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Influence of flight altitude and control points in the georeferencing of images obtained by unmanned aerial vehicle
European Journal of Remote Sensing ( IF 3.7 ) Pub Date : 2021-01-10
Lucas Santos Santana, Gabriel Araújo E Silva Ferraz, Diego Bedin Marin, Brenon Dienevam Souza Barbosa, Luana Mendes Dos Santos, Patrícia Ferreira Ponciano Ferraz, Leonardo Conti, Stefano Camiciottoli, Giuseppe Rossi

ABSTRACT

This study aimed to explore the influence of flight altitude, density, and distribution of ground control points (GCPs) on the digital terrain model (DTM) in surveys conducted by unmanned aerial vehicles (UAVs). A total of 144 photogrammetric projects consisting of 399 aerial photos were carried out in a 2 ha area. These photogrammetric projects involved six GCP distributions (edge, center, diagonal, parallel, stratified, and random), six GCP densities, and four flight altitudes (30, 60, 90, and 120 m). The response surface methodology was used to find interference factors and total root-mean-square error (RMSEt) as well. The 60 m flight altitude presented was the most efficient. Central GCP distribution was observed to have low precision. Using stratified and random edge distributions, 10 GCPs are recommended to achieve geometric precision below 0.07 m at any flight height. However, for studies requiring up to 0.07 m precision, the best distribution was parallel with 4 GCPs at any altitude. Diagonal positioning of the GCPs showed RMSEt values below 0.11 m with 4 GCPs at any altitude. A good distribution of GCPs was found to be important, but the density of GCPs per image was more relevant when obtaining a lower RMSEt.



中文翻译:

飞行高度和控制点对无人飞行器获得的图像进行地理配准的影响

摘要

这项研究旨在探讨无人飞行器(UAV)进行的调查中飞行高度,密度和地面控制点(GCP)的分布对数字地形模型(DTM)的影响。在2公顷的区域内共进行了144个摄影测量项目,包括399张航拍照片。这些摄影测量项目涉及六个GCP分布(边缘,中心,对角线,平行,分层和随机),六个GCP密度和四个飞行高度(30、60、90和120 m)。响应面方法还用于查找干扰因子和总均方根误差(RMSEt)。提出的60 m飞行高度是最有效的。观察到中央GCP分布的精度较低。使用分层和随机边缘分布,建议使用10个GCP,以在任何飞行高度下达到0.07 m以下的几何精度。但是,对于要求精度高达0.07 m的研究,最佳分布是在任何高度下都与4个GCP平行。GCP的对角线定位显示在任何高度下都有4个GCP时,RMSEt值低于0.11 m。发现良好的GCP分布很重要,但是当获得较低的RMSEt时,每张图像的GCP密度更为相关。

更新日期:2021-01-11
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