Rana, S.; (2005) Use of GIS for planning visual surveillance: an analogy to maximum coverage problem. Presented at: Centre for Transport Studies Research Seminars, UCL (University College London), London, UK.

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Abstract

Visual Surveillance is now an essential part of the urban infrastructure in cities like London. One of the primary aims in visual surveillance is to ensure a maximum visual coverage with the least number of surveillance installations, which is analogous to the maximal coverage problem. Starting of with a brief description about the types of visual surveillance (artificial and natural), I will give examples of the rapid spread of visual surveillance. The examples will highlight the traditional approach in the layout of observers in artificial visual surveillance (e.g. CCTV camera), which involves an iterative, manual and gut-feel process of trying various layouts until a satisfactory solution has been found, often producing too many surveillance installations. I will demonstrate how a GIS, can be used to identify the optimal number and locations of observers, ensuring complete visual coverage using an automated technique, namely Rank and Overlap Elimination (ROPE). The ROPE technique is essentially a greedy-search method, which iteratively selects the most visibly dominant observer with minimum overlapping vistas. The talk will also delve a little into measurements to characterise the shape of open spaces, relevant in assessing natural surveillance. One of the key features of the talk will be a demonstration of Isovist Analyst, which is a customised interface to popular geographical information system ArcView, for planning artificial and natural surveillance in indoor and outdoor open spaces, with arbitrary geometry and topology.

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