Alan T. Murray

Estimating impervious surface distribution by spectral mixture analysis

Abstract Estimating the distribution of impervious surface, a major component of the vegetation–impervious surface–soil (V–I–S) model, is important in monitoring urban areas and understanding human activities. Besides its applications in physical geography, such as run-off models and urban change studies, maps showing impervious surface distribution are essential for estimating socio-economic factors, such as population density and social conditions. In this paper, impervious surface distribution, together with vegetation and soil cover, is estimated through a fully constrained linear spectral mixture model using Landsat Enhanced Thematic Mapper Plus (ETM+) data within the metropolitan area of Columbus, OH in the United States. Four endmembers, low albedo, high albedo, vegetation, and soil were selected to model heterogeneous urban land cover. Impervious surface fraction was estimated by analyzing low and high albedo endmembers. The estimation accuracy for impervious surface was assessed using Digital Orthophoto Quarterquadrangle (DOQQ) images. The overall root mean square (RMS) error was 10.6%, which is comparable to the digitizing errors of DOQQ images. Results indicate that impervious surface distribution can be derived from remotely sensed imagery with promising accuracy.

Monitoring Growth in Rapidly Urbanizing Areas Using Remotely Sensed Data

Urbanization and the ability to manage for a sustainable future present numerous challenges for geographers and planners in metropolitan regions. Remotely sensed data are inherently suited to provide information on urban land cover characteristics, and their change over time, at various spatial and temporal scales. Data models for establishing the range of urban land cover types and their biophysical composition (vegetation, soil, and impervious surfaces) are integrated to provide a hierarchical approach to classifying land cover within urban environments. These data also provide an essential component for current simulation models of urban growth patterns, as both calibration and validation data. The first stages of the approach have been applied to examine urban growth between 1988 and 1995 for a rapidly developing area in southeast Queensland, Australia. Landsat Thematic Mapper image data provided accurate (83% adjusted overall accuracy) classification of broad land cover types and their change over time. The combination of commonly available remotely sensed data, image processing methods, and emerging urban growth models highlights an important application for current and next generation moderate spatial resolution image data in studies of urban environments.

PUBLIC TRANSPORTATION ACCESS

The form of a city has a major impact on the lifestyles of its residents. As urban centers grow, careful strategies are required to ensure that the regional quality of life is not adversely affected by this growth. An important strategic consideration is transportation planning. Questions regarding the sustainability of dispersed car dependent urban forms have led to a renewed interest in public transportation. This paper examines access to public transportation and discusses approaches for improving such access. Examples from the South East Queensland region of Australia will be used for illustration.

Strategic analysis of public transport coverage

Abstract Public transport service provision is viewed as an important component of the overall transportation planning and management process. Research examining public transportation performance and how it may be enhanced is much needed. This paper addresses strategic aspects of service access. Public transport in Brisbane, Australia is evaluated using a commercial geographical information system integrated with various spatial analytical techniques including a location covering model. The developed strategic analysis approach is effective for justifying local modifications to the public transport system with respect to system inefficiencies and also allows this to be done with significant user (or public) input. Such strategic approaches are likely to result in higher regional utilization of public transportation.

A stochastically constrained cellular model of urban growth

Abstract Recent approaches to modeling urban growth use the notion that urban development can be conceived as a self-organizing system in which natural constraints and institutional controls (land-use policies) temper the way in which local decision-making processes produce macroscopic patterns of urban form. In this paper a cellular automata (CA) model that simulates local decision-making processes associated with fine-scale urban form is developed and used to explore the notion of urban systems as self-organizing phenomenon. The CA model is integrated with a stochastic constraint model that incorporates broad-scale factors that modify or constrain urban growth. Local neighborhood access rules are applied within a broader neighborhood in which friction-of-distance limitations and constraints associated with socio-economic and bio-physical variables are stochastically realized. The model provides a means for simulating the different land-use scenarios that may result from alternative land-use policies. Application results are presented for possible growth scenarios in a rapidly urbanizing region in south east Queensland, Australia.

Recent advances in accessibility research: Representation, methodology and applications

Abstract. In this article we examine recent advances in accessibility research and their implications for future studies. We base our discussion on three intersecting dimensions that are useful for evaluating the contribution of recent studies: representation, methodology and applications. Various examples are selected to show that research concerned with representation and methodological problem solving is often applied to issues of broad concern in policy and planning. It is, however, not clear that the simultaneous treatment of representation, methodological and application issues has ever been fully worked out. The questions raised in this article may serve as a foundation for addressing issues pertinent to accurate representation, improved model building, and more rigorous applications in accessibility research.

Heuristic solution approaches to operational forest planning problems

Operational forest planning problems are typically very difficult problems to solve due to problem size and constraint structure. This paper presents three heuristic solution approaches to operational forest planning problems. We develop solution procedures based on Interchange, Simulated Annealing and Tabu search. These approaches represent new and unique solution strategies to this problem. Results are provided for applications to two actual forest planning problems and indicate that these approaches provide near optimal solutions in relatively short amounts of computer time.ZusammenfassungOperationale Forstplanungsprobleme sind typischerweise sehr schwierige Probleme, was durch die Problemgröße und durch die Struktur der „constraints“ gegeben ist. Dieser Artikelzeigt drei heuristische Lösungsansätze für operationale Forstplanungsprobleme auf. Wir haben Lösungsprozeduren entwickelt, die auf interchange, simulated annealing und Tabu-Suche basieren. Diese Ansätze stellen neue und andersartige Lösungsstrategien für dieses Problem dar. Ergebnisse bei Anwendung auf zwei tatsächliche Forstplanungsprobleme werden vorgestellt. Sie zeigen, daß diese Ansätze nahezu optimale Lösungen bei relativ kurzer Berechnungszeit liefern.

Excess Commuting and the Modifiable Areal Unit Problem

Excess commuting has emerged during the past two decades as an important construct for evaluating the spatial relationships between employment and residential locations. During this time-period, there has been an on-going debate regarding how one should measure excess commuting in urban regions. This paper contributes to the debate by focusing on the spatial issues inherent in excess commuting evaluation. We demonstrate how scale and unit definition (the modifiable areal unit problem) are manifested in the assessment of excess commuting, both in theoretical and empirical terms. To this end, a geographical information systems-based analysis is presented which explores spatial sensitivities in the excess commuting measure. Our results show that aggregation and spatial unit definition may have profound impacts on the estimation of excess commuting. This work provides a formal resolution to much of the recent debate regarding estimates of excess commuting in urban regions.

Modeling s-t path availability to support disaster vulnerability assessment of network infrastructure

The maintenance of system flow is critical for effective network operation. Any type of disruption to network facilities (arcs/nodes) potentially risks loss of service, leaving users without access to important resources. It is therefore an important goal of planners to assess infrastructures for vulnerabilities, identifying those vital nodes/arcs whose debilitation would compromise the most source-sink (s-t) interaction or system flow. Due to the budgetary limitations of disaster management agencies, protection/fortification and planning for the recovery of these vital infrastructure facilities is a logical and efficient proactive approach to reducing worst-case risk of service disruption. Given damage to a network, evaluating the potential for flow between s-t pairs requires assessing the availability of an operational s-t path. Recent models proposed for identifying infrastructure vital to system flow have relied on enumeration of all s-t paths to support this task. This paper proposes an alternative model constraint structure that does not require complete enumeration of s-t paths, providing computational benefits over existing models. To illustrate the model, an application to a practical infrastructure planning problem is presented.

Applying simulated annealing to location-planning models

Simulated annealing is a computational approach that simulates an annealing schedule used in producing glass and metals. Originally developed by Metropolis et al. in 1953, it has since been applied to a number of integer programming problems, including the p-median location-allocation problem. However, previously reported results by Golden and Skiscim in 1986 were less than encouraging. This article addresses the design of a simulated-annealing approach for the p-median and maximal covering location problems. This design has produced very good solutions in modest amounts of computer time. Comparisons with an interchange heuristic demonstrate that simulated annealing has potential as a solution technique for solving location-planning problems and further research should be encouraged.