Environment and Planning B: Urban Analytics and City Science

A method is proposed for plotting the plans of a large variety of rectangular built forms across a two-dimensional ‘morphospace’ of possibilities. The plans are enumerated by means of a technique of binary coding, such that similar shapes are grouped within distinct areas of this morphospace. Some applications to a geometrical history of building types are sketched, with examples from 19th-century pavilion hospitals, English elementary schools, and early New York skyscrapers. The purpose is to provide classification of built forms, to understand their interrelationships in a systematic way, and to see how building types have followed characteristic ‘morphological trajectories’ through this space of forms. It is a tool with which to approach the history of architecture from a geometrical point of view. It is not primarily conceived as an aid to design: nevertheless the paper concludes with some brief speculations about possible implications for design methods, using genetic algorithms.

Computerised 3D models are more intuitive and rich in landscape detail. They are considered an essential visualisation method for the presentation of environmental data with spatial contents. The 3D technology has been increasingly applied in environmental impact assessment (EIA) and urban planning to view and better appreciate human impacts on the environment. Their uses are not restricted to the professionals. Because of their great likeness to the natural world, 3D representations have also been employed to convey information to the general population through public hearings, workshops, and the Internet. The use of 3D visualisation in EIA applications is not without problems, particularly for those without the necessary skills in computer operations and map comprehension. This paper is an assessment of the applicability and effectiveness of 3D visualisation in EIA. First we illustrate different scenarios of 3D portrayals in environmental management. This is followed by a discussion about the problems and concerns of using 3D visualisation in presenting environmental data. These issues are examined in greater detail to highlight various technical considerations and types of data suitable (or not suitable) for the implementation of 3D models. A reference is made to the potential incorporation of feedback mechanisms in a 3D system intended for public participation.

This paper aims to develop a new approach to investigating the relationships between people's perceptions and physical components of sidewalk environments. A psychological survey composed of semantic differential items was administered to 112 participants in order to assess their perceptions of 20 sidewalk environments in Iksan city, South Korea. A field survey of the selected sidewalks was conducted to survey the physical components of the sidewalk environments. Because conventional statistical methods are not appropriate owing to the qualitative data, small sample size, and uncertainty, a new approach based on an artificial intelligence technique—rough sets theory—is applied to deal with the collected data. The application of the rough sets theory outputs the most important attributes of people's perceptions, minimal attribute sets without redundancy, and a series of decision rules that represent the relationships between perceptions and physical components of sidewalk environments. The analytical approach helps to understand better people's perceptions to sidewalk environments in a small city and then to establish a useful and constructive ground of discussion for walking environment design and management.

Recent years have witnessed substantial advances in the precision and availability of digital infrastructure data, remote sensing data, and microscale socioeconomic data for urban areas in many parts of the world. However, these data still remain deficient in detail especially with respect to the fine-grained property-level structural attributes that form the basis of housing-market models and simulations. This lack of detail is hindering the development of house-price models, the validation of housing-market theories, and restricting the quality of empirical input into urban planning. A methodology is developed for deriving estimates of floor area for individual properties from the integration of Ordnance Survey Mastermap data and Environment Agency LiDAR data for an area in the city of Cardiff, Wales. Floor area is an important determinant of house price and a fundamental variable in housing-market models. The estimates are validated against measures of floor area obtained from an estate-agent survey of a large sample of properties. The research investigates the reasons for the differences in the estimates and the implications for the methodology. The paper concludes with a discussion about how the methodology can be developed and some future research applications.

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.

The approach of this study was to determine, theoretically, what impact current and future urban land use in the coastal city of Houston, Texas has on the space and time evolution of precipitation on a ‘typical’ summer day. Regional model simulations of a case study for 25 July 2001 were applied to investigate possible effects of urban land cover on precipitation development. Simulations in which Houston urban land cover was included resolved rain cells associated with the sea breeze front and a possible urban circulation on the northwest fringe of the city. Simulations without urban land cover did not capture the initiation and full intensity of the ‘hypothesized’ urban-induced rain cell. The response is given the terminology the ‘urban rainfall effect’ or URE. An urban growth model (UrbanSim) was used to project the urban land-cover growth of Houston, Texas from 1992 to 2025. A regional atmospheric-land surface model was then run with the 2025 urban land-cover scenario. Though we used a somewhat theoretical treatment, our results show the sensitivity of the atmosphere to urban land cover and illustrate how atmosphere — land interactions can affect cloud and precipitation processes. Two urban-induced features, convergence zones along the inner fringe of the city and an urban low-pressure perturbation, appear to be important factors that lead to enhanced rain clouds independently or in conjunction with the sea breeze. Simulations without the city (NOURBAN) produced less cumulative rainfall in the west-northwest Houston area than simulations with the city represented (URBAN). Future urban land-cover growth projected by UrbanSim (URBAN2025) led to a more expansive area of rainfall, owing to the extended urban boundary and increased secondary outflow activity. This suggests that the future urban land cover might lead to temporal and spatial precipitation variability in coastal urban microclimates. It was beyond the scope of the analysis to conduct an extensive sensitivity analysis of cause — effect relationships, though the experiments provide some clues as to why the rainfall evolution differs. This research demonstrates a novel application of urban planning and weather — climate models. It also raises viable questions concerning future planning strategies in urban environments in consideration of hydroclimate changes.

The main aim of this study is to understand the relevant variables underlying the mechanisms of office supply, office demand, and market equilibrium to support municipal decision-making processes. Public decisions, at the local level, are expected to ensure that office prices are kept under control, avoiding the speculative behaviour of real-estate agents, and are able to prepare appropriate forms of intervention over supply and demand, in the short term as well as in the medium or long term. In order to reach these goals an identification of the most relevant variables that shape office supply and office demand and their respective elasticities is carried out, and ongoing supply, demand, and market equilibrium hedonic appraisal models are developed. These models allow for: (1) the computation of the influence of the identified variables on office prices (per m²); (2) the measurement of the price gaps between demand and supply according to location; and (3) the characterisation of market balances. Despite short-term adjustments between supply and demand functions, in search of market equilibrium, balances are ephemeral because they are modelled by different factors that change over time. However, these models can be adjusted and applied to different moments in time and extended to other urban contexts. As such they are able to support municipal decisions concerning land-use office location and management.

In a digital age public sector geoinformation (PSGI) is potentially a vital link in the added-value chain. Yet private sector value-added resellers (VARs) still face a number of barriers to using PSGI. Price is only one impediment. The complexity of licences and restrictive licence conditions of PSGI may be an even bigger obstacle. Especially when combining different datasets, VARs can face a quagmire of conflicting licence conditions. Batty (2006 Environment and Planning B: Planning and Design 33 163–164) called for research that would stimulate value-added use of PSGI. However, inconsistent and intransparent licence conditions for PSGI are among the biggest obstacles of PSGI for VARs. This paper explores the current PSGI licences to assess the actual restrictions and how current obstacles can be levelled. The Creative Commons licensing concept was explored and adapted to make it suitable for licensing PSGI. The resulting concept of Geo Shared licences is a means to harmonise licence conditions for PSGI. Our research shows that the Geo Shared concept can be a valuable contribution to further harmonisation of PSGI licences and thus development of value-added chains. Furthermore, development of geographic information infrastructures will also be stimulated. Similarly, the concept can be considered as a serious option within the Infrastructure of Spatial Information for Europe (INSPIRE), as a way towards transparent harmonised licences in Europe and beyond.

UrbanSim is an integrated transportation land-use model that has been under development since the late 1990s. It has received a significant amount of attention in the integrated modeling community. It is well known for its disaggregated approach. A number of papers describing the application of UrbanSim have appeared in the formal and gray literatures. Some of these papers report on successful applications of UrbanSim with little description of the amount of effort required to develop an operational model. Those that do report on the effort and challenges of using UrbanSim suggest that substantial data and human resources are required. One recent report quantifies the human resource requirements as an interdisciplinary team of four for three years. This reputation makes many potential users think twice before developing an UrbanSim model. We believe the best way to evaluate UrbanSim for a new region is by having a sense of how it can be used, and how much effort is required to do so. Understanding UrbanSim, however, does not require having a fully operational model. This paper is aimed at researchers and institutions that would like to evaluate UrbanSim, but are concerned about the effort required to do so. Based on two applications (Brussels in Belgium and Lausanne in Switzerland), it describes a procedure to develop a prototype UrbanSim model and how to use it to evaluate UrbanSim for application to a new region. Its objective is to motivate, describe, comment and illustrate a procedure for an efficient evaluation of the use of UrbanSim. Its main contributions are threefold. First, it develops a procedure by which a prototype UrbanSim model can be developed for evaluation purposes in a new region. Second, it provides an analysis of the effort required to do so. Finally, in so doing it advances knowledge in the field of transportation and land-use modeling by helping modelers to evaluate the use of UrbanSim for a particular study region, in a rigorous and systematic way.

Increasingly, researchers have discussed ways of utilizing excess commuting/jobs — housing methodologies in policy analyses. One potential barrier involves the uncertainty associated with using network-based travel time estimates in the commute models. This paper examines the extent to which various excess commuting/jobs — housing statistics are sensitive to changes in their input transportation costs. A series of computational experiments are run using spatial data from a smaller metropolitan area. Results reveal the variability in the commuting estimates given assumptions about likely travel time variability.