Unconditional and conditional competing risk models of activity duration and activity sequencing decisions: An empirical comparison

 This paper reports the results of an empirical comparison of various types of competing risk models in predicting the timing and duration of activities. In particular, three types of models are compared: a non-competing risk model, an unconditional competing risk model, and a conditional competing risk model. The models are applied to an activity diary, collected in the Netherlands. The results of the comparison indicate that the conditional competing risk model performs best, indicating that the choice and timing of activities depends on the nature and duration of the activity conducted previously. The specific structure of these dependent transition probabilities are discussed in detail. Several socio-demographic variables are found to be significantly related to the transition probabilities. Received: 19 July 2001 / Accepted: 25 January 2002     

Misspecifications in interaction model distance decay relations: A spatial structure effect

 An exclusively statistical approach is proposed to address the spatial structure effects of general interaction models. It is shown that the spatial heterogeneity in the estimated region-specific distance decay parameters may in part be due to the combination of two factors: (a) a functional mis-specification of the global distance decay relationship; and (b) the heterogeneity in the region-specific conditional distance distributions. A properly specified global distance decay function allows controlling for these spatially induced biases in the local distance decay parameters. However, inherent multicollinearities between the set of region specific distance decay parameters and other estimated model parameters prevent an unambiguous interpretation. A key conclusion is that a proper model specification, in particular, the specification of the global distance decay relationship, is of paramount importance in interaction modeling and for accessibility studies. Received: September 2002 / Accepted: January 2003     

The role of spatial effects in the empirical analysis of regional concentration

 Economists have recently devoted an increasing attention to the issue of spatial concentration of economic activities. However, surprisingly enough, most of the empirical work is still based on the computation of very basic statistical measures in which the geographical characteristics of data play no role. By making use of a series of empirical examples we show that spatial concentration consists of two different features that are rarely kept as separate in the statistical analysis: an a-spatial concept of variability which is invariant to permutations, and the concept of polarization that refers to the geographical position of observations. Received: 8 August 2000 / Accepted: 20 June 2001     

Individual accessibility and distance from major employment centers: An examination using space-time measures

 Distance has often been assumed to be an influence on intraurban accessibility, whether in traditional proximity-based measures of accessibility, or through expectations about distance-minimizing travel behavior and the logic of the monocentric model. This paper examines the importance of distance from major employment centers to individual accessibility in Portland, Oregon, using space-time accessibility measures computed using GIS. The results of this research indicate that distance from these locations has mixed results on individual accessibility. This appears to reflect the importance of time, both the time of day activities are scheduled as well as time constraints, to individual activity patterns. Received: September 2002 / Accepted: January 2003 The author gratefully acknowledges the contributions of two anonymous reviewers, whose comments greatly improved the content of this paper     

Change detection thresholds for remotely sensed images

 The detection of change in remotely sensed images is often carried out by designating a threshold to distinguish between areas of change and areas of no change. The choice of threshold is often arbitrary however. The purpose of this paper is to offer a statistical framework for the selection of thresholds. The framework accounts for the facts that one carries out multiple tests of the null hypothesis of no change, when searching for regions of change over an image with a large number of pixels. Special attention is given to global spatial autocorrelation, which can affect the selection of appropriate threshold values. Received: 8 March 2001 / Accepted: 12 October 2001     

Modeling spatial dependence in high spatial resolution hyperspectral data sets

 As either the spatial resolution or the spatial scale for a geographic landscape increases, both latent spatial dependence and spatial heterogeneity also will tend to increase. In addition, the amount of georeferenced data that results becomes massively large. These features of high spatial resolution hyperspectral data present several impediments to conducting a spatial statistical analysis of such data. Foremost is the requirement of popular spatial autoregressive models to compute eigenvalues for a row-standardized geographic weights matrix that depicts the geographic configuration of an image's pixels. A second drawback arises from a need to account for increased spatial heterogeneity. And a third concern stems from the usefulness of marrying geostatistical and spatial autoregressive models in order to employ their combined power in a spatial analysis. Research reported in this paper addresses all three of these topics, proposing successful ways to prevent them from hindering a spatial statistical analysis. For illustrative purposes, the proposed techniques are employed in a spatial analysis of a high spatial resolution hyperspectral image collected during research on riparian habitats in the Yellowstone ecosystem. Received: 25 February 2001 / Accepted: 2 August 2001     

Accessibility tradeoffs in public transit planning

 Spatial accessibility is a critical consideration in the provision of services, both public and private. In public transit planning, accessibility is comprised of access and geographic coverage. Interestingly, these two considerations are somewhat at odds with each other. Access is important because it is the process associated with getting to and departing from the service. Such access is typically perceived of in spatial terms as the physical proximity to transit stops or stations. Additional stops along a route usually mean greater access, because a stop is more likely to be within an acceptable walking/driving standard for a larger number of people. On the other hand, more stops and greater access slow transit travel speeds, thereby decreasing the area of service reachable given a travel time budget. More stops along a route translate to greater service interruption and longer travel times. The faster the travel time, the more desirable the service. Further, if travel times become excessive, then user demand for service will decrease. All of this means that stop spacing along a route is central to accessibility, as it is a tradeoff of access (more stops) and geographic coverage (service efficiency through less stops). This paper details modeling approaches for addressing accessibility concerns in an integrated fashion. Bus-based transit service in Columbus, Ohio will be utilized to illustrate the usefulness of these approaches in transit planning. Received: September 2002 / Accepted: January 2003 This research was supported in part by an Ohio State University seed grant.     

Towards a conjoint-based, context-dependent model of task allocation in activity settings: Some numerical experiments

 None of the currently developed activity-based models of transport demand explicitly models task allocation among household members. To fill this gap, the present paper suggests to complement activity-based models of activity scheduling with a context-dependent model of task allocation. That is, it is assumed that the allocation of tasks within households is partly based on such contextual variables as the amount of time a member has to spend on mandatory activities and car availability. In particular, the paper advocates a conjoint-based approach, based on an assignment task as opposed to the traditional ranking, rating or choice response formats. By definition, an assignment task involves a combinatorial explosion of choice alternatives, implying that additional operational decisions to estimate the context-dependent model are required. This study presents the results of various numerical experiments, conducted to better understand the impacts of those decisions on the degree of bias in the parameter estimates of the choice model. The results of these simulations indicate that under particular assumptions, the development and estimation of a conjoint-based, context-dependent model of task allocation within households is feasible. Received: March 1999 / Accepted: June 2001     

Map projection errors in the Weber problem

 When demand points are given as a planar map where projection method is explicitly stated, we usually know the latitudes and longitudes of these points from the map. Then we can solve the Weber problem on the globe, and we do not suffer from errors. This paper analyses how cylindrical projections cause distortion in the Weber problem when demands are distributed on the Northern Hemisphere. First, we demonstrate that planar solutions are always located south of the spherical solution if the Mercator projection, the equirectangular projections with standard parallels near the demands, or the equal-area projection with the same characteristic is chosen. Second, we verify that this geographical tendency is inclined to hold when the demand points, are distributed symmetrically, widely or toward the north. Received: 15 August 2001 / Accepted: 20 April 2002 This paper was partially written while the first author was visiting the Department of Geography at the Catholic University of Louvain, Louvain-la-Neuve, Belgium [1993–1994]. He is grateful for the hospitality of this department. An earlier version of this paper was presented in 1994 at the Seventh Meeting of the European Operational Research Working Group on Locational Analysis in Brussels, and in 1996 at the Fifth World Congress of the Regional Science Association International in Tokyo. The authors would also like to thank the participants as well as three anonymous referees for their constructive comments.     

Developing a bivariate spatial association measure: An integration of Pearson's r and Moran's I

 This research is concerned with developing a bivariate spatial association measure or spatial correlation coefficient, which is intended to capture spatial association among observations in terms of their point-to-point relationships across two spatial patterns. The need for parameterization of the bivariate spatial dependence is precipitated by the realization that aspatial bivariate association measures, such as Pearson's correlation coefficient, do not recognize spatial distributional aspects of data sets. This study devises an L statistic by integrating Pearson's r as an aspatial bivariate association measure and Moran's I as a univariate spatial association measure. The concept of a spatial smoothing scalar (SSS) plays a pivotal role in this task. Received: 07 November 2000 / Accepted: 02 August 2001     

Toward micro-scale spatial modeling of gentrification

 A simple preliminary model of gentrification is presented. The model is based on an irregular cellular automaton architecture drawing on the concept of proximal space, which is well suited to the spatial externalities present in housing markets at the local scale. The rent gap hypothesis on which the model's cell transition rules are based is discussed. The model's transition rules are described in detail. Practical difficulties in configuring and initializing the model are described and its typical behavior reported. Prospects for further development of the model are discussed. The current model structure, while inadequate, is well suited to further elaboration and the incorporation of other interesting and relevant effects. Received: 1 November 2001 / Accepted: 12 April 2002 Town centres data were made available by kind permission of the UK Department of the Environment, Transport and the Regions.     

Area-based tests for association between spatial patterns

 Edge effects pervade natural systems, and the processes that determine spatial heterogeneity (e.g. physical, geochemical, biological, ecological factors) occur on diverse spatial scales. Hence, tests for association between spatial patterns should be unbiased by edge effects and be based on null spatial models that incorporate the spatial heterogeneity characteristic of real-world systems. This paper develops probabilistic pattern association tests that are appropriate when edge effects are present, polygon size is heterogeneous, and the number of polygons varies from one classification to another. The tests are based on the amount of overlap between polygons in each of two partitions. Unweighted and area-weighted versions of the statistics are developed and verified using scenarios representing both polygon overlap and avoidance at different spatial scales and for different distributions of polygon sizes. These statistics were applied to Soda Butte Creek, Wyoming, to determine whether stream microhabitats, such as riffles, pools and glides, can be identified remotely using high spatial resolution hyperspectral imagery. These new “spatially explicit” techniques provide information and insights that cannot be obtained from the spectral information alone. Received 1 June 2001 / Accepted 25 October 2001     

The development of computer networks: First results from a microeconomic model

 Computer networks like the Internet are gaining importance in social and economic life. The accelerating pace of the adoption of network technologies for business purposes is a rather recent phenomenon. Many applications are still in the early, sometimes even experimental, phase. Nevertheless, it seems to be certain that networks will change the socioeconomic structures we know today. This is the background for our special interest in the development of networks, in the role of spatial factors influencing the formation of networks, and consequences of networks on spatial structures, and in the role of externalities. This paper discusses a simple economic model – based on a microeconomic calculus – that incorporates the main factors that generate the growth of computer networks. The paper provides analytic results about the generation of computer networks. The paper discusses (1) under what conditions economic factors will initiate the process of network formation, (2) the relationship between individual and social evaluation, and (3) the efficiency of a network that is generated based on economic mechanisms. Received: 5 July 2000 / Accepted: 28 November 2000     

Determining the size of spatial clusters in focused tests: Comparing two methods by means of simulation in a GIS

 Based on a four-point evaluation system consisting of accuracy, consistency, power, and chance to commit type I errors, this study compares Tango's minimum p (MinP) and Stone's maximum relative risk (MaxRR) methods for detecting focused cluster size through simulations in GIS. It reveals that the MinP method is more effective than the MaxRR method. The MinP method exhibits higher levels of accuracy and consistency; and its power and chance to commit type I errors are similar to the MinP method. The MaxRR method has a tendency to underestimate the cluster size, while the MinP method tends to overestimate the cluster size, particularly when the clusters are relatively big and have high relative risk levels. In addition, the MinP method seems to be most effective in revealing the size of clusters when clusters are neither too strong nor too weak. The lowest detection rates for clustering occur when the clustering signal is relatively weak, which is easily understandable. In practice, it might be useful to use both the methods to estimate a range of possible cluster sizes, where the MaxRR method indicates the lower estimate, while the MinP method gives the higher estimate of the cluster size. Received: 24 August 2002 / Accepted: 20 December 2002     

Spatial decision support system for home-delivered services

 We present a spatial decision support system for the non-profit sector, designed to assist planning in the area of home-delivered services such as meals on wheels. Using data collected from existing programs, current and forecasted demographic data, and a set of algorithmic tools, we provide a system for evaluating current meals on wheels facilities, and for making incremental facility location decisions that satisfy coverage and equity requirements. Received: 27 September 2000 / Accepted: 22 March 2001     

An integrated representation of spatial and temporal relationships between evolving regions

 The study of relationships between evolving regions within GIS still needs the development of operators that integrate the spatial and temporal dimensions. This paper introduces a new approach that combines topological relationships between regions in 2-dimensional space with temporal relationships between convex intervals in time. Resulting relationships are defined and visually presented within a 3-dimensional space that integrates the geographical space as a 2-dimensional space and the time line as the third dimension. Conceptual neighbourhoods are identified and extended by the concept of semi-transitions and transitions. Such a flexible framework presents the advantage of being derived from accepted relationships in both space and time. Its computational implementation is therefore compatible with current spatial and temporal GIS models. Received: May 2000 / Accepted: June 2001     

An integrated urban systems model with GIS

The main purpose of this paper is to explore a possible integration for the entire transportation modeling procedure – from data inventory to future demand forecasting – by implementing integrated land use and transportation models with a geographic information system (GIS). In order to make an integrated, procedural modeling system possible, Land Use and Transportation modeling system with GIS (LUTGIS) has been developed and presented in this paper.  There are four sub-systems in LUTGIS: (1) a data inventory system, (2) a traffic analysis zone generation system, (3) an integrated land use and transportation modeling system, and (4) a graphic user interface (GUI) system. Since the main target of this paper is to explore a possible way to create a viable system, LUTGIS integrates currently available and user-friendly computing technologies. For both transportation planners and administrative decision-makers, such an operable system is very desirable for sharing information so they may arrive at a consensus through the use of LUTGIS, an integrated land use and transportation modeling system. Received: 22 October 1998/Accepted 11 July 1999     

The parameter distributions of the integer GPS model

 A parameter estimation theory is incomplete if no rigorous measures are available for describing the uncertainty of the parameter estimators. Since the classical theory of linear estimation does not apply to the integer GPS model, rigorous probabilistic statements cannot be made with reference to the classical results. The fact that integer parameters are involved in the estimation process forces a reappraisal of the propagation of uncertainty. It is with this purpose in mind that the joint and marginal distributional properties of both the integer and non-integer parameters of the GPS model are determined. These joint distributions can also be used to determine the distribution of functions of the parameters. As an important example, the distribution of the vector of ambiguity residuals is determined. Received: 30 January 2001 / Accepted: 31 July 2001     

Control sample design using a geodemographic discriminator: An application of Super Profiles

 The development and application of an innovative sampling framework for use in a British study of the early detection of gastric cancer are described. The Super Profiles geodemographic discriminator is used in the identification of geographically distinct control and contrast areas from which samples of cancer registry case records may be drawn for comparison with the records of patients participating in the gastric cancer intervention project. Preliminary results of the application of the framework are presented and confirm its effectiveness in satisfactorily reflecting known patterns of variation in cancer occurrence by age, gender and social class. The method works well for cancers with a known and clear social gradient, such as lung and breast cancer, moderately well for gastric cancer and somewhat less well for oesophageal cancer, where the social class gradient is less clear. Received: 1 January 2000 / Accepted: 18 September 2000     

A computational approach for the analysis of changes in polygon distributions

 This paper develops a computational method for analyzing changes in polygon distributions. Unmovable polygons that change discontinuously without explicit functional linkage information are discussed. Six types of primitive events are used to describe the change: 1) generation, 2) disappearance, 3) expansion, 4) shrinkage, 5) union, and 6) division. The change of polygon distributions is decomposed into a combination of these events. A computational procedure for deducing a set of events from polygon distributions of two times is proposed. The method is applied to the analysis of the spatial competition between the major and small chains of convenience stores in Tokyo, Japan. Some empirical findings are shown. Received: 3 August 2000 / Accepted: 6 February 2001