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Geometry accuracy of DSM in water body margin obtained from an RGB camera with NIR band and a multispectral sensor embedded in UAV

机译:用NIR带和嵌入UAV的RGB摄像机获得水体边缘中DSM的几何精度和UAV中的多光谱传感器

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摘要

The photogrammetry techniques are known to be accessible due to its low cost, while the geometric accuracy is a key point to ensure that models obtained from photogrammetry are a feasible solution. This work evaluated the discrepancies in 3D (DSM) and 2D (orthomosaic) models obtained from photogrammetry using control points (GCPs) near a reflective/refractive area (water body), where the objective was to evaluate these points, analysing the independence, normality and randomness and other basic statistic. The images were obtained with a 16 MP Canon PowerShot ELPH 110S with a modified NiR band and a multispectral sensor Parrot Sequoia, both embedded in a hex-rotor UAV in flight over the Unisinos University’s artificial lake in the city of São Leopoldo, Rio Grande do Sul, Brazil. Due the distribution of the data found to be not normal, we applied non-parametric tests Chebyshev’s Theorem and the Mann–Whitney’s U test, where it showed that the values obtained from Sequoia DSM presented significant similarities with the values obtained from the GCP’s considering the confidence level of 95%; however, this was not confirmed for the model generated from a Canon camera, showing that we found better results using the multispectral Parrot Sequoia.
机译:摄影测量技术是已知的可访问由于其成本低,而几何精度是一个关键点,以确保从摄影获得的模型是一个可行的解决方案。这项工作评估的差异在3D(DSM)和2D使用摄影测量控制点(控制点)附近的一个反射/折射区域(水体),其中目的是评估这些点获得(orthomosaic)模型,分析该独立性,常态和随机性等基本统计。与修改的NIR频带和多光谱传感器鹦鹉红杉一个160万像素的佳能的PowerShot ELPH 110S获得的图像,无论是嵌入在十六进制转子无人机在城市圣保罗波尔多的飞越Unisinos大学的人工湖,南里奥格兰德州,巴西。由于数据的分布发现不正常的,我们采用非参数检验切比雪夫定理和曼 - 惠特尼U检验,它表明,红杉DSM获得的数值呈现显著相似之处从GCP的考虑所得到的值95%的置信水平;然而,这并没有证实从佳能相机生成的模型,表明我们发现更好的结果使用多光谱鹦鹉红杉。

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