Framework of Spatial Decision Support System for Large-Scale Public Building Evacuation

Buildings or constructions are the basis of modern human life. While unexpected and sudden emergencies happen in large-scale public buildings bring great lost of wealth and casualties. How to control such extreme events and make efficient evacuation is quite a problem for emergency planners and decision makers. In this paper, a spatial approach based on Exploratory Spatial Data Analysis (ESDA) technology is described to build a Spatial Decision Support System (SDSS) for large-scale public building evacuation. Method and application of ESDA for building environment spatial risk appraisal is the core algorithmic model for environment analysis module and the basis of evacuation routing optimization. Framework structure of SDSS for large-scale public building evacuation is explicated. SDSS could not only bring emergency routing scheme for evacuees, but also provide reliable environment risk related spatial information for emergency management decision making.

[1]  Mauricio Osorio,et al.  Modeling evacuation planning using A-Prolog , 2005, 15th International Conference on Electronics, Communications and Computers (CONIELECOMP'05).

[2]  Michael Pidd,et al.  CEMPS: a configurable evacuation management and planning system—a progress report , 1993, WSC '93.

[3]  Michael Pidd,et al.  Cemps: Configurable Evacuation Management and Planning System - a Progress Report , 1993, Proceedings of 1993 Winter Simulation Conference - (WSC '93).

[4]  Gunnar G. Løv On the Importance of Building Evacuation System Components , 1998 .

[5]  David Ingle Smith,et al.  Riding the storm: a comparison of uncertainty modelling techniques for storm surge risk management , 2002 .

[6]  Michael Batty,et al.  Modelling Inside GIS: Part 1. Model Structures, Exploratory Spatial Data Analysis and Aggregation , 1994, Int. J. Geogr. Inf. Sci..

[7]  K G Zografos,et al.  Methodological framework for developing decision support systems (DSS) for hazardous materials emergency response operations. , 2000, Journal of hazardous materials.

[8]  A. Siebes,et al.  Data Mining and Statistics , 2000, Computational Intelligence in Data Mining.

[9]  A. Getis The Analysis of Spatial Association by Use of Distance Statistics , 2010 .

[10]  Antony Unwin,et al.  SPIDER - an interactive statistical tool for the analysis of spatially distributed data , 1990, Int. J. Geogr. Inf. Sci..

[11]  L. Anselin Local Indicators of Spatial Association—LISA , 2010 .

[12]  J. Keith Ord,et al.  Spatial Processes Models and Applications , 1981 .

[13]  Michael J. Kevany,et al.  GIS in the World Trade Center attack - trial by fire , 2003, Comput. Environ. Urban Syst..

[14]  Mei-Po Kwan,et al.  Emergency response after 9/11: the potential of real-time 3D GIS for quick emergency response in micro-spatial environments , 2005, Comput. Environ. Urban Syst..

[15]  Padhraic Smyth,et al.  From Data Mining to Knowledge Discovery: An Overview , 1996, Advances in Knowledge Discovery and Data Mining.

[16]  J. Ord,et al.  Spatial Processes: Models and Applications , 1984 .