The use of mobile devices and the development of geo-positioning technologies make applications that use location-based services very attractive and useful. These applications are composed of sensors that generate various and heterogeneous spatio-temporal data. Exploiting this spatio-temporal data to support video surveillance systems remains a relevant purpose for video content filtering. Since the data processed in such a context are heterogeneous (indoor and outdoor environment, various position types and reference systems, various data format), interoperability and management of these data remains a problem to be solved. In this paper, we define an approach that integrates camera location and field of view metadata, mobile objects trajectories, and metadata from video content analysis algorithms (e.g. detection and movement of mobile objects) to address problems related to processing of huge amount of data (big data) generated by CCTV systems. We propose a new generic trajectory based query in order to handle trajectory segment's heterogeneity for both environments (indoor and outdoor). The proposed data model integrate multi-source metadata and enable to handle interoperability issue of data. Our querying mechanism enable to automatically retrieve video segments that could contain relevant information for the CCTV operator (suspects, trajectories, etc.). We provide an experimental evaluation demonstrating the utility of our approach in a real-world case. Results show that the proposed approach enhances the efficiency of investigators by reducing the search space, as the operator will analyze only the relevant data, therefore he needs less time for video processing (video reviewing).