Application of predictive models for territorial planning in Pasto, Colombia

Jheison Edilson Arteaga Quistial, Miguel Ángel Velásquez Bravo and Omar Alexander Revelo Zambrano

Land and Architecture, 2024, vol. 3, 110

Abstract: The research analysed urban growth in the city of Pasto between 2000 and 2022. The need to properly manage large volumes of data using technological tools that would allow for the organisation, analysis and prediction of urban expansion behaviour was identified. To this end, a predictive model was implemented, supported by software developed with open-source technologies such as Python and Laravel, with an interface based on HTML and CSS. This software facilitated the identification of growth patterns through data mining and multi-criteria analysis techniques. The project received institutional support from the University of Nariño, as well as the participation of teachers and researchers from the fields of engineering and architecture. In addition, data was collected both digitally and through fieldwork in order to build a reliable repository to feed the information system. The study showed that urban growth is a multifactorial process influenced by social, economic, demographic and political variables. Finally, it was concluded that the predictive model made it possible to determine interactive scenarios of urban expansion and offered an effective tool for territorial planning. The results confirmed that it is possible to apply methodologies such as EMC and information systems to support strategic decisions in urban planning.

Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:dbk:landar:v:3:y:2024:i::p:110:id:1056294la2024110

DOI: 10.56294/la2024110

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