Use of Big Data software in architecture and urban-territorial planning
A frequent problem in architecture and urban-territorial planning is to be able to find groups of elements with homogeneous characteristics. In architecture, building/construction classifications are deduced from a number of parameters or variables; and if the urban structure is analyzed, it is poss...
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| Autores principales: | , , , |
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| Formato: | Online |
| Lenguaje: | spa |
| Publicado: |
Universidad Nacional del Nordeste. Facultad de Arquitectura y Urbanismo
2020
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| Acceso en línea: | https://revistas.unne.edu.ar/index.php/crn/article/view/4624 |
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| Sumario: | A frequent problem in architecture and urban-territorial planning is to be able to find groups of elements with homogeneous characteristics. In architecture, building/construction classifications are deduced from a number of parameters or variables; and if the urban structure is analyzed, it is possible to identify homogeneous areas according to the type of land use, services coverage, among other possible aspects. When the volume of data to be processed is such that it cannot be analyzed by conventional methods, it is necessary to use Big data techniques. In this work, a framework for Big data (Apache Spark) will be used to discover homogeneous areas in terms of coverage of urban basic services of infrastructure and sanitation. Identifying such areas will allow to locate places with similar benefits, infer new demands based on possible urban growths and identify places on the periphery where the city can grow, among other possible uses. |
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