测绘学报 ›› 2017, Vol. 46 ›› Issue (10): 1238-1248.doi: 10.11947/j.AGCS.2017.20170337

• 院士论坛 • 上一篇    下一篇

谈大数据时代的“云控制”摄影测量

张祖勋1, 陶鹏杰1,2   

  1. 1. 武汉大学遥感信息工程学院, 湖北 武汉 430079;
    2. 武汉大学资源与环境科学学院, 湖北 武汉 430079
  • 收稿日期:2017-06-21 修回日期:2017-08-26 出版日期:2017-10-20 发布日期:2017-10-26
  • 通讯作者: 陶鹏杰 E-mail:pjtao@whu.edu.cn
  • 作者简介:张祖勋(1937-),男,教授,博士生导师,中国工程院院士、欧亚科学院院士,研究方向为数字摄影测量与遥感。E-mail:zhangzx@cae.cn

An Overview on “Cloud Control” Photogrammetry in Big Data Era

ZHANG Zuxun1, TAO Pengjie1,2   

  1. 1. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China;
    2. School of Resources and Environmental Science, Wuhan University, Wuhan 430079, China
  • Received:2017-06-21 Revised:2017-08-26 Online:2017-10-20 Published:2017-10-26

摘要: 在当今大数据时代,影像数据采集方式的多样化、高效化、便捷化产生的摄影测量影像大数据需要高效、自动与智能的处理。然而,作为传统摄影测量几何定位主要控制数据的外业控制点,其获取的复杂性与低效性仍然是制约摄影测量处理效率的关键因素。针对该问题,本文提出了“云控制”摄影测量的概念,以带有地理空间信息的数据作为几何控制替代外业控制点,通过自动匹配(或配准)获取大量密集的控制信息;并介绍了基于影像、矢量和LiDAR点云的3种“云控制”摄影测量技术;最后对“云控制”摄影测量的应用前景进行了展望并对其问题进行了讨论。

关键词: 摄影测量大数据, “云控制”摄影测量, “云控制”信息的自动提取

Abstract: In the present era of big data, photogrammetric image collection modes are characterized with the progressive course of diversity, efficiency and facilitation, which are producing large sets of photogrammetric image data. They further bring the request for advanced processing with higher level of efficiency, automation and intelligence. However, the efficiency of fundamental photogrammetric processing, known as geometric positioning, is still majorly restricted to control points acquired through complex and inefficient field works. In view of this problem, we promote the concept of "cloud control" photogrammetry, which regards geo-encoded data as geometric control instead of field control points, and is achieved via control information extraction with extensive and intensive automatic matching (or registration) technology. Three control modes will be introduced, considered as image-based-control, vector-map-based-control and LiDAR-point-based-control respectively. By the end of the paper, we provide the discussion on the application prospects and foreseeable problems of "cloud control" photogrammetry.

Key words: photogrammetric big data, “cloud control” photogrammetry, cloud control information extraction

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