Urban Simulation Model Research Articles

Evaluating Water Demands under Climate Change and Transitions in the Urban Environment

Urban regions are complex and dynamic with many external and internal factors driving growth, movement, and composition. Forecasting regional characteristics important for long-term planning is inherently difficult for such settings, but quantitative estimates of the changes in urban environments are necessary for engineers and planners. This study examines how population growth, land use, pricing policy, and climate change affect residential water demands in the Puget Sound region. A spatially disaggregate water demand model is coupled with an advanced urban simulation model (UrbanSim) to generate demands at a detailed spatial resolution over a 30 year planning horizon. A baseline scenario is compared with output from UrbanSim for three different planning scenarios.

Omnipresent Sprawl? A Review of Urban Simulation Models with Respect to Urban Shrinkage

Simulation models on urban land-use change help in understanding urban systems and assist in urban planning. One of the challenges of simulating urban regions in Europe as well as in North America or Japan is urban shrinkage, where deindustrialisation, massive population losses, and ageing cause unforeseen (or unexpected) commercial and housing vacancies in cities. In order to set up a conceptual framework for model improvement to assist such challenges, we review recent urban land-use-change simulation models, using four different modelling approaches: system dynamics, linked transport — urban models, cellular automata, and agent-based modelling. The focus of the review is to assess the causalities and feedback mechanisms that were implemented in these models. The results show that simulation models are very heterogeneous in implemented mechanisms leading to urban land-use dynamics. No single model fulfils all of the criteria required to model urban shrinkage in a spatially explicit way. However, system-dynamic models that are documented in the literature can serve as a good starting point for spatially nonexplicit simulation, and one example was found for linked transport — urban models which encompasses aspects of urban shrinkage. The potential of cellular automata is unclear as spatially explicit data on vacancies to feed this class of models is usually not available. Agent-based models appear to be the most promising approach for spatially explicit modelling of urban shrinkage.

Modelling the Appearance and Behaviour of Urban Spaces

Abstract Urban spaces consist of a complex collection of buildings, parcels, blocks and neighbourhoods interconnected by streets. Accurately modelling both the appearance and the behaviour of dense urban spaces is a significant challenge. The recent surge in urban data and its availability via the Internet has fomented a significant amount of research in computer graphics and in a number of applications in urban planning, emergency management and visualization. In this paper, we seek to provide an overview of methods spanning computer graphics and related fields involved in this goal. Our paper reports the most prominent methods in urban modelling and rendering, urban visualization and urban simulation models. A reader will be well versed in the key problems and current solution methods.

COASTAL URBAN FLOOD SIMULATION USING FEM-GIS BASED MODEL

ABSTRACT In this paper, a coastal urban flood simulation model is presented using simple mass balance technique for overland flow and diffusion wave equation for channel flow. Finite Element Method (FEM) has been used for solving the diffusion wave equation. Effect of tidal variation is considered as the boundary condition. Geographic Information System (GIS) is used for data management while remote sensing is used for land use classification. The model is applied to an urban catchment of Panvel, Maharashtra and possibility of flooding is investigated for three rainfall events. It is observed from the results, that the model reasonably simulates the water levels in the channel compared to field observations. Parameter based sensitivity analysis showed that model results are reasonably stable for different parameters. It is observed that peak discharge and time to peak are moderately sensitive to land use within the catchment.

Visualization of Simulated Urban Spaces: Inferring Parameterized Generation of Streets, Parcels, and Aerial Imagery

Urban simulation models and their visualization are used to help regional planning agencies evaluate alternative transportation investments, land use regulations, and environmental protection policies. Typical urban simulations provide spatially distributed data about number of inhabitants, land prices, traffic, and other variables. In this article, we build on a synergy of urban simulation, urban visualization, and computer graphics to automatically infer an urban layout for any time step of the simulation sequence. In addition to standard visualization tools, our method gathers data of the original street network, parcels, and aerial imagery and uses the available simulation results to infer changes to the original urban layout and produce a new and plausible layout for the simulation results. In contrast with previous work, our approach automatically updates the layout based on changes in the simulation data and thus can scale to a large simulation over many years. The method in this article offers a substantial step forward in building integrated visualization and behavioral simulation systems for use in community visioning, planning, and policy analysis. We demonstrate our method on several real cases using a 200 GB database for a 16,300 km2 area surrounding Seattle.

A simulation model for generating alternative scenarios

The Iuci2 urban simulation model simulates new urban development for a large region in central Indiana (USA) that includes multiple metropolitan areas. The model has been developed for use by persons without specialised expertise. It is freely distributed and may be downloaded from the Internet. Land use data for the model have been estimated from satellite imagery. Aggregate logit models have been estimated and are used to predict the probabilities of land being converted from non-urban to residential and employment-related uses for 1609-meter grid cells. A key feature of the model is the capability to generate alternative development scenarios reflecting a range of policy choices and assumptions regarding future development, ranging from the imposition of development restrictions to changes in densities of development to different overall rates of population growth. The model and its capabilities to produce alternative scenarios have been applied in a variety of planning contexts.

Estimation and validation of a microscopic model for spatial economic effects of transport infrastructure

The spatial economic effects in integrated land use and transport models are increasingly disaggregate and can benefit from improved knowledge into the effect of accessibility and agglomeration on the spatial behaviour of firms. This article strives to contribute to this knowledge by first analysing the influence of accessibility and agglomeration on firm behaviour with exceptionally detailed firm data for the province of South Holland in The Netherlands. Next the added value of incorporating such effects in urban simulation models is tested with two series of validation runs with a microscopic model for firm dynamics. The presented Spatial Firm-demographic Micro-simulation (SFM) model simulates transitions and events in the firm population, including firm relocations, firm growth, firm dissolution and firm formation. Accessibility is measured with proximity to infrastructure access points and logsums of business and commuting trips from a transport model. Agglomeration measures are based on theories from urban economics and integrate travel time range bands into measures for specialisation and diversification. Estimation results confirm a significant influence of accessibility and agglomeration on the choice behaviour of firms. Application of these measures prove to increase the validity of the firm-demographic simulation model to a significant but modest extend.

Assessing uncertainty in urban simulations using Bayesian melding

We develop a method for assessing uncertainty about quantities of interest using urban simulation models. The method is called Bayesian melding, and extends a previous method developed for macrolevel deterministic simulation models to agent-based stochastic models. It encodes all the available information about model inputs and outputs in terms of prior probability distributions and likelihoods, and uses Bayes’s theorem to obtain the resulting posterior distribution of any quantity of interest that is a function of model inputs and/or outputs. It is Monte Carlo based, and quite easy to implement. We applied it to the projection of future household numbers by traffic activity zone in Eugene-Springfield, Oregon, using the UrbanSim model developed at the University of Washington. We compared it with a simpler method that uses repeated runs of the model with fixed estimated inputs. We found that the simple repeated runs method gave distributions of quantities of interest that were too narrow, while Bayesian melding gave well calibrated uncertainty statements.

Toward a Cognitive Approach to Urban Dynamics

‘A cognitive approach to urban dynamics’ is proposed in this paper as a theorization of the dynamics of cities from the first principles of humans' cognitive capabilities. The aim is to initiate a discussion concerning the potential of such an approach. This is done by examining some of the cognitive processes that are relevant to cities and their dynamics, by considering some conceptual and methodological obstacles for such a project, and by suggesting SIRN (Synergetic Inter-Representation Networks) as an approach that can overcome these obstacles. I then discuss and exemplify the implications to urban simulation models and conclude by suggesting further research directions.

A Case Study in Digital Government

The UrbanSim project provides a case study in Digital Government, and this article examines progress to date in developing and applying the system in a range of metropolitan areas. Digital Government is meant here in the context of an innovative, cross-cutting initiative of the National Science Foundation. The project integrates academic research on urban simulation modeling and policy evaluation with research on human-computer interaction and software engineering, and uses a value-sensitive design to ensure that the system addresses the needs of governments and citizens. This article addresses the importance of the problem domain and the project objectives, presents a range of challenges, and outlines the design and application of UrbanSim in response to these. It discusses issues arising in the application of the model in the Salt Lake City metropolitan region, where a lawsuit over a highway project has precipitated use of UrbanSim to assess the interactions of transportation, land use, and environmental outcomes, and concludes with an assessment and directions for future research.

Microsimulation of Land Use

The project ILUMASS (Integrated Land-Use Modelling and Transportation System Simulation) aims at embedding a microscopic dynamic simulation model of urban traffic flows into a comprehensive model system incorporating changes of land use, the resulting changes in transport demand, and the impacts of transport on the environment. The land-use component of ILUMASS will be based on the land-use parts of an existing urban simulation model, but is to be microscopic like the transport parts of ILUMASS. Microsimulation modules will include models of demographic development, household formation, firm lifecycles, residential and non-residential construction, labour mobility on the regional labour market and household mobility on the regional housing market. These modules will be closely linked with the models of daily activity patterns and travel and goods movements modeled in the transport parts of ILUMASS developed by other partners of the project team. The design of the land-use model takes into account that the collection of individual micro data (i.e. data which because of their micro location can be associated with individual buildings or small groups of buildings) or the retrieval of individual micro data from administrative registers for planning purposes is neither possible nor, for privacy reasons, desirable. The land-use model therefore works with synthetic micro data which can be retrieved from generally accessible aggregate data.

Macro-To-Micro Urban Simulation Model for the Assessment of Quality of Life

Upgrading of the Quality of Life (QOL) is a key concept in urban policies. Proposed QOL indicators in past studies include both macro and micro factors. From the aspect of policy formulation, the causalities between policies and these indicators have to be captured for its evaluation. The factors of QOL vary very broadly from regional socio-economic to the consequences on individual life, therefore, as to giving shape to this QOL evaluation analysis, we attempt to develop comprehensive simulation framework that consists of large zonal activity location model and small mesh land-use model. In this paper, as a first step of this attempt, we present a conceptual frame of the whole system and especially propose a micro land-use simulation model in this system.

Microsimulation of Urban Development and Location Choices: Design and Implementation of UrbanSim

UrbanSim is a new urban simulation model, developed over the past several years, which is now operational in three urban areas in the United States. The model system is designed to address emerging needs to better coordinate transportation and land use planning as a result of recognition of the strong interactions between land use and transportation, increasing pressure from federal transportation and environmental legislation, and growing adoption of state growth management programs. The model system is implemented as a set of interacting model components that represent the major actors and choices in the urban system, including household moving and residential location, business choices of employment location, and developer choices of locations and types of real estate development, all subject to the influence of governmental transportation and land use policy scenarios. The model design is unusual in the degree of disaggregation of space, time, and agents, and in the adoption of a dynamic disequilibrium approach. The objective of this paper is to describe the entire system at a sufficient level of detail to convey the key specification and design choices made in implementing the system.

A SIMPLE MODEL OF URBAN CANYON ENERGY BUDGET AND ITS VALIDATION

An urban canyon energy budget simulation model is described. The model is simple and computationally inexpensive enough to permit characterization of the spatial and temporal variability of canyon energy exchanges by running multiple cases. It is two-dimensional and dry and avoids the necessity for computational fluid dynamical calculations by using parameterizations for the down-canyon wind profile and cross-canyon vortex flow, and by employing an exchange coefficient formulation for sensible heat loss from the walls. These are combined with radiation calculations using the procedure of Arnfield (1976, 1982) and substrate heat fluxes computed using the Fourier heat conduction equation and wall and floor thermal property information. The model is validated against the measured canyon energy budget data of Nunez and Oke (1977) and reproduces these data quite well, with Willmott indices of agreement in the range 0.91 to 1.00 and root-mean-square errors of 14 to 46 W m-2 for individual facets and for the total canyon system. The poorest correspondence was for the substrate heat flux, the maxima for which were overestimated, suggesting use of excessively large facet thermal properties. These inputs were adjusted based on the measurement-simulation discrepancies, leading to further improvement in model performance. The adjusted thermal properties are consistent both with published data and with the available information on the morphological characteristics of the canyon. [Key words: urban canyon energy budget, urban climate, numerical simulation model.]

An integrated urban development and ecological simulation model

This paper develops an integrated strategy to model the urban development and ecological dynamics in the Central Puget Sound Region. This effort is part of the Puget Sound Regional Integrated Synthesis model (PRISM) – an interdisciplinary initiative at the University of Washington aiming to develop a dynamic and integrated understanding of the environmental and human systems in the Puget Sound. We describe a model that predicts the environmental stresses associated with urban development and related changes in land use and human activities under alternative demographic, economic, environmental, and policy scenarios. We build on UrbanSim, an existing urban simulation model developed by Waddell [42]. The principal urban actors, represented in the model as objects corresponding to businesses, households, developers, and governments, make choices about location of activities and land development. We extend the object properties and methods now implemented in the UrbanSim model to predict three types of human-induced environmental stressors: land conversion, resource use, and emissions. The core location model in UrbanSim will be revised from its current aggregate structure to one based on microsimulation, and from a zone description of space to one based on a high-resolution grid structure. We will use a spatially explicit process-based landscape modeling approach to replicate ecosystem processes and represent land use–cover interactions at the regional scale. The output of the urban ecological model will serve as the input to several biophysical models for hydrology, hillslope stability, water quality, atmosphere, and ecosystems. Ecological changes will feed back on the choices of both households and business locations, and availability of land and resources.

A Simulation Model of a Decentralized Metropolitan Area with Two-Worker, "Traditional," and Female-Headed Households

An urban simulation model is developed in which there are multiple household types: two-worker households, traditional households, and female-headed households, and multiple employment locations: a CBD and two subcenters. Female workers are assumed to have lower wages. Labor force participation and choice of job and residential locations are endogenous. The model shows that a fairly realistic city can be represented, particularly when a random component to wages is introduced. The distribution of household types within the city is shown to be quite sensitive to relative wages of male versus female workers, to commuting costs, and to the level of CBD versus suburban wages—for example, when CBD wages fall, the proportion of female-headed households declines sharply.

Dynamic forecasting of travel demand, residential location and land development

TheChicago Area Transportation/Land-Use Analysis System (CATLAS) is a large scale urban simulation model which synthesizes “location rent analysis” from urban economics with “travel demand analysis” from transportation planning. This paper describes the theoretical formulation, empirical estimation and policy application of CATLAS to the evaluation of CBD-oriented rapid transit projects in Chicago.

DYNAMIC FORECASTING OF TRAVEL DEMAND, RESIDENTIAL LOCATION AND LAND DEVELOPMENT

ABSTRACT The Chicago Area Transportation/Land‐Use Analysis System (CATLAS) is a large scale urban simulation model which synthesizes “location rent analysis” from urban economics with “travel demand analysis” from transportation planning. This paper describes the theoretical formulation, empirical estimation and policy application of CATLAS to the evaluation of CBD‐oriented rapid transit projects in Chicago.

Characteristics of discrete housing market model equilibria

A discrete microeconomic model of a market for heterogeneous housing units is presented. It is proven that whenever bid rents are lower semicontinuous monotone decreasing functions of utility and asked rents are continuous monotone increasing functions of profits an equilibrium solution exists whose graph corresponds to a bipartite tree. This graphical representation of the solutions provides a mechanism for analyzing important theoretical issues. Using graph theoretic techniques, it is demonstrated that bargaining power assumptions are sufficient to ensure unique equilibrium price and utility levels. Alternatively ruling out the possibility of isolated submarkets guarantees unique market clearing prices. Unique equilibrium prices imply almost unique location decisions: One may still be able to reassign households among housing units for which they are indifferent. The model reconciles the dichotomy between open and closed market models by providing a robust mechanism for characterizing conditions when agents leave the market. The reconciliation underscores the necessity for carefully choosing bargaining power, market exit, reservation rent, and reservation utility assumptions in closed as well as open models. Without at least implicitly making assumptions of these sorts, neither closed nor open models can determine anything more than relative prices. The model generalizes versions of The Urban Institute Housing Market Model, and the market clearing section of the National Bureau of Economic Research Urban Simulation Model. It presents an algorithm for computing equilibria and describes an application of this algorithm to The Urban Institute Housing Market Model. The algorithm computes equilibrium solutions at one-sixth of the cost of using the original U.I. Model algorithm.

Analysis and comparison of the Mills-Muth urban residential land-use simulation models

Analysis and comparison of the Mills-Muth urban residential land-use simulation models