Location Suitability Maps Based on the LSP Method


Michalis Andreas Pittas

Oral Defence Date: 

Wednesday, May 12, 2010 - 16:30


TH 331


4:30 PM


Profs. Dujmovic and Yang


In this project, we developed a web application which generates suitability maps for urban areas. Suitability maps help users to choose the most appropriate location in an urban area according to their specific needs. Recent developments in map technologies and data gathering methods enabled large enterprises, like Google, to produce web based maps that provide locations of points of interest (POI) in all urban areas in the USA. In addition, Google has developed an open source API that allows developers to embed Google Maps in web pages using JavaScript. The API provides a number of utilities for manipulating maps and adding content to the map through a variety of services, allowing one to create robust map applications on websites. Suitability maps are based on user criteria. In this project we create criteria using a soft computing evaluation method called LSP (Logic Scoring of Preference). Our software enables users to make criteria that combine mandatory and desired requirements, adjustable relative importance, and specific distance requirements for each selected POI. We chose web based technologies for the implementation to create a tool with high availability over the internet. We use a backend LSP decision making engine and a frontend PHP based API which accepts http requests. Our application gathers data from Google maps and the user, and in turn sends the data to the LSP server which returns the evaluation scores to the application. The resulting suitability maps are realized as a color based, grid divided, overlay on top of the Google maps. The displayed format allows the user to easily understand and evaluate an area of interest. This application can be utilized in a variety of ways, from simple individual area evaluation to real estate property value estimations.

Michalis Andreas Pittas

Suitability maps, LSP, points of interest, urban area evaluation