Rahul Dev Garg
Associate Professor
Indian Institute of Technology (IIT) Roorkee
India

Biography
Dr. R.D. Garg has about 19 years of experience in the field of Geoinformatics. His research interests are thermal and microwave remote sensing, sub-surface investigations using ground penetrating radar, GIS and GPS. He has supervised 4 PhDs and more than 30 MTech theses. He has been conferred 'Outstanding Teacher Award' by IIT for excellence in teaching and research.

Abstract
Web GIS based Decision Support System for Optimal Evacuation Route Identification during Flood Disaster

This paper focuses to develop a web based spatial GIS application, which would help people to find the optimal evacuation route during flood. It presents architecture of web based decision support system for an improved evacuation route identification method during flood disaster. Open source GeoServer is used for integrating Web GIS. It first constructs a weighted parameter model by considering road quality and environmental factors. PostGIS is used for spatial database management which contains the preprocessed spatial data. Weighted parameters are given as input to the fuzzy decision support system for building the path model based on the minimum time consumption with safety. The water depth and the availability of high altitude building or area are the most important factors for immediate rescue. Then by using the modified Dijkstra's algorithm, most suitable path for safe and speedy evacuation is delineated. The optimal path is not the shortest path. This method finds the lowest impedance on path based on various factors which are important during flood. The results are found according to the criteria involved. The user friendly interface is developed in open source software. It provides an easy way to query so that a non-GIS person can also view and explore its maps and results, and can understand it in detail. People who live in flood plains, can locate the shelter point at higher altitude which is less vulnerable to the flood water. The timely and easy to understand information will help flood managers and emergency services to take appropriate decision at right time. Future work will focus on real time disaster conditions and realistic factors, to achieve more accurate models and to achieve high quality results.