Simulating the co-emergence of urban spatial structure and commute patterns in an African metropolis: A geospatial agent-based model

《Simulating the co-emergence of urban spatial structure and commute patterns in an African metropolis: A geospatial agent-based model》

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关键字: Urban structure;Location choice;Agent-based modelling;Informal land markets;Land use -transport interaction;Informal urbanism

作者单位: Department of Planning and Environmental Management, University of Manchester, UK;Department of Physical Geography, Institute of Geography, University of Goettingen, Germany;Department of Planning and Environmental Management, University of Manchester, UK;Department of Physical Geography, Institute of Geography, University of Goettingen, Germany

摘要: Urban spatial structure and mobility patterns co-evolve. A fundamental process that underpins the emergent structure of cities and commuting patterns is location choice with respect to housing and employment. Consequently, location choice models constitute important sub-components of land use-and-transport-interaction (LUTI) and urban growth models. This paper documents the development and application of the Metropolitan Location and Mobility Patterns Simulator (METLOMP-SIM). METLOMP-SIM is a geospatial agent-based model that simulates how urban structure and travel patterns co-emerge, as a function of the location decisions of heterogeneous households and individuals within a spatially-explicit urban context. After specifying a generic conceptual model that identifies the model's structure, entities and agents' decision-making framework, METLOMP-SIM is implemented using the Kumasi Metropolis in Ghana, Sub-Saharan Africa as case study. Overall, the implemented model demonstrates that the encoded micro-scale behaviour of households and individuals are able to mimic some macro-scale residential and job location patterns, and patterns of home-work trip flows that closely match patterns in the case study metropolis. The current model represents property and job market dynamics in both their ‘formal’ and ‘informal’ manifestations, making it potentially relevant to dynamic, agent-based LUTI model development and applications in Sub-Saharan African cities.