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A Markov-Monte Carlo Simulation Model to Support Urban Planning Decisions: A Case Study for Medellín, Colombia

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Applied Computer Sciences in Engineering (WEA 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 915))

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Abstract

The identification of properties and land destinations are key factors in urban planning decisions, especially in rapid-growing urbanized cities. This information is vital for cadaster matters, property taxes calculations, and therefore for the financial sustainability of a city. In this work we present a Markov-Monte Carlo simulation model to predict changes in land destinations. First, a Markov chain is established to identify the transition finite-state matrix of property destinations, and then a Monte Carlo simulation model is used to predict the changes. We present a case study for the city of Medellín, Colombia, using historical information from the cadaster office from 2004 to 2016. Results obtained allow identifying the urban areas with the larger number of changes. Moreover, these results provide support for urban planning decisions related to workforce sizing and visits sequences to the identified areas.

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Acknowledgements

The authors acknowledge the support from the Subsecretaría de Catastro of Medellín, for providing the necessary information for this study.

Author information

Authors and Affiliations

  1. Subsecretaría de Catastro, Secretaría de Gestión y Control Territorial, Municipio de Medellín, Colombia

    Julián Andrés Castillo

  2. Departamento de Ingeniería Industrial, Facultad de Ingeniería, Universidad de Antioquia, Medellín, Colombia

    Yony Fernando Ceballos & Elena Valentina Gutiérrez

Authors
  1. Julián Andrés Castillo
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  2. Yony Fernando Ceballos
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  3. Elena Valentina Gutiérrez
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Corresponding author

Correspondence to Julián Andrés Castillo .

Editor information

Editors and Affiliations

  1. Department of Industrial Engineering, Universidad Distrital Francisco José de Caldas, Bogotá, Colombia

    Juan Carlos Figueroa-García

  2. Industrial Engineering Department, Univ. Distrital Francisco José de Caldas, Bogotá, Colombia

    Eduyn Ramiro López-Santana

  3. Department of Industrial Engineering, Universidad Distrital Francisco José de Caldas, Bogotá, Colombia

    José Ignacio Rodriguez-Molano

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Castillo, J.A., Ceballos, Y.F., Gutiérrez, E.V. (2018). A Markov-Monte Carlo Simulation Model to Support Urban Planning Decisions: A Case Study for Medellín, Colombia. In: Figueroa-García, J., López-Santana, E., Rodriguez-Molano, J. (eds) Applied Computer Sciences in Engineering. WEA 2018. Communications in Computer and Information Science, vol 915. Springer, Cham. https://doi.org/10.1007/978-3-030-00350-0_29

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  • DOI: https://doi.org/10.1007/978-3-030-00350-0_29

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  • Online ISBN: 978-3-030-00350-0

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