Improvement of satellite derived pollution maps with the use of a geostatistical interpolation method

 The small number of ground stations for the assessment of the spatial distribution of air pollutants motivates the search for methods that make use of satellite images. One such method, known as Differential Texture Analysis (DTA), is used to measure the Aerosol Optical Thickness in the Visible (AOTV), which correlates highly with air quality. With this method, the presence of clouds and/or land cover changes produce patches of missing values. In this paper we demonstrate that universal kriging can be used to obtain reasonable estimates for these missing values. The methodology was applied to a satellite derived AOTV map of the city of Brescia (Italy). Received: 17 July 2001 / Accepted: 11 December 2001     

Evaluating the importance of accessibility to congestion response using a GIS-based travel simulator

 This paper examines the effect of accessibility on individual response to unexpected traffic delays and congestion. The dataset used was collected by means of a travel simulator developed within a geographic information system (GIS) environment. The simulator models a commute trip where congestion takes place, and subjects are asked to respond by making a choice among alternative courses of action. Available alternatives for dealing with the unexpected traffic delay include changing the location of the planned activities or changing the activities to be performed. Accessibility to the new locations and to the different activities is computed using a cumulative measure. Analysis using CHAID tree technique found that accessibility is a good predictor of subjects' choice when responding to unexpected traffic delays. Received: September 2002 / Accepted: January 2003 Support for this research by a grant from the Center of Intelligent Transportation Research of the Ohio State University is gratefully acknowledged. The author would also like to thank Joe Weber, Mei-Po Kwan and two anonymous reviewers for their valuable comments.     

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     

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     

Geostatistical incorporation of spatial coordinates into supervised classification of hyperspectral data

 This paper presents a methodology to incorporate both hyperspectral properties and spatial coordinates of pixels in maximum likelihood classification. Indicator kriging of ground data is used to estimate, for each pixel, the prior probabilities of occurrence of classes which are then combined with spectral-based probabilities within a Bayesian framework. In the case study (mapping of in-stream habitats), accounting for spatial coordinates increases the overall producer's accuracy from 85.8% to 93.8%, while the Kappa statistic rises from 0.74 to 0.88. Best results are obtained using only indicator kriging-based probabilities, with a stunning overall accuracy of 97.2%. Significant improvements are observed for environmentally important units, such as pools (Kappa: 0.17 to 0.74) and eddy drop zones (Kappa: 0.65 to 0.87). The lack of benefit of using hyperspectral information in the present study can be explained by the dense network of ground observations and the high spatial continuity of field classification which might be spurious. Received: 12 April 2001 / Accepted: 7 September 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     

Testing spatial patterns and growth spillover effects in clusters of cities

 This paper analyzes the spatial patterns of households' distribution in clusters of cities and the effects on regional growth using spatial exploratory techniques and a model of growth that incorporates spatial location. Our empirical analysis shows that, over the 1980–1990 period, in Southern New England, patterns of spatial clustering of households did create heterogeneous growth rates in the region. Also, there is evidence that clusters of cities and isolated cities created spillover growth effects in bordering towns. Received: 5 September 2001 / Accepted: 2 August 2002     

Emerging and vector-borne diseases: Role of high spatial resolution and hyperspectral images in analyses and forecasts

 Many infectious diseases that are emerging or transmitted by arthropod vectors have a strong link to landscape features. Depending on the source of infection or ecology of the transmitting vector, micro-habitat characteristics at the spatial scale of square meters or less may be important. Recently, satellite images have been used to classify habitats in an attempt to understand associations with infectious diseases. Whether high spatial resolution and hyperspectral (HSRH) images can be useful in studies of such infectious diseases is addressed. The nature of questions that such studies address and the desired accuracy and precision of answers will determine the utility of HSRH data. Need for such data should be based on the goals of the effort. Examples of kinds of questions and applications are discussed. The research implications and public health applications may depend on available analytic tools as well as epidemiological observations. Received: 30 July 2001 / Accepted: 14 October 2001     

Regularization of geopotential determination from satellite data by variance components

 Different types of present or future satellite data have to be combined by applying appropriate weighting for the determination of the gravity field of the Earth, for instance GPS observations for CHAMP with satellite to satellite tracking for the coming mission GRACE as well as gradiometer measurements for GOCE. In addition, the estimate of the geopotential has to be smoothed or regularized because of the inversion problem. It is proposed to solve these two tasks by Bayesian inference on variance components. The estimates of the variance components are computed by a stochastic estimator of the traces of matrices connected with the inverse of the matrix of normal equations, thus leading to a new method for determining variance components for large linear systems. The posterior density function for the variance components, weighting factors and regularization parameters are given in order to compute the confidence intervals for these quantities. Test computations with simulated gradiometer observations for GOCE and satellite to satellite tracking for GRACE show the validity of the approach. Received: 5 June 2001 / Accepted: 28 November 2001     

Space-time accessibility measures: A geocomputational algorithm with a focus on the feasible opportunity set and possible activity duration

 Space-time accessibility measures have received much attention in recent years due to their sensitivity to differences in individual ability to participate in activities in space and time. Despite the conceptual attractiveness and robustness of space-time measures, only few attempts have been made to operationalize them to date. Research that seeks to improve space-time accessibility measures is still sorely needed. This study seeks to enhance space-time accessibility measures through developing a new operational method and GIS-based algorithm that better represents the space-time characteristics of urban opportunities (e.g. their geographical distribution and opening hours) and human activity-travel behavior (e.g. delay times, minimum activity participation time, and maximum travel time threshold). The proposed method not only takes into account the number and size of opportunities, but also the possible activity duration at each activity location given its opening hours and the effect of transport network topology (e.g. one-way streets, turn restrictions and over-pass). Incorporating these elements into space-time measures helps overcome several shortcomings of previous approaches to evaluating space-time accessibility. Received: 15 September 2002 / Accepted: 10 February 2003 A version of this paper was presented at the 98th Annual Meeting of the Association of American Geographers, Los Angeles, March 19-23, 2002. We thank Joe Weber for providing the digital transport network with travel speeds and a version of the geocomputational algorithm he used in his study (Weber 2001), upon which our developmental effort has been based. We are also grateful to the helpful comments and suggestions of the reviewers.     

Short-arc analysis of intersatellite tracking data in a gravity mapping mission

 A technique for the analysis of low–low intersatellite range-rate data in a gravity mapping mission is explored. The technique is based on standard tracking data analysis for orbit determination but uses a spherical coordinate representation of the 12 epoch state parameters describing the baseline between the two satellites. This representation of the state parameters is exploited to allow the intersatellite range-rate analysis to benefit from information provided by other tracking data types without large simultaneous multiple-data-type solutions. The technique appears especially valuable for estimating gravity from short arcs (e.g. less than 15 minutes) of data. Gravity recovery simulations which use short arcs are compared with those using arcs a day in length. For a high-inclination orbit, the short-arc analysis recovers low-order gravity coefficients remarkably well, although higher-order terms, especially sectorial terms, are less accurate. Simulations suggest that either long or short arcs of the Gravity Recovery and Climate Experiment (GRACE) data are likely to improve parts of the geopotential spectrum by orders of magnitude. Received: 26 June 2001 / Accepted: 21 January 2002     

A spectral optimally interpolated mean sea surface from satellite radar altimetry

 A technique is presented for the development of a high-precision and high-resolution mean sea surface model utilising radar altimetric sea surface heights extracted from the geodetic phase of the European Space Agency (ESA) ERS-1 mission. The methodology uses a cubic-spline fit of dual ERS-1 and TOPEX crossovers for the minimisation of radial orbit error. Fourier domain processing techniques are used for spectral optimal interpolation of the mean sea surface in order to reduce residual errors within the initial model. The EGM96 gravity field and sea surface topography models are used as reference fields as part of the determination of spectral components required for the optimal interpolation algorithm. A comparison between the final model and 10 cycles of TOPEX sea surface heights shows differences of between 12.3 and 13.8 cm root mean square (RMS). An un-optimally interpolated surface comparison with TOPEX data gave differences of between 15.7 and 16.2 cm RMS. The methodology results in an approximately 10-cm improvement in accuracy. Further improvement will be attained with the inclusion of stacked altimetry from both current and future missions. Received: 22 December 1999 / Accepted: 6 November 2000     

Deriving rules from activity diary data: A learning algorithm and results of computer experiments

 Activity-based models consider travel as a derived demand from the activities households need to conduct in space and time. Over the last 15 years, computational or rule-based models of activity scheduling have gained increasing interest in time-geography and transportation research. This paper argues that a lack of techniques for deriving rules from empirical data hinders the further development of rule-based systems in this area. To overcome this problem, this paper develops and tests an algorithm for inductively deriving rules from activity-diary data. The decision table formalism is used to exhaustively represent the theoretically possible decision rules that individuals may use in sequencing a given set of activities. Actual activity patterns of individuals are supplied to the system as examples. In an incremental learning process, the system progressively improves on the selection of rules used for reproducing the examples. Computer experiments based on simulated data are performed to fine-tune rule selection and rule value update functions. The results suggest that the system is effective and fairly robust for parameter settings. It is concluded, therefore, that the proposed approach opens up possibilities to derive empirically tested rule-based models of activity scheduling. Follow-up research will be concerned with testing the system on empirical data. Received: 31 January 2001 / Accepted: 13 September 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     

Formation of surface spherical harmonic normal matrices and application to high-degree geopotential modeling

 The structure of normal matrices occurring in the problem of weighted least-squares spherical harmonic analysis of measurements scattered on a sphere with random noises is investigated. Efficient algorithms for the formation of the normal matrices are derived using fundamental relations inherent to the products of two surface spherical harmonic functions. The whole elements of a normal matrix complete to spherical harmonic degree L are recursively obtained from its first row or first column extended to degree 2L with only O(L ⁴) computational operations. Applications of the algorithms to the formation of surface normal matrices from geoid undulations and surface gravity anomalies are discussed in connection with the high-degree geopotential modeling. Received: 22 March 1999 / Accepted: 23 December 1999     

The AUSGeoid98 geoid model of Australia: data treatment, computations and comparisons with GPS-levelling data

 The AUSGeoid98 gravimetric geoid model of Australia has been computed using data from the EGM96 global geopotential model, the 1996 release of the Australian gravity database, a nationwide digital elevation model, and satellite altimeter-derived marine gravity anomalies. The geoid heights are on a 2 by 2 arc-minute grid with respect to the GRS80 ellipsoid, and residual geoid heights were computed using the 1-D fast Fourier transform technique. This has been adapted to include a deterministically modified kernel over a spherical cap of limited spatial extent in the generalised Stokes scheme. Comparisons of AUSGeoid98 with GPS and Australian Height Datum (AHD) heights across the continent give an RMS agreement of ±0.364 m, although this apparently large value is attributed partly to distortions in the AHD. Received: 10 March 2000 / Accepted: 21 February 2001     

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     

Adjacency selection in Markov Random Fields for high spatial resolution hyperspectral data

 Markov Random Fields, implemented for the analysis of remote sensing images, capture the natural spatial dependence between band wavelengths taken at each pixel, through a suitable adjacency relationship between pixels, to be defined a priori. In most cases several adjacency definitions seem viable and a model selection problem arises. A BIC-penalized Pseudo-Likelihood criterion is suggested which combines good distributional properties and computational feasibility for analysis of high spatial resolution hyperspectral images. Its performance is compared with that of the BIC-penalized Likelihood criterion for detecting spatial structures in a high spatial resolution hyperspectral image for the Lamar area in Yellowstone National Park. Received: 9 March 2001 / Accepted: 2 August 2001