ABSTRACT This paper employs the Normalized Difference Water Index (NDWI), Automated Water Extraction Index (AWEI), Modified Normalized Difference Water Index (MNDWI) and Near-Infrared (NIR) threshold methods to extract the boundaries of Hongjiannao Lake, Zasak reservoir and Changjiagou reservoir. The real boundary of the water bodies was obtained by visual interpretation from high-resolution imagery. The Digital Shoreline Analysis System (DSAS) is further used to calculate the net shoreline movement (NSM) between the real lake boundary and the lake boundary extracted by the NDWI, AWEI, MNDWI and NIR threshold methods. We quantitatively evaluated the accuracy of each water body extraction method by NSM, which was competed with kappa coefficient (κ) and edge detection. The results showed that the average of the |NSM| of the NDWI, MNDWI, AWEI and NIR threshold methods are 12.77 m, 16.76 m, 28.65 m and 31.43 m, respectively. The κ is 0.9869, 0.9855, 0.9747 and 0.9736, respectively and the correct extracted (T) ratios for the edge detection are 84.06%, 82.68%, 56.8% and 53.52%, respectively. The mean value of |NSM| for NDWI is the smallest, while κ and T are the highest. It indicates that the accuracy of NDWI is the highest in Hongjiannao lake. The smaller the |NSM| is, the larger κ and the higher T are. This shows that the |NSM| is consistent with the commonly used accuracy verification method such as κ and edge detection. The results of water extraction from the other two reservoirs also support this conclusion. Therefore, the accuracy verification of NSM can reflect the spatial position information and has reliability. It provides a new approach in verifying the accuracy of water body extraction methods. The optimum water extraction index for different study areas is different. The NIR band threshold method and AWEI can accurately extract water boundaries with a small amount of aquatic vegetation. However, NDWI and MNDWI are more suitable for extracting water bodies located in complex terrains.

中文翻译：

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一种新的水体提取精度评价方法

摘要 本文采用归一化差水指数（NDWI）、自动取水指数（AWEI）、修正归一化差水指数（MNDWI）和近红外（NIR）阈值方法提取红尖脑湖、扎萨克水库和张家沟的边界。水库。水体的真实边界是通过高分辨率图像的目视解译获得的。进一步使用数字海岸线分析系统（DSAS）计算真实湖泊边界与通过NDWI、AWEI、MNDWI和NIR阈值方法提取的湖泊边界之间的净海岸线运动（NSM）。我们通过 NSM 定量评估了每种水体提取方法的准确性，与 kappa 系数 (κ) 和边缘检测相竞争。结果表明|NSM|的平均值 NDWI, MNDWI, AWEI 和 NIR 阈值方法分别为 12.77 m、16.76 m、28.65 m 和 31.43 m。κ 分别为 0.9869、0.9855、0.9747 和 0.9736，边缘检测的正确提取 (T) 比率分别为 84.06%、82.68%、56.8% 和 53.52%。|NSM|的平均值 因为NDWI最小，而κ和T最大。表明NDWI的精度在红尖脑湖中是最高的。|NSM| 越小 即，κ 越大，T 越大。这表明 |NSM| 与常用的 κ 和边缘检测等精度验证方法一致。其他两个水库的抽水结果也支持了这一结论。因此，NSM 的精度验证可以反映空间位置信息，具有可靠性。它为验证水体提取方法的准确性提供了一种新方法。不同研究区的最佳抽水指标不同。NIR波段阈值法和AWEI可以准确提取少量水生植被的水域边界。但NDWI和MNDWI更适合提取位于复杂地形的水体。