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Mapping topo-bathymetry of transparent tufa lakes using UAV-based photogrammetry and RGB imagery

机译:使用基于UAV的摄影测量和RGB图像映射透明TUFA湖泊的Topo-Bathymetry

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摘要

Seasonal or interannual precipitation differences lead to changes in the water level of a tufa lake, while the underwater topography affects its local depth. Therefore, topo-bathymetry is important to study and protect the aquatic environment of tufa lakes. However, traditional field-based topo-bathymetric surveying methods (e.g., sounding rod or sonar) inevitably disturb the fragile lake ecosystem. In recent years, the emerging remote sensing technology of unmanned aerial vehicles (UAV) has provided a cost-effective solution for measuring topobathymetry without disturbance. In this paper, taking Spark Lake in Jiuzhaigou, China, as an example, we captured red-green-blue (RGB) images using a fixed-wing UAV and produced a digital elevation model (DEM) prior to the Jiuzhaigou Earthquake using Structure-from-Motion (SfM) photogrammetry. The underwater topography of Spark Lake was obtained by refraction correction and water color inversion based on the DEM and orthophoto, respectively. For refraction correction, a water depth correction model based on Snell's Law was used. For water color inversion, general band ratio models were replaced by a band difference model (blue band-green band). The qualities of the resulting DEMs produced by the two methods were evaluated against the topography of the drained Spark Lake after the earthquake, and the corresponding DEMs of difference (DoD) were also analyzed. The coefficient of determination (R2) and root mean square error (RMSE) are 0.88 and 1.32 m for refraction correction, and 0.86 and 1.37 m for water color inversion, respectively. The results demonstrated the feasibility and effectiveness of applying UAV-acquired RGB imagery and the two optical remote sensing methods to topo-bathymetric mapping of transparent tufa lakes. (C) 2021 Elsevier B.V. All rights reserved.
机译:季节性或续沉淀差异导致涂沱湖水位的变化,而水下地形影响其局部深度。因此,Topo-Bathymetry对研究和保护Tufa Lakes水生环境非常重要。然而,传统的基于领域的Topo-Bathymetric测量方法(例如,发声杆或声纳)不可避免地打扰脆弱的湖泊生态系统。近年来,无人驾驶飞行器(UAV)的新出现遥感技术提供了一种经济高效的解决方案,用于测量无干扰的胸甲。在本文中,在九寨沟,中国的火花湖,作为一个例子,我们使用固定翼的无人机捕获了红绿蓝(RGB)图像,并在九寨沟地震之前使用结构生产了数字高度模型(DEM) - 来自运动(SFM)摄影测量。 Spark Lake的水下地形分别通过基于DEM和Orthophoto的折射校正和水颜色反转而获得。对于折射校正,使用了基于Snell定律的水深校正模型。对于水色反转,通用频带比模型被带差模型(蓝色带 - 绿色带)所取代。通过两种方法产生的所得DEM的质量对地震后排出的火花湖的形貌进行评估,并且还分析了相应的差异DEM(DOD)。用于折射校正的测定系数(R2)和均方根误差(RMSE)分别为0.88和1.32μm,分别为0.86和1.37m,用于水彩反转。结果表明,应用无人机获得的RGB图像和两种光学遥感方法对透明TUFA湖泊的Topo-Bandetric映射来实现的可行性和有效性。 (c)2021 elestvier b.v.保留所有权利。

著录项

  • 来源
    《Geomorphology》 |2021年第15期|107832.1-107832.11|共11页
  • 作者单位

    Southwest Univ Sch Geog Sci Chongqing Jinfo Mt Karst Ecosyst Natl Observat & Chongqing 400715 Peoples R China|Southwest Univ Chongqing Engn Res Ctr Remote Sensing Big Data Ap Sch Geog Sci Chongqing 400715 Peoples R China;

    Southwest Univ Sch Geog Sci Chongqing Jinfo Mt Karst Ecosyst Natl Observat & Chongqing 400715 Peoples R China|Southwest Univ Chongqing Engn Res Ctr Remote Sensing Big Data Ap Sch Geog Sci Chongqing 400715 Peoples R China;

    Southwest Univ Sch Geog Sci Chongqing Jinfo Mt Karst Ecosyst Natl Observat & Chongqing 400715 Peoples R China|Southwest Univ Chongqing Engn Res Ctr Remote Sensing Big Data Ap Sch Geog Sci Chongqing 400715 Peoples R China;

    Chinese Acad Sci Inst Geog Sci & Nat Resources Res Beijing 100101 Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Tufa lake; Bathymetry; Unmanned aerial vehicle (UAV); Refraction correction; Band difference model;

    机译:Tufa Lake;沐浴浴室;无人驾驶飞行器(无人机);折射校正;带差模型;

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