suitable for water body classification than single-band methods when the frequency histogram method is used.
机译:遥感是监测水资源的有效技术。然而,在遥感影像中用于识别水体开放的许多方法通常显示出对相同水体产生不同的水体分类结果。因此,有必要采取措施评估这些方法。在这项研究中,我们使用在野外收集的数据集来评估使用Landsat 8 Operational Land Imager的图像识别开放水体的方法。由此,我们阐明了在光谱反射率图像和数字(DN)值图像用于水体分类之间的性能差异。结果表明,使用具有反射率的绿色和近红外波段(NDWIGreen / NIR)计算出的归一化差水指数(NDWI)可以以95%以上的精度捕获正确的控制点,因此是一种较好的方法。反射率图像和DN值图像之间在NDWI方面的性能比较结果与它们的初始定义一致。通过初始定义计算出的NDWI指数在水体分类中产生了更合理的结果。经737个现场控制点校准和验证的最佳阈值产生的水分类结果对本研究具有较高的信心。我们认为最好将NDWIGreen / NIR的优化阈值设置为-0.05,而不是许多研究中使用的零值。但是,如果数据可用,则需要对其他区域的更优化阈值进行校准和确认。我们的结果表明,当使用频率直方图方法时,NDWI方法比单波段方法更适合于水体分类。

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