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IKONOS geometric characterization

机译:IKONOS几何特征

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摘要

The IKONOS spacecraft acquired images on July 3, 17, and 25, and August 13, 2001 of Brookings SD, a small city in east central South Dakota, and on May 22, June 30, and July 30, 2000, of the rural area around the EROS Data Center. South Dakota State University (SDSU) evaluated the Brookings scenes and the USGS EROS Data Center (EDC) evaluated the other scenes. The images evaluated by SDSU utilized various natural objects and man-made features as identifiable targets randomly distribution throughout the scenes, while the images evaluated by EDC utilized pre-marked artificial points (panel points) to provide the best possible targets distributed in a grid pattern. Space Imaging provided products at different processing levels to each institution. For each scene, the pixel (line, sample) locations of the various targets were compared to field observed, survey-grade Global Positioning System locations. Patterns of error distribution for each product were plotted, and a variety of statistical statements of accuracy are made. The IKONOS sensor also acquired 12 pairs of stereo images of globally distributed scenes between April 2000 and April 2001. For each scene, analysts at the National Imagery and Mapping Agency (NIMA) compared derived photogrammetric coordinates to their corresponding NIMA field-surveyed ground control point (GCPs). NLMA analysts determined horizontal and vertical accuracies by averaging the differences between the derived photogrammetric points and the field-surveyed GCPs for all 12 stereo pairs. Patterns of error distribution for each scene are presented.
机译:IKONOS航天器分别于2001年7月3日,17日和25日以及2001年8月13日获得了南达科他州中东部小城市布鲁金斯SD以及2000年5月22日,6月30日和2000年7月30日的图像。在EROS数据中心附近。南达科他州立大学(SDSU)对布鲁金斯场景进行了评估,而USGS EROS数据中心(EDC)对其他场景进行了评估。 SDSU评估的图像将各种自然物体和人造特征作为可识别的目标随机分布在整个场景中,而EDC评估的图像则利用预先标记的人工点(面板点)来提供尽可能最佳的网格分布目标。太空影像公司为每个机构提供了不同处理级别的产品。对于每个场景,将各种目标的像素(线条,样本)位置与实地观察的,调查级的全球定位系统位置进行比较。绘制了每种产品的误差分布图,并制作了各种准确性的统计数据。 IKONOS传感器还获取了2000年4月至2001年4月之间全球分布场景的12对立体图像。对于每个场景,美国国家影像和制图局(NIMA)的分析人员都将得出的摄影测量坐标与相应的NIMA实地调查的地面控制点进行了比较。 (GCP)。 NLMA分析师通过对所有12对立体声对的导出的摄影测量点与现场测量的GCP之间的差异进行平均,确定了水平和垂直精度。给出了每个场景的错误分布模式。

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