Low Cost Technique of Enhancement Georeferencing for UAV Linear Projects

Elsheshtawy M. Amr, G. Larisa, Elshewy A. Mohamed
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Abstract

Global positioning System (GPS) on Unmanned Aerial Vehicles (UAV) platform depend on MEMS (Micro Electro Mechanical Systems) technology with 10 m accuracy at UAV camera position at shooting time. However, obstacles to GPS signal at the finest flight altitude might avoid accurate retrieval of camera station positions. The aim of this investigation is getting accurate photogrammetric products in UAV linear projects by improving the georeferencing, using a little number of Ground Control Points (GCPs) in a small part and improved camera station positions. This technique is low cost and helpful in disasters especially in projects that cannot be distributing GCPs all over it. DJI PHANTOM 4 PRO acquired 390 images in three flight lines with average flight altitude about 40 m along 1000 m length of study area. The ground sample distance (GSD) is about 1.2 cm. The average end lap and side lap are about 80%. The dimension of area covered by this area is 1000 m by 90 m. Methodology of enhancement GPS auxiliary data is by using Linear Relation (LR) model. In LR model, correlation for the same specified images between the auxiliary by GPS on UAV platform and computed photo centers coordinates through georeferencing using a little of GCPs in small part of project has been determined. The specified images only contained GCPs, which are used in georeferencing. Moreover, using LR model to generate new coordinate values for the rest images to use them in georeferencing. The errors assessment was done using 86 checkpoints (CPs) not used in georeferencing distributed all over the study area. The using of the generated photo centers coordinates by LR model with the four GCPs gives accurate results in georeferencing better than using only the same four GCPs.
无人机线性项目的低成本增强地理参考技术
无人机(UAV)平台上的全球定位系统(GPS)依赖于MEMS(微电子机械系统)技术,在拍摄时无人机相机位置精度为10米。然而,在最佳飞行高度,GPS信号的障碍可能会避免准确检索摄像站位置。本研究的目的是通过改进地理参考,在一小部分使用少量地面控制点(gcp)和改进摄像站位置,在无人机线性项目中获得精确的摄影测量产品。这种技术成本低,在灾难中很有帮助,特别是在无法在所有地方分发gcp的项目中。DJI PHANTOM 4 PRO在研究区域1000 m长度的3条飞行线上获得了390张图像,平均飞行高度约为40 m。地样距离(GSD)约1.2 cm。平均端圈和侧圈约为80%。这个区域所覆盖的面积是1000米乘90米。GPS辅助数据增强的方法是采用线性关系模型。在LR模型中,利用一小部分项目的一小部分gcp进行地理参考,确定了无人机平台上GPS辅助与计算的照片中心坐标之间的相同指定图像的相关性。指定的图像仅包含用于地理参考的gcp。此外,利用LR模型对剩余图像生成新的坐标值,用于地理参考。使用分布在整个研究区域的86个未用于地理参考的检查点(CPs)进行误差评估。将LR模型生成的照片中心坐标与4个gcp结合使用,在地理参考方面比仅使用相同的4个gcp获得更准确的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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