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首页> 外文期刊>International journal of remote sensing >Optimal flight parameters for unmanned aerial vehicles collecting spatial information for estimating large-scale waste generation
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Optimal flight parameters for unmanned aerial vehicles collecting spatial information for estimating large-scale waste generation

机译:用于收集空间信息以估计大规模废物产生的无人机的最佳飞行参数

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摘要

Large-scale waste and debris from disasters and building construction can cause secondary damage and environmental pollution. Satellite images and the Global Positioning System are being used to calculate the amounts of such waste. However, efficiency in terms of accuracy and cost remains problematic. To solve this problem, this study used an unmanned aerial vehicle (UAV) to build three-dimensional (3D) spatial information for large-scale waste generation. Appropriate parameters were selected to quickly and accurately estimate the amount of waste. Fifty-six scenarios were distinguished according to parameters such as flight altitude, image overlap, and number of ground control points (GCPs). Images were then registered by implementing the SIFT (Scale Invariant Feature Transform) and SfM (Structure from Motion) algorithms to build 3D spatial information and estimate the amount of waste. The accuracy was generally high when flight altitude and image overlap were high, and the number of GCPs was specific. Scenario A, with the lowest flight altitude and overlap, did not yield any registrable images. The results of the flight altitude showed a different tendency from those of existing studies. This could be attributable to the difference in the distance covered on the ground by an image in the width direction, which depended on the characteristics of study sites. Among all the scenarios, D-7 had the highest accuracy, with a root-mean-square error of about 0.08 m. In this scenario, the amount of waste was estimated to be approximately 767,571.3 m(3). The top 10 scenarios in terms of the accuracy of x, y, and z locations displayed similar tendencies with regard to the amount of waste. In contrast, the bottom 15 scenarios showed a variety of results. When the accuracy and flight time of each scenario were considered, scenarios H-3, H-4, and H-5 achieved the highest accuracy in a short time. Thus, these scenarios were the most effective and applicable for estimating the amount of waste. Consequently, parameters such as flight altitude, image overlap, and GCPs need to be considered when estimating large-scale waste associated with a difference in elevation using a UAV.
机译:灾难和建筑施工产生的大量废物和碎屑可能造成二次破坏和环境污染。卫星图像和全球定位系统正在用于计算此类废物的数量。然而,就准确性和成本而言,效率仍然存在问题。为了解决这个问题,本研究使用了无人飞行器(UAV)来建立三维(3D)空间信息,以产生大量废物。选择适当的参数可以快速准确地估计废物量。根据飞行高度,图像重叠和地面控制点(GCP)数量等参数区分了56种情况。然后,通过实施SIFT(尺度不变特征变换)和SfM(运动结构)算法来配准图像,以构建3D空间信息并估计浪费的数量。当飞行高度和图像重叠很高时,精度通常很高,并且GCP的数量是特定的。方案A,具有最低的飞行高度和重叠,没有产生任何可注册的图像。飞行高度的结果显示出与现有研究不同的趋势。这可能归因于图像在宽度方向上在地面上覆盖的距离差异,这取决于研究地点的特征。在所有方案中,D-7的精度最高,均方根误差约为0.08 m。在这种情况下,废物量估计约为767,571.3 m(3)。就x,y和z位置的准确性而言,排名前10位的方案在浪费量方面显示出相似的趋势。相比之下,最底层的15个场景显示了各种结果。考虑每种情况的准确性和飞行时间后,情况H-3,H-4和H-5在短时间内达到了最高准确性。因此,这些方案对于估算废物量是最有效和最适用的。因此,在使用UAV估算与海拔高度差相关的大规模废物时,需要考虑诸如飞行高度,图像重叠和GCP之类的参数。

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