Wetlands play a significant role in flood mitigation. Remote sensing technologies as an efficient and accurate approach have been widely applied to delineate wetlands. Supervised classification is conventionally applied for remote sensing technologies to improve the wetland delineation accuracy. However, performing supervised classification requires preparing the training data, which is also considered time-consuming and prone to human mistakes. This paper presents a deterministic topographic wetland index to delineate wetland inundation areas without performing supervised classification. The classic methods such as Normalized Difference Vegetation Index, Normalized Difference Water Index, and Topographic Wetness Index were chosen to compare with the proposed deterministic topographic method on wetland delineation accuracy. The ground truth sample points validated by Google satellite imageries from four different years were used for the assessment of the delineation overall accuracy. The results show that the proposed deterministic topographic wetland index has the highest overall accuracy (98.90%) and Kappa coefficient (0.641) among the selected approaches in this study. The findings of this paper will provide an alternative approach for delineating wetlands rapidly by using solely the LiDAR-derived Digital Elevation Model.

中文翻译：

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基于激光雷达DEM的确定性地形湿地指数划定开放水域湿地

湿地在缓解洪水方面发挥着重要作用。遥感技术作为一种高效、准确的方法，已被广泛应用于湿地划定。监督分类通常应用于遥感技术以提高湿地划定精度。然而，执行监督分类需要准备训练数据，这也被认为是耗时且容易出现人为错误的。本文提出了一种确定性地形湿地指数，用于在不进行监督分类的情况下划定湿地淹没区。选择归一化差异植被指数、归一化差异水指数和地形湿度指数等经典方法与提出的确定性地形方法对湿地划定精度进行比较。由 Google 卫星图像验证的四个不同年份的地面实况样本点用于评估描绘的整体准确性。结果表明，在本研究选择的方法中，所提出的确定性地形湿地指数具有最高的总体准确度（98.90%）和 Kappa 系数（0.641）。本文的研究结果将为仅使用 LiDAR 衍生的数字高程模型快速描绘湿地提供另一种方法。