With the increasing threats and damages from the natural and man-made hazards, emergency response has become a critical challenge to the smart management of modern cities. Due to limited human resources, how to correctly and quickly assess the priority of disaster relief operations remains a major issue to the disaster management. While the emergency response team may continuously receive lots of disaster information from various sources, they are required to validate whether the reported situations is real or not. CCTV systems are one of the primary references for visually presenting the status in reality. However, current maps of CCTV are usually presented in 2D, such that the monitored spatial coverage is also restricted to 2D. From a 3D perspective, this paper proposes to integrate the GIS-based urban data and the field of view (FOV) of CCTV for improving the collection, management and decision making during emergency response. As the pressure for making prompt and correct decision is often overwhelming, the key issue is to find the best CCTV as soon as possible. Although the current result is only preliminary, the proposed approach demonstrates the advantages of enabling a “real” 3D spatial illustration about the spatial coverage information of CCTV systems by linking it to the features in the real world. With such standardized metadata for FOV available, further analysis can be readily developed, such as quickly determine if a feature is visible, if a reported disaster situation can be validated, and assess the area not covered by the current CCTV systems. By including the disaster events from the historical database, the proposed approach allows the responsible agencies to assess if the deployment and management of current CCTV systems can provide a satisfactory spatial coverage for the cities in the mitigation phase.
CITATION STYLE
Hong, J. H., Lu, Y. H., & Chen, C. H. (2019). The use of CCTV in the emergency response: A 3D GIS perspective. In International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives (Vol. 42, pp. 19–25). International Society for Photogrammetry and Remote Sensing. https://doi.org/10.5194/isprs-archives-XLII-4-W15-19-2019
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