Center for Technology and Geosciences, Federal University of Pernambuco (UFPE), Recife 50670-901, Brazil.
Center for Technology, Federal University of Piauí (UFPI), Teresina 64049-550, Brazil.
Sensors (Basel). 2021 Nov 11;21(22):7494. doi: 10.3390/s21227494.
Although the single threshold is still considered a suitable and easy-to-do technique to extract water features in spatiotemporal analysis, it leads to unavoidable errors. This paper uses an enumerative search to optimize thresholds over satellite-derived modified normalized difference water index (MNDWI). We employed a cross-validation approach and treated accuracy as a random variable in order to: (a) investigate uncertainty related to its application; (b) estimate non-optimistic errors involving single thresholding; (c) investigate the main factors that affect the accuracy's model, and (d) compare satellite sensors performance. We also used a high-resolution digital elevation model to extract water elevations values, making it possible to remove topographic effects and estimate non-optimistic errors exclusively from orbital imagery. Our findings evidenced that there is a region where thresholds values can vary without causing accuracy loss. Moreover, by constraining thresholds variation between these limits, accuracy is dramatically improved and outperformed the Otsu method. Finally, the number of scenes employed to optimize a single threshold drastically affects the accuracy, being not appropriate using a single scene once it leads to overfitted threshold values. More than three scenes are recommended.
尽管单阈值仍然被认为是在时空分析中提取水体特征的一种合适且易于操作的技术,但它会导致不可避免的错误。本文使用枚举搜索来优化基于卫星的改进归一化差异水体指数 (MNDWI) 的阈值。我们采用交叉验证方法,并将准确性视为随机变量,以便:(a) 研究其应用相关的不确定性;(b) 估计涉及单阈值的非最优误差;(c) 研究影响模型准确性的主要因素,以及 (d) 比较卫星传感器的性能。我们还使用高分辨率数字高程模型提取水体高程值,从而可以消除地形影响,并仅从轨道图像估计非最优误差。我们的研究结果表明,存在一个阈值值可以变化而不会导致精度损失的区域。此外,通过限制这些限制内的阈值变化,准确性得到了显著提高,并超过了 Otsu 方法。最后,用于优化单个阈值的场景数量会极大地影响准确性,因此不建议仅使用单个场景,因为这会导致过拟合的阈值值。建议使用三个以上的场景。