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。
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.
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