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首页> 外文期刊>International journal of applied earth observation and geoinformation >Comparison of four UAV georeferencing methods for environmental monitoring purposes focusing on the combined use with airborne and satellite remote sensing platforms
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Comparison of four UAV georeferencing methods for environmental monitoring purposes focusing on the combined use with airborne and satellite remote sensing platforms

机译:四UAV地理转移方法对空中和卫星遥感平台结合使用的关注

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This work is aimed at the environmental remote sensing community that uses UAV optical frame imagery in combination with airborne and satellite data. Taking into account the economic costs involved and the time investment, we evaluated the fit-for-purpose accuracy of four positioning methods of UAV-acquired imagery: 1) direct georeferencing using the onboard raw GNSS (GNSSNAV) data, 2) direct georeferencing using Post Processed Kinematic single-frequency carrier-phase without in situ ground support (PPK1), 3) direct georeferencing using Post-Processed Kinematic double-frequency carrier-phase GNSS data with in situ ground support (PPK2), and 4) indirect georeferencing using Ground Control Points (GCP). We tested a multispectral sensor and an RGB sensor, onboard multicopter platforms. Orthophotomosaics at 0.05 m spatial resolution were generated with photogrammetric software. The UAV image absolute accuracy was evaluated according to the ASPRS standards, wherein we used a set of GCPs as reference coordinates, which we surveyed with a differential GNSS static receiver. The raw onboard GNSSNAV solution yielded horizontal (radial) accuracies of RMSEr = 1.062 m and vertical accuracies of RMSEz = 4.209 m; PPK1 solution gave decimetric accuracies of RMSEr = 0.256 m and RMSEz = 0.238 m; PPK2 solution, gave centimetric accuracies of RMSEr = 0.036 m and RMSEz = 0.036 m. These results were further improved by using the GCP solution, which yielded accuracies of RMSEr = 0.023 m and RMSEz = 0.030 m. GNSSNAV solution is a fast and low-cost option that is useful for UAV imagery in combination with remote sensing products, such as Sentinel-2 satellite data. PPK1, which can register UAV imagery with remote sensing products up to 0.25 m pixel size, as WorldView-like satellite imagery, airborne lidar or orthoimagery, has a higher economic cost than the GNSSNAV solution. PPK2 is an acceptable option for registering remote sensing products of up to 0.05 m pixel size, as with other UAV images. Moreover, PPK2 can obtain accuracies that are approximate to the usual UAV pixel size (e.g. co-register in multitemporal studies), but it is more expensive than PPK1. Although indirect georeferencing can obtain the highest accuracy, it is nevertheless a time-consuming task, particularly if many GCPs have to be placed. The paper also provides the approximate cost of each solution.
机译:这项工作旨在环境遥感社区,使用UAV光学框架图像与空中和卫星数据相结合。考虑到所涉及的经济成本和时间投资,我们评估了无人机收购图像的四种定位方法的适当准确性:1)使用船上原始GNSS(GNSSNAV)数据,2)直接地地理使用经过处理的运动单频载波 - 阶段,无需原位接地支持(PPK1),3)使用后处理的运动双频载波 - 阶段GNSS数据直接地地理转移,其原位接地支持(PPK2)和4)间接地地理使用地面控制点(GCP)。我们测试了多光谱传感器和RGB传感器,车载多电平平台。 &使用摄影测量软件生成0.05米的空间分辨率。根据ASPRS标准评估UAV图像绝对精度,其中我们使用一组GCP作为参考坐标,我们用差分GNSS静态接收器进行调查。原始GNSSNAV溶液产生RMSER的水平(径向)精度& = 1.062米,RMSEZ的垂直精度& = 4.209米; PPK1溶液对RMSER的比例精度提供了折叠的粗糙精度。 PPK2溶液,给出了RMSER厘米的厘米厘米且0.036米和RMSEZ& = 0.036米。通过使用GCP溶液进一步改善了这些结果,其产生了RMSER的精度& =0.023μm和rmsez =0.030μm。 GNSSNAV解决方案是一种快速和低成本的选项,可与UAV Imagery相结合的遥感产品,例如Sentinel-2卫星数据。 PPK1,可以使用高达0.25米像素尺寸的遥感产品注册UAV图像,作为WorldView的卫星图像,机载LIDAR或OrthoAgery,具有比GNSSNAV解决方案更高的经济成本。 PPK2是注册高达0.05米像素大小的遥感产品的可接受选项,如其他UAV图像。此外,PPK2可以获得近似于通常的UAV像素大小的精度(例如,在多立体研究中的共同寄存器),但它比PPK1更昂贵。虽然间接地地地球衰减可以获得最高的精度,但是它仍然是耗时的任务,特别是如果必须放置许多GCP。本文还提供了每种解决方案的近似成本。

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