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Understanding the errors in input prescription maps based on high spatial resolution remote sensing images

机译:基于高分辨率的遥感影像了解输入处方图中的错误

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The aim of this study was to determine the positional accuracy of GeoEye-1 images and how it affects the delineation of the input prescription map (IPM) for site-specific strategies. Seven panchromatic and multi-spectral GeoEye-1 satellite images were taken over the LaVentilla village area (Andalusia, Spain), from April to October 2010, at an interval of approximately 3–4 weeks. Sixteen hard-edge ground control points (GCPs) were geo-referenced using a sub-decimetre DGPS. Each DGPS-GCP position was compared with the corresponding co-ordinates for each image to determine the position error (PE) and error direction angle ( Upphitextge° {Upphi_{text{ge}}}^{^circ } ). The PE and Upphitextge° {Upphi_{text{ge}}}^{^circ } for each GCP varied slightly for any given GeoEye-1 image and the overall PE among images estimated through the root mean square error (RMSE) varied considerably. RMSE ranged from approximately 2–9 m and from 3.5 to 9 m for the panchromatic and multi-spectral images studied, respectively, and the average was approximately 6.0 m for each of the series of images. Consequently, the geo-referencing of GeoEye-1 images is recommended to increase the positioning accuracy. Conventional geo-referencing using GCPs provided an average RMSE of 2 m for the panchromatic and 3.5 m for the multi-spectral images. The AUGEO System® geo-referencing of the 4-May GeoEye-1 image provided an RMSE of 0.75 m for the panchromatic and 2.70 ± 1.30 m for the multi-spectral images. The IPM delineated from remote-sensed images takes up the image geo-referencing error and, consequently, each micro-plot does not coincide with its corresponding ground-truth micro-plot. In this report, the percentage of non-overlapping area (%NOA) has been developed as a function of the PE/RMSE, α° (the angle between Φge and the operating direction, Φop), and the micro-plot size. The %NOA consistently increased as the RMSE and α° increased, and it decreased as the micro-plot width or length increased. The decision about micro-plot size should be based on the RMSE, α°, and the maximum admissible %NOA. In the case of the GeoEye-1 images studied with an average RMSE of 6 m, a micro-plot size of 6 × 30 m would have yielded an IPM inaccuracy (%NOA) of approximately 5 %, assuming an α° = 0°.
机译:这项研究的目的是确定GeoEye-1图像的位置准确性,以及它如何影响针对特定地点策略的输入处方图(IPM)的轮廓。 2010年4月至2010年10月,在LaVentilla村庄地区(西班牙安达卢西亚)拍摄了七张全色和多光谱的GeoEye-1卫星图像,间隔大约3-4周。使用亚分米DGPS对16个硬边地面控制点(GCP)进行了地理参考。将每个DGPS-GCP位置与每个图像的相应坐标进行比较,以确定位置误差(PE)和误差方向角(Upphi text ° < / sup> {Upphi_ {text {ge}}} ^ {^ circ})。每个GCP的PE和Upphi textge ° {Upphi_ {text {ge}}} ^ {^ circ}对于任何给定的GeoEye都略有不同-1图像和通过均方根误差(RMSE)估计的图像中的整体PE差异很大。对于所研究的全色和多光谱图像,RMSE的范围分别从大约2–9 m和3.5至9 m,并且每个系列图像的均值大约为6.0 m。因此,建议使用GeoEye-1图像的地理参考以提高定位精度。使用GCP的常规地理参考为全色图像提供2 m的平均RMSE,为多光谱图像提供3.5 m的平均RMSE。 4月5日的GeoEye-1图像的AUGEO System ®地理参考为全色图像提供了RMS 0.75 m,多光谱图像提供了2.70±1.30 m的RMSE。从遥感图像中划定的IPM占用了图像地理参考误差,因此,每个微图与相应的地面微图不重合。在本报告中,非重叠区域的百分比(%NOA)已作为PE / RMSE的函数α°(Φ ge 与工作方向之间的角度Φ op ),以及微图尺寸。随着RMSE和α°的增加,%NOA持续增加,而随着微图宽度或长度的增加,NONO%持续下降。有关微图大小的决定应基于RMSE,α°和最大允许%NOA。对于平均RMSE为6 m的GeoEye-1图像进行研究,假设α°= 0°,则6×30 m的微图尺寸将产生约5%的IPM误差(%NOA) 。

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