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| Author(s): |
Renato da Silva Lima
Total Authors: 1
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| Document type: | Doctoral Thesis |
| Press: | São Carlos. |
| Institution: | Universidade de São Paulo (USP). Escola de Engenharia de São Carlos (EESC/SBD) |
| Defense date: | 2003-06-26 |
| Examining board members: |
Antonio Nelson Rodrigues da Silva;
Vania Barcellos Gouvea Campos;
José Fernando Gomes Mendes;
Suely da Penha Sanches;
Ismael Ulysséa Neto
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| Advisor: | Antonio Nelson Rodrigues da Silva; José Fernando Gomes Mendes |
| Abstract | |
One of the main problems faced by brazilian cities is the lack of adequate methodologies for the implementation and rational use of public service facilities (such as schools and health care centers). That was the starting point in the definition of the main objective of the present work, which is the development of a spatial analysis tool for seeking an optimal arrangement of primary health and education facilities, in order to reduce transportation costs. The use of such a tool in the public administration is important not only for planning but also for management purposes. The study starts with an investigation of approaches that have been used in real cases, in cities of different countries, to define health and education facility types and their distribution. A careful analysis of location-allocation concepts and analysis tools for the solution of spatial problems, with particular emphasis on the Spatial Decision Support Systems (SDSS), was also conducted. The system (or methodology) proposed, which was meant to support the process of location of new facilities and also an efficient use of the existing ones while reducing transportation costs, was based on that conceptual framework. The system was directed to the context of brazilian medium-sized cities, where planning concepts are not widely applied and even the databases available are sometimes very limited and frequently outdated. The system design looked for both traditional and innovative approaches and computer-based techniques, such as Cellular Automata (CA) and Artificial Neural Networks (ANN). These techniques, although not yet extensively applied in urban planning and management, seem to be promising alternatives for those activities. The integration of the different tools and techniques was tested in a practical application carried out in the city of São Carlos (SP) and developed in a Geographic Information System (GIS) environment. The results drawn from the application are clear: the main action to reduce the transportation costs in the case studied was a re-distribution of the demand. It was considerable, despite the fact that not a single facility has been added. Another important outcome of the research was the confirmation of the hypothesis that the distinct planning and management tools tested could be used in an integrated approach. Therefore, the methodology discussed here could effectively become a Spatial Decision Support System only by means of software development for building the system interfaces. As a general conclusion, the data gathering problems still seem to be the main barrier for research development in this area. Consequently, the construction of solid and reliable databases is undoubtedly a key point to start any potentially successful project (AU) | |