高分辨率遥感图像几何精校正在高山峡谷区1:5万地质填图中的应用

    Application of geometric precision correction based on high-resolution Remote Sensing Image in 1:50000 geological mapping

    • 摘要: 高山峡谷区海拔高、切割深,穿越条件极差,借助高分辨率遥感图像开展1:5万区域地质填图工作具有非常重要的意义。然而市场购置的遥感图像产品与实地位置信息和地形图等工作底图不匹配,其几何精度严重制约地质填图野外调查工作。为解决这一现实问题,采用高分辨率遥感图像SPOT7,以青藏高原柴达木盆地北缘赛什腾山为例开展研究,提出一套高分辨率遥感图像几何精校正技术方法。该方法在高分辨率遥感图像融合配准的基础上,创新半自动化人机交互式地面控制点选取方法,以及典型特征控制点海量选取、空间均匀分布等技术,通过对校正后遥感图像几何精度的反复检查提升,实现了高分辨率遥感图像的几何精校正。该方法校正后的遥感图像充分发挥了遥感技术的先导作用,极大地提高了野外地质填图的工作效率,可为地形复杂地区高分辨率遥感图像几何精校正提供技术参考。

       

      Abstract: The high resolution remote sensing images can play an important role in the 1:50000 geological mapping in the alpine-gorge area with high altitude, deep cutting and poor crossing conditions.However, the remote sensing image products provided by the current market cannot match the working base maps such as field position information and topographic maps, and their geometric accuracy seriously restricts the field investigation of geological mapping.In order to solve this practical problem, a set of geometric precision correction techniques for high resolution remote sensing images is proposed by using high resolution remote sensing image SPOT7 and exemplifying Saishiteng Mountain in the northern margin of Qaidam Basin in Qinghai-Tibet Plateau as an example.Based on the fusion registration of high-resolution remote sensing images, this method innovates the semi-automatic man-machine interactive ground control point selection method, as well as the techniques of mass selection and spatial uniform distribution of typical feature control points.Through repeatedly checking and improving the geometric accuracy of corrected remote sensing images, the geometric precision correction of high-resolution remote sensing images is realized.The corrected remote sensing images give full play to the leading role of remote sensing technology, greatly improve the efficiency of field geological mapping, and can provide technical reference for geometric precision correction of high resolution remote sensing images in complex terrain areas.

       

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