Simulation of suburban migration: driving forces, socio-economic characteristics, migration behaviour and resulting land-use patterns

Land-use transitions in metropolitan areas have a high impact on environment and appear as pressures on the inhabitants' living conitions. Tools are needed to support planning decisions to overcome or at least mitigate those pressures. Simulation models are such tools, generating land-use change scenarios that help to examine effects of planning strategies. This article introduces a model that establishes a multiagent system approach to achieve results for changes in land-use and migration patterns with high spatial accuracy. Details of suburban migration behaviour modelling are described with emphasis on the definition of socio-economic classes, on the detection of driving forces triggering suburban migration and on migration behaviour aspects with respect to those socio-economic classes. The model concept is presented as well as results of retrospective simulation runs for a 30-year time range that are compared with the observations of the simulation target year in order to examine the model's validity. Future scenario runs show different urban sprawl trends with either restricted or unlimited residential area zoning and higher versus lower target residential density regulations. A remarkable decrease of suburban sprawl can be achieved by applying the right planning measures, even if the numbers of migrating households remain the same.

Actors and factors - bridging social science findings and urban land use change modeling

Recent uneven land use dynamics in urban areas resulting from demographic change, economic pressure and the cities’ mutual competition in a globalising world challenge both scientists and practitioners, among them social scientists, modellers and spatial planners. Processes of growth and decline specifically affect the urban environment, the requirements of the residents on social and natural resources. Social and environmental research is interested in a better understanding and ways of explaining the interactions between society and landscape in urban areas. And it is also needed for making life in cities attractive, secure and affordable within or despite of uneven dynamics.\ud The position paper upon “Actors and factors – bridging social science findings and urban land use change modeling” presents approaches and ideas on how social science findings on the interaction of the social system (actors) and the land use (factors) are taken up and formalised using modelling and gaming techniques. It should be understood as a first sketch compiling major challenges and proposing exemplary solutions in the field of interest

Modelling urban spatial change: a review of international and South African modelling initiatives

August 2013Urban growth and land use change models have the potential to become important tools for urban spatial planning and management. Before embarking on any modelling, however, GCRO felt it was important to take note of, and critically assess lessons to be learnt from international experience and scholarship on spatial modelling, as well as a number of South African experiments that model future urban development. In 2012, GCRO initiated preliminary research into current international and South African modelling trends through a desktop study and telephone, email and personal interviews. This Occasional paper sets out to investigate what urban spatial change modelling research is currently being undertaken internationally and within South Africa. At the international level, urban modelling research since 2000 is reviewed according to five main categories: land use transportation (LUT), cellular automata, urban system dynamics, agent-based models (ABMs) and spatial economics/econometric models (SE/EMs). Within South Africa, urban modelling initiatives are categorised differently and include a broader range of urban modelling techniques. Typologies used include: provincial government modelling initiatives in Gauteng; municipal government modelling initiatives; other government-funded modelling research; and academic modelling research. The various modelling initiatives described are by no means a comprehensive review of all urban spatial change modelling projects in South Africa, but provide a broad indication of the types of urban spatial change modelling underway. Importantly, the models may form the basis for more accurate and sophisticated urban modelling projects in the future. The paper concludes by identifying key urban modelling opportunities and challenges for short- to long-term planning in the GCR and South Africa.Written by Chris Wray, Josephine Musango and Kavesha Damon (GCRO) Koech Cheruiyot (NRF:SARChI chair in Development Planning and Modelling at Wits

Urban Development and Infrastructure Cost Modelling for Managing Urban Growth in Latin American Cities

Rapid urban growth presents considerable challenges to cities in Latin America and calls for tools and mechanisms that can help identify priority areas of work and enable integrated responses for urban sustainability, especially with regard to access and delivery of infrastructure services. The concentration of population, however, generates high demand for services. When the expansion of the supply of services is inadequate, significant deficits emerge in the coverage and quality of infrastructure and services, including housing. These problems are compounded by weak urban governance. (IDB, 2015) Thus solutions are required to secure sustainable urban development considering financing limits of cities authorities as well quality of life and environment. Infrastructure planning can either respond to urban growth providing supply by following the demand or it can pro-actively shape urban development in a resource efficient way by providing supply directing the demand. Thus appropriate infrastructure design can serve as an instrument for “soft” urban growth management. AIT (Austrian Institute of Technology) has been contracted by the IDB (Inter-American Development Bank) to develop a tool (model) to simulate urban expansion triggered by infrastructure development and to estimate related infrastructure costs. The tool allows simulating different urban development scenarios based on different assumption on population behaviour and criteria triggering this behaviour. The tool called UIDS (Urban and Infrastructure Development Simulator) allows testing infrastructure networks extensions and estimates the expected infrastructure costs to assist cities in resource efficient as well as cost efficient infrastructure design. Backbone of the tool is a spatially explicit micro-simulation of urban expansion conducted through an agent-based model (ABM) as well as AIT’s MASGISmo simulation platform making use of the RePastJ environment for ABM modeling and R-statistics as well as a PostgreSQL/PostGis database and a GeoServer for Web Map Services (WMS). Single agents representing households of different socioeconomic classes trigger land cover and land use change within an area by moving to certain places. To model dwelling suitability for the agent classes the urban-region landscape is described through attractiveness layers representing different characteristics increasing (or decreasing) the suitability of potential urban expansion areas. The additional infrastructure costs for road network, water- and sanitation network, electricity and gas network, are estimated based on costs per unit (e.g. km pipeline, area covered etc.) and the related supply ratio. Based on the new dwelling allocations the infrastructure costs related to water and sanitation, transportation, and energy are calculated as distribution and connection costs and aggregated to total costs for the city, which are compared between different urban development scenarios

Spatiotemporal modeling of interactions between urbanization and flood risk: a multi-level approach

The main goal of this PhD research is to investigate the expected flood damage for future urban patterns at different scales. Four main steps are followed to accomplish this goal. In the first step, a retrospective analysis is performed for the evolution of the urban development in Wallonia (Belgium) as a case study. Afterward, two land use change models, cellular automata-based, and agent-based are proposed and compared. Based on this comparison, the agent-based model is employed to simulate future urbanization scenarios. An important feature of this research is evident in the consideration of the multiple densities of built-up areas, which enables to study both expansion and densification processes. As the model simulates urbanization up to 2100, forecasting land use change over such time frames entails very significant uncertainties. In this regard, uncertainty in land use change models has been considered. In the third step, 24 urbanization scenarios that differed in terms of spatial policies and urbanization rate are generated. The simulated scenarios have then been integrated with a hydrological model. The results suggest that urban development will continue within flood-prone zones in a number of scenarios. Therefore, in the fourth and last step, a procedural urban generation system is developed to analyze the respective influence of various urban layout characteristics on inundation flow, which assists in designing flood-resistant urban layouts within the flood-prone zones.This thesis was funded through the ARC grant for Concerted Research Actions for project number 13/17-01 entitled "Land-use change and future flood risk: influence of micro-scale spatial patterns (FloodLand)" financed by the French Community of Belgium (Wallonia-Brussels Federation)

Addressing Urban Sprawl from the Complexity Sciences

Urban sprawl is nowadays a pervasive topic that is subject of a contentious debate among planners and researchers, who still fail to reach consensual solutions. This paper reviews controversies of the sprawl debate and argues that they owe to a failure of the employed methods to appraise its complexity, especially the notion that urban form emerges from multiple overlapping interactions between households, firms and governmental bodies. To address such issues, this review focuses on recent approaches to study urban spatial dynamics from the perspective of the complexity sciences. Firstly, spatial metrics from landscape ecology provide means of quantifying urban sprawl in terms of increasing fragmentation and diversity of land use patches. Secondly, cellular automata and agent-based models suggest that the prevalence of urban sprawl and fragmentation at the urban fringe emerge from negative spatial interaction between residential agents, which seem accentuated as the agent’s preferences become more heterogeneous. Then, the review turns to practical applications that employ such models to spatially inform urban planning and assess future scenarios. A concluding discussion summarizes potential contributions to the debate on urban sprawl as well as some epistemological implications

Modelling built-up expansion and densification with multinomial logistic regression, cellular automata and genetic algorithm

This paper presents a model to simulate built-up expansion and densification based on a combination of a non-ordered multinomial logistic regression (MLR) and cellular automata (CA). The probability for built-up development is assessed based on (i) a set of built-up development causative factors and (ii) the land-use of neighboring cells. The model considers four built-up classes: non built-up, low-density, medium-density and high-density built-up. Unlike the most commonly used built-up/urban models which simulate built-up expansion, our approach considers expansion and the potential for densification within already built-up areas when their present density allows it. The model is built, calibrated, and validated for Wallonia region (Belgium) using cadastral data. Three 100 × 100 m raster-based built-up maps for 1990, 2000, and 2010 are developed to define one calibration interval (1990–2000) and one validation interval (2000 − 2010). The causative factors are calibrated using MLR whereas the CA neighboring effects are calibrated based on a multi-objective genetic algorithm. The calibrated model is applied to simulate the built-up pattern in 2010. The simulated map in 2010 is used to evaluate the model’s performance against the actual 2010 map by means of fuzzy set theory. According to the findings, land-use policy, slope, and distance to roads are the most important determinants of the expansion process. The densification process is mainly driven by zoning, slope, distance to different roads and richness index. The results also show that the densification generally occurs where there are dense neighbors whereas areas with lower densities retain their densities over time

Addressing urban sprawl from the complexity sciences

Urban sprawl is nowadays a pervasive topic that is subject of a contentious debate among planners and researchers, who still fail to reach consensual solutions. This paper reviews controversies of the sprawl debate and argues that they owe to a failure of the employed methods to appraise its complexity, especially the notion that urban form emerges from multiple overlapping interactions between households, firms and governmental bodies. To address such issues, this review focuses on recent approaches to study urban spatial dynamics. Firstly, spatial metrics from landscape ecology provide means of quantifying urban sprawl in terms of increasing fragmentation and diversity of land use patches. Secondly, cellular automata and agent-based models suggest that the prevalence of urban sprawl and fragmentation at the urban fringe emerge from negative spatial interaction between residential agents, which seem accentuated as the agent’s preferences become more heterogeneous. Then, the review turns to practical applications that employ such models to spatially inform urban planning and assess future scenarios. A concluding discussion summarizes potential contributions to the debate on urban sprawl as well as some epistemological implications