Can geocomputation save urban simulation? Throw some agents into the mixture, simmer and wait ...

There are indications that the current generation of simulation models in practical, operational uses has reached the limits of its usefulness under existing specifications. The relative stasis in operational urban modeling contrasts with simulation efforts in other disciplines, where techniques, theories, and ideas drawn from computation and complexity studies are revitalizing the ways in which we conceptualize, understand, and model real-world phenomena. Many of these concepts and methodologies are applicable to operational urban systems simulation. Indeed, in many cases, ideas from computation and complexity studies—often clustered under the collective term of geocomputation, as they apply to geography—are ideally suited to the simulation of urban dynamics. However, there exist several obstructions to their successful use in operational urban geographic simulation, particularly as regards the capacity of these methodologies to handle top-down dynamics in urban systems. This paper presents a framework for developing a hybrid model for urban geographic simulation and discusses some of the imposing barriers against innovation in this field. The framework infuses approaches derived from geocomputation and complexity with standard techniques that have been tried and tested in operational land-use and transport simulation. Macro-scale dynamics that operate from the topdown are handled by traditional land-use and transport models, while micro-scale dynamics that work from the bottom-up are delegated to agent-based models and cellular automata. The two methodologies are fused in a modular fashion using a system of feedback mechanisms. As a proof-of-concept exercise, a micro-model of residential location has been developed with a view to hybridization. The model mixes cellular automata and multi-agent approaches and is formulated so as to interface with meso-models at a higher scale

Cellular automata and urban studies: a literature survey

Este artigo apresenta uma pesquisa bibliográfica sobre a técnica matemática de autómatos celulares (CA) e a sua aplicação a estudos urbanos. Os modelos baseados em CA são actualmente alvo de intensa investigação não só em termos teóricos como também na sua aplicação operacional. Diversos modelos são já aplicados a diversas áreas urbanas e regiões metropolitanas em todo o mundo. É feita a apresentação da formulação clássica de CA bem como das suas primeiras aplicações a problemas geográficos e urbanos, sendo ainda discutidas as principais evoluções da técnica. É apresentada uma série de aplicações de modelos baseados em CA e é dedicada uma atenção particular às suas medidas de desempenho e a diversas abordagens de calibração dos modelos.Peer Reviewe

State of the Art on Artificial Intelligence in Land Use Simulation

[Abstract] This review presents a state of the art in artificial intelligence applied to urban planning and particularly to land-use predictions. In this review, different articles after the year 2016 are analyzed mostly focusing on those that are not mentioned in earlier publications. Most of the articles analyzed used a combination of Markov chains and cellular automata to predict the growth of urban areas and metropolitan regions. We noticed that most of these simulations were applied in various areas of China. An analysis of the publication of articles in the area over time is included.This project was supported by the General Directorate of Culture, Education and University Management of Xunta de Galicia (ref. ED431G/01 and ED431D 2017/16), the Spanish Ministry of Economy and Competitiveness via funding of the unique installation BIOCAI (UNLC08-1E-002 and UNLC13-13-3503), and the European Regional Development Funds (FEDER). CITIC, as Research Center accredited by Galician University System, is funded by “Consellería de Cultura, Educación e Universidade from Xunta de Galicia,” supported in an 80% through ERDF Funds, ERDF Operational Programme Galicia 2014–2020, and the remaining 20% by “Secretaria Xeral de Universidades” (grant no. ED431G 2019/01)Xunta de Galicia; ED431G/01Xunta de Galicia; ED431D 2017/16Xunta de Galicia; ED431G 2019/0

A theory driven, spatially explicit agent-based simulation to model the economic and social implications of urban regeneration

We model the economic mechanics of housing regeneration employing the rent-gap theory proposed by Neil Smith in 1979. We discuss the conditions for successful regeneration in theory, using an abstract representation of a city, then try and evaluate the possible outcomes of an actual regeneration programme in Salford, England in terms of property prices and area social composition

Multi-criteria expert based analysis for ranking the urban gentrification drivers in developing countires

More than 40 years have passed since the term “gentrification” was coined by Ruth Glass (Torrens & Nara, 2007). Originating from Britain, gentrification has become popular concept in developed countries and much research has been conducted in the US, Europe, Canada and Australia since the 1970s on gentrification of the inner cities (Bounds & Mourris, 2008; Hamnett, 1991). Research was also conducted in some premier cities of developing world such as Mexico, Istanbul, Ankara and Seoul (Ha, 2004; Ergun, 2004; Guzey, 2006; Jones & Varley, 1999). Most of the gentrification researchers come to the point that appearance of the already formulated origins of gentrification are time and place-specific (Guzey, 2006), as this urban phenomenon through an evolutionary process found different aspects and drivers. The reason is that through its evolution from late 1950s different preconditions have brought different logics and outcomes in different geographies. Thus it is worth to threat gentrification as a complex phenomenon by sophisticated tools to examine the ideas and hypotheses behind it. In this research it is intended to use the analytical network process (ANP) integrated with GIS to figure out the gentrification drivers in Kuala Lumpur inner city and rank them according to their influence. This would provide a decision support system as tool par excellence for exploring the expert idea based on time and place. Besides, the methodology will foster the future works on modeling and simulating the behaviors of gentrification in developing countries that have not been applied hitherto

Gentrification and models for real estate analysis

This research propose a deep analysis of Milanese real estate market, based on data supplied by three real estate organizations; gentrification appears in some neighborhoods, such as Tortona, Porta Genova, Bovisa, Isola Garibaldi: the latest is the subject of the final analysis, by surveying of physical and social state of the area. The survey takes place in two periods (2003 and 2009) to compare the evolution of gentrification. The results of surveys has been employed in a simulation by multi-agent system model, to foresee long term evolution of the phenomenon. These neighborhood micro-indicators allow to put in evidence actual trends, conditioning a local real estate market, which can translate themselves in phenomena such as gentrification. In present analysis, the employ of cellular automata models applied to a neighborhood in Milan (Isola Garibaldi) produced the dynamic simulation of gentrification trend during a very long time: the cyclical phenomenon (one loop holds a period of twenty – thirty years) appears sometimes during a theoretical time of 100 – 120 – 150 years. Simulation of long period scenarios by multi-agent systems and cellular automata provides estimator with powerful tool, without limits in implementing it, able to support him in appraisal judge. It stands also to reason that such a tool can sustain urban planning and related evaluation processes

Combining a land parcel cellular automata (LP-CA) model with participatory approaches in the simulation of disruptive future scenarios of urban land use change

Urban development is a process that becomes increasingly complex as the city evolves and in which unexpected events can happen which may alter the envisaged trend over time. To anticipate and examine the sudden emergence of processes that are difficult to predict over long-term future timelines, prospective methodologies are required to manage and implement disruptive narrative storylines in future scenario planning. In this research, a method that combines Land Parcel Cellular Automata (LP-CA) and participatory approaches was developed in order to generate land use trajectories that are spatially consistent with disruptive narrative storylines. The urban-industrial corridor of Henares (Spain), which has undergone important urban transformations in recent decades, was chosen as the study area to test the model. In a preliminary validation of the LP-CA model, a Figure of Merit (FOM) value of 0.2817 indicated satisfactory performance. The results demonstrated the usefulness of the participatory scenario-building and the workshop in supporting the configuration of the model parameters and the spatial representation of complex urban dynamics. In conclusion, this methodology can be used to generate simulations of urban land use change in disruptive future scenarios and to spatially observe the propagation of the uncertainty associated with future events across different urban land uses.This work was supported by the Spanish Ministry of Science, Innovation and Universities and the European Social Fund [grant number PRE2018–084663]; the Spanish Ministry of Economy and Competitiveness [TRANSURBAN Project CSO2017–86914-C2–1-P]; and the “Estímulo a la Excelencia para Profesores Universitarios Permanentes” research programme funded by the University of Alcal´a and the Regional Government of Madrid [grant number EPU-INV/2020/009]

The Effects of Inequality, Density, and Heterogeneous Residential Preferences on Urban Displacement and Metropolitan Structure: An Agent-Based Model

Urban displacement - when a household is forced to relocate due to conditions affecting its home or surroundings - often results from rising housing costs, particularly in wealthy, prosperous cities. However, its dynamics are complex and often difficult to understand. This paper presents an agent-based model of urban settlement, agglomeration, displacement, and sprawl. New settlements form around a spatial amenity that draws initial, poor settlers to subsist on the resource. As the settlement grows, subsequent settlers of varying income, skills, and interests are heterogeneously drawn to either the original amenity or to the emerging human agglomeration. As this agglomeration grows and densifies, land values increase, and the initial poor settlers are displaced from the spatial amenity on which they relied. Through path dependence, high-income residents remain clustered around this original amenity for which they have no direct use or interest. This toy model explores these dynamics, demonstrating a simplified mechanism of how urban displacement and gentrification can be sensitive to income inequality, density, and varied preferences for different types of amenities

Amélioration du processus de géosimulation des phénomènes urbains complexes par l'adaptation d'une tessellation Voronoï

Similar to the intensive developments in Geographic Information Systems (GIS) and spatial databases, the field of urban geosimulation was increasingly used in recent years, with an emphasis on high-resolution applications. This recent tendency does not agree however with the traditionally homogeneous spatial representation provided by regular cellular automata which are commonly used as the spatial structures of geosimulation applications. Several issues are raised in the literature, including reports of limitations in spatial reasoning and a lack of realism related to such spatial representations. The few solutions that, so far, deviate from the ‘dogma of regularity of the spatial representation’ are also subject to recent criticism. In this context, we propose an alternative multi-scale model based on the Voronoi diagram of polygons, which matches geographic features of the urban environment. The proposed theoretical model was developed and tested in the context of a urban geosimulation using high resolution spatial data, in the form of registered parcels of irregular shapes and sizes. The first results of the approach demonstrate the potential of our model in the context of urban geosimulation. Finally, based on our extensive analysis of the main approaches of space segmentation, we propose a schematic method to choose a spatial decomposition suited to urban geosimulation