Simulating Urban Growth with Raster and Vector Models: A Case Study for the City of Can Tho, Vietnam View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2017

AUTHORS

Patrick Taillandier , Arnaud Banos , Alexis Drogoul , Benoit Gaudou , Nicolas Marilleau , Quang Chi Truong

ABSTRACT

Urban growth has been widely studied and many models (in particular Cellular Automata and Agent-Based Models) have been developed. Most of these models rely on two representations of the geographic space: raster and vector. Both representations have their own strengths and drawbacks. The raster models are simpler to implement and require less data, which explains their success and why most of urban growth models are based on this representation. However, they are not adapted to microscopic dynamics such as, for example, the construction of buildings. To reach such goal, a vector-based representation of space is mandatory. However, very few vector models exist, and none of them is easily adaptable to different case studies. In this paper, we propose to use a simple raster model and to adapt it to a vector representation of the geographic space and processes allowing studying urban growth at fine scale. Both models have been validated by a case study concerning the city of Can Tho, Vietnam. More... »

PAGES

21-38

References to SciGraph publications

Book

TITLE

Agent Based Modelling of Urban Systems

ISBN

978-3-319-51956-2
978-3-319-51957-9

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-51957-9_2

DOI

http://dx.doi.org/10.1007/978-3-319-51957-9_2

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1012261150


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