MODELING SETTLEMENT PATTERNS IN REAL TERRITORIES

Joaquim Carvalho (), Rui L. Lopes () and João Tojo ()
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Joaquim Carvalho: Centro de Informática e Sistemas da Universidade de Coimbra, Polo II — Pinhal de Marrocos, 3030-290 Coimbra, Portugal
Rui L. Lopes: Centro de Informática e Sistemas da Universidade de Coimbra, Polo II — Pinhal de Marrocos, 3030-290 Coimbra, Portugal
João Tojo: Centro de Informática e Sistemas da Universidade de Coimbra, Polo II — Pinhal de Marrocos, 3030-290 Coimbra, Portugal

Advances in Complex Systems (ACS), 2011, vol. 14, issue 04, 549-565

Abstract: This paper, describes an agent based model of the spreading of a population over a territory. The models aims at reproducing a distribution of settlements with statistical and spatial characteristics similar to a historically produced pattern. The model operates on a representation of a real territory, taking into account hydrography and relief. The two main goals are to obtain a rank size distribution of the size of settlements which corresponds to a power law (also known as the Zipf Law of settlements) and to place the settlements in the territory in patterns that are close to the real ones, in zones where settlements were the result of a long historical process. The goal of the project was to demonstrate that a set of relatively simple rules could produce a complex pattern, similar to the result of a long and complex historical process. Therefore, it is an assumed reductionist approach.Our conclusions show that a simple territorial logic, taking into account the quality of land, accessibility, population growth and migration preferences could reproduce Zipf distributions and interesting patterns of agent flow among the settlements created. However, achieving spatial patterns closer to the historical record needs an extra dimension involving field of sight. The best results were achieved by creating an artifical population which chooses to create settlements in places where a wide field of view exists of quality territory.

Keywords: Settlement; pattern; Zipf; multi-agent; self-organization (search for similar items in EconPapers)
Date: 2011
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DOI: 10.1142/S021952591100313X

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