In recent years, more than one billion cameras have been actively used on moving platforms, and various video analytics applications for moving cameras are emerging in diverse areas. Each of these applications can generate very large datasets to analyze. In this paper, we present practical approaches to handle and summarize the video content from moving cameras and use the application of unmanned aerial vehicles (UAVs) as an example. Our system is enabled by a geographic information system (GIS), and video summarization is used to generate efficient representations of videos on the basis of moving object detection and tracking. The approach automatically creates a panorama for videos and includes a novel registration method we developed for normalizing 3D distortion. Our experimental results on the UAV dataset show that we can accomplish a 10,000-fold data reduction without losing significant activities of interest. We also present a summary of the emerging landscape of mobile video analytics and how it may evolve in conjunction with other distributed mobile and static sensor networks.