Impacts of Spatial Autocorrelation in Georeferenced Beta and Multinomial Random Variables

The literature is replete with acknowledgments that spatial autocorrelation (SA) inflates the variance of a random variable (RV), and that it also may alter other RV distributional properties. In most studies, impacts of SA have been examined only for the three most commonly used distributions: the normal, Poisson (and its negative binomial counterpart), and binomial distributions; much less is known about its effects on two other RVs that are utilized in GIScience research: the beta and the multinomial. The beta distribution—which is considered to be very flexible because it can mimic a uniform, exponential, sinusoidal, and normal RV—can be utilized to analyze the radiance of a remotely sensed image, for example. The multinomial distribution, a generalization of the binomial distribution, has been widely used for land use classification, and to describe land use change. The literature also suggests that RV impacts of negative SA, a neglected topic in spatial analysis, may differ from those of positive SA, at least for some RVs (e.g., the Poisson RV). The purpose of this article is to extend the investigation of effects of SA to beta and multinomial RVs, with both positive SA and negative SA assessed and contrasted with each other, using simulation experiments. The simulation experiments are designed to support this assessment. One of the major discoveries is that impacts of positive SA and negative SA behave similarly when a RV conforms to a normal distribution; however, maximum negative SA is unable to materialize for asymmetric RV, whereas positive SA always converges upon its maximum.     

Approximating the Length of Vehicle Routing Problem Solutions Using Complementary Spatial Information

Accurately estimating the length of Vehicle Routing Problem (VRP) distances can inform transportation planning in a wide variety of delivery and service provision contexts. This study extends the work of previous research where multiple linear regression models were used to estimate the average distance of VRP solutions with various customer demands and capacity constraints. This research expands on that approach in two ways: first, the point patterns used in estimation have a wider range of customer clustering or dispersion values as measured by the Average Nearest Neighbor Index (ANNI) as opposed to just using a Poisson or random point process; second, the tour coefficient adjusted by this complementary spatial information is shown to exhibit statistically more accurate estimations. To generate a full range of ANNI values, point patterns were simulated using a Poisson process, a Matern clustering process, and a simple sequential inhibition process to obtain random, clustered, and dispersed point patterns, respectively. The coefficients of independent variables in the models were used to explain how the spatial distributions of customers influence the VRP distances. These results demonstrate that complementary spatial data can be used to improve operational results, a concept that could be applied more broadly.     

Contact Number Properties in the Study Of Cellular Networks

The purpose of the paper is to determine if different generating processes produce cellular networks with distinctive contact number properties. Properties resulting from patterns produced by three generating processes, the Poisson, the compound negative binomial, and the “Smalley,” are examined in detail. The implications of the findings for the analysis of empirical cellular networks are discussed.     

Evaluating Crash Risk in Urban Areas Based on Vehicle and Pedestrian Modeling

This article presents a method for investigating the spatial distribution of vehicle and pedestrian traffic crashes relative to the volume of vehicle and pedestrian movement in urban areas. This method consists of two phases. First, vehicle and pedestrian traffic volumes on the street network are modeled using a space syntax configurational analysis of the network, land use data, and observed traffic data. Second, crash prediction models are fitted to the traffic crash data, using negative binomial regression models and based on traffic volume estimates and street segment lengths. The method was applied in two areas in Tel Aviv, Israel, which differ in their morphological and traffic characteristics. The case‐studies illustrated the method's capability in identifying hazardous locations on the network and examining relative crash risks. The analysis shows that an increase in vehicle or pedestrian traffic volume tends to be associated with a decrease in relative crash risk. Moreover, the spatial patterns of relative crash risks are associated with the design characteristics of urban space: areas characterized by dense street networks encourage more walking, and are generally safer for pedestrians, while those with longer street segments encourage more driving, are less safe for pedestrians, but safer for vehicles.     

Fluvial transport of bovid long bones fragmented by the feeding activities of hominins and carnivores

This study explores the hydraulic transportability of bovid long bone fragments created through hominin and carnivore carcass consumption in order to determine the effect of fluvial transport on the incidences of hominin- and carnivore-induced bone surface modifications. Transportability was determined using an oval race track flume and 311 long bone fragments from modern control collections of hominin- and carnivore-modified bone. Results show that the fluvial transport of long bone fragments is predicted by animal size class and bone specimen size, as measured by maximum cortical thickness, maximum length, and maximum width. All of these variables can be measured on fossil specimens. Long bone portion (midshaft, near-epiphysis, and epiphysis) does not affect transport and hydraulic transport does not substantially modify the incidences of tooth, percussion, and cut marking in transported or lag assemblages in low energy fluvial environments. Implications of this study are: 1) animal size classes, and cortical thickness, length, and width of long bone fragments can be used to identify fluvial winnowing in fossil assemblages; 2) analyses concerning the relative timing of hominin and carnivore carcass consumption based on the proportions of long bone fragments bearing tooth, percussion, or cut marks can be meaningfully applied to fossil assemblages deposited in low-energy fluvial environments.     

Tradeoffs between Local Taxes and Government Spending as Determinants of Business Location*

Abstract. This paper investigates the effects of local fiscal policy on the location decisions of 3,763 establishments that began operations in Maine between 1993 and 1995. Empirical results, estimated from Poisson and negative binomial regression models, indicate that businesses favor municipalities that spend high amounts on public goods and services, even when these expenditures are financed by an increase in local taxes. This suggests that a local fiscal policy of reduced government spending, to balance a tax cut, may attract fewer new businesses than a policy featuring additional spending and higher taxes.     

LONG-TERM FORECASTING OF NONCOINTEGRATED AND COINTEGRATED REGIONAL AND NATIONAL MODELS*

ABSTRACT. Johansen's (1988) multivariate test for cointegration is first applied to four models involving quarterly state data and five variables, along with a national model based on Friedman and Kuttner's (1992) model of money demand, which uses three variables. Each regional model consists of frequently used national and state series, for which theory suggests the possible cointegration of several series pairs. Beginning with all five series, however, one state model is found to be cointegrated over each of 20 successive estimation intervals. The money demand model and one state model are not cointegrated over the same intervals. In the cointegrated case, five-year experimental forecasts show that error correction mechanism (ECM) and Bayesian ECM models outperform all other approaches. More importantly, forecasting performance improves further by respecifying the ECM model based on three cointegrated series pairs rather than the five-component cointegrating vector. For the two noncointegrated systems, the first-difference model suggested by the cointegration/ error correction literature is far superior to VAR in levels over both shortand long-term horizons.     

WHAT ATTRACTS KNOWLEDGE WORKERS? THE ROLE OF SPACE AND SOCIAL NETWORKS

The aim of this paper is to identify the determinants of the geographical mobility of skilled individuals, such as inventors, across European regions. Among a large number of variables, we focus on the role of social proximity between inventors’ communities. We use a control function approach to address the endogenous nature of networks, and zero‐inflated negative binomial models to accommodate our estimations to the count nature of the dependent variable and the high number of zeros it contains. Our results highlight the importance of physical proximity, job opportunities, social networks, as well as other relational variables in mediating this phenomenon.     

Modelling Soil Erosion by Grazing: Recent Developments and New Approaches

Grazing is still widely held responsible for land degradation. The interaction between grazing and erosion is still rather poorly understood. As a consequence, counter‐measures and associated management techniques have been slow to develop in southern Europe compared with Australia. Developments in ecological and economic‐ecological modelling have improved our understanding of the processes and enhanced management capacity. Some of these developments are reviewed and two applications are described. One is a model for semi‐extensive grazing in dry Mediterranean mountain conditions in which the shepherds, on random paths, seek to optimise resources use for economic benefit. The other is a spatial optimisation of vegetation canopy to minimise erosion rates.     

降雨对榆阳区明长城单体建筑破坏模式的试验研究

前期调查分析可知,降雨对榆阳区明长城单体建筑的破坏形式包括水力侵蚀和重力侵蚀两大类,主要影响因素为降雨特征、遗址保存形态和遗址土的性质。为了进一步了解降雨对该类土遗址的破坏方式及主要影响因素作用特点,按照相似理论要求设计模型试验,研究了降雨对榆阳区明长城单体建筑的破坏模式。试验结果表明,降雨对遗址模型的破坏方式与前期调查分析结果基本一致,水力侵蚀方式有冲沟侵蚀、片流面蚀、流水淘蚀和流水冲蚀,重力侵蚀方式有坍塌和滑塌。一般A型暴雨条件下,各种水力侵蚀方式均有发生,重力侵蚀发生次数相对较少;B型暴雨条件下,主要发生片流面蚀,重力侵蚀破坏发生次数较多。通过模型试验得出的降雨对遗址模型的破坏方式及发生特点方面的结论,可以在一定程度上为降雨对该类遗址破坏的评估和防治提供参考。     

Modeling Micro-Spatial Employment Location Patterns: A Comparison of Count and Choice Approaches

This article studies employment location patterns in the Puget Sound Region of Washington State at a micro level of geography. Traditional discrete choice modeling using multinomial logit (MNL) models may be problematic at a micro level of geography due to the high dimensionality of the set of alternative locations and the likely violations of the independence from irrelevant alternatives (IIA) assumption. Count models are free from the IIA assumption and, unlike logit models, actually benefit from large numbers of alternatives by adding degrees of freedom. This study identifies the best-fitting count model as the zero-inflated negative binomial (ZINB) model, because this model more effectively addresses the large number of cells with no jobs and reflects a dual process that facilitates the identification of threshold clustering effects such as those found in specialized employment centers. The estimation and prediction results of ZINB are compared with those of MNL with a random sampling of alternatives estimated on an equivalent data set. The ZINB and MNL models largely agree on major trends, with the ZINB model providing more insightful details, but with less capacity to predict large count situations.     

POISSON GRAVITY MODELS OF SPATIAL FLOWS*

ABSTRACT The purpose of this paper is to bring together a number of results on spatial flow models, and to reformulate them within a unified probability framework based on Poisson frequencies. To do so, a class of discrete stochastic processes, designated as independent flow processes, is developed which not only yields a complete characterization of Poisson flow frequencies, but also allows a wide range of gravity-type flow models to be formulated within this distributional framework. In particular, a hierarchical classification of 12 model types is developed, and each model type is shown to be characterizable directly in terms of behavioral axioms on independent flow processes.     

Multicollinearity and Parameter Estimation in Simultaneous-Equation Models of Fluvial Systems

Simultaneous-equation statistical models are an attractive method for directly analyzing interactions among components of geomorphic systems. This study demonstrates that the utility of simultaneous-equation analysis is limited for fluvial systems by inherent multicollinearity among hydrologic and morphologic variables. Although multicollinearity for observed data may not be severe, estimation procedures for simultaneous-equation models often enhance this multicollinearity to problematic levels. Diagnostic tests are applied to three models of fluvial systems to illustrate the severity of the problem. It is recommended that investigators who develop simultaneous-equation models perform appropriate diagnostic evaluations to determine the impact of multicollinearity on specific parameter estimates.     

新国家空间理论视角下城市群的国家空间选择性研究

基于新国家空间理论,将城市群置于社会经济转型宏观背景下,分析其空间选择的国家空间项目与国家空间策略,并初步探讨了其空间效应。城市群作为目前国家空间选择性的具体形式,其产生背景、依据以及生产策略体现了国家空间选择性内涵与演变路径,是国家应对城市企业主义危机采取的一种新型城市与区域治理形式。在国家空间项目及其策略的支持下,城市群享有优先于其它地区发展的特权并实现经济快速发展,从而培育地方增长极并推动区域协调发展。然而,城市群的空间选择并未改变城市企业主义的逻辑而是将其转移到了区域尺度,并且存在城市间竞争激烈等一系列问题,亟待与其它空间项目与策略的配套实施以实现区域崛起并提高国家竞争力。     

Borders Moderating Distance: A Social Network Analysis of Spatial Effects on Policy Interaction

The present paper examines the importance of integrating geographical effects into the analysis of social networks. Specifically, we study the impacts of spatial distance and territorial borders on information exchange within two European cross-border regions where there is evidence of extensive cross-border political interaction in the domain of public transportation. We use exponential random graph models to review how these spatial factors influence policy interaction. We show how the effect of distance on the exchange of information between organizations is less obvious than it seems at first sight, when we control for endogenous networks effects with which it tends to be confounded. We also explore moderating effects among the spatial factors studied and in particular how the effect of distance affects information exchange by territoriality. While the probability of interaction decreases with distance in the context of domestic ties, distance does not exert the same friction when it comes to cross-border ties. These findings suggest that borders are not necessarily a barrier to interaction and that peripheral actors located in border regions may bridge distance in order to access strategic information they do not have access to within their territorial jurisdiction and is likely concentrated in foreign decision centers.     

A Dynamic Analysis of Interaction Data: U.S. Rail Freight Flows, 1972-81

The purpose of this paper is to extend Poisson regression to the analysis of spatial interactions over time. The methodology involves derivation of models using information methods and calibration using Poisson regression. Poisson regression is then used to analyze interannual variation in U.S. rail freight flows, 1972-81. Findings indicate that import and export variability is less important than is flow variability. Import and export variability is highest for the northeastern United States, but flow variability is highest for the southern and western United States. This has implications for the specification of dynamic models of commodity flow.     

Reducing Errors in Rainfall Estimates through Rain Gauge Location

Facility location models are examined as a framework for generating rain gauge networks designed to reduce errors in mean areal precipitation (MAP) estimation. Errors in estimating MAP may be divided into two types: (i) capture error, not observing a storm which occurs in a gauged area, and (ii) extrapolation error, using a rain gauge measurement to represent a heterogeneous area. In this paper, five rain gauge location models are developed to minimize these errors. The models include adaptations of the maximal covering location problem, the p-median model, and three models derived from multicriteria cluster analysis. The models are tested using precipitation data from an experimental watershed maintained by the U.S. Department of Agriculture in Arizona. Analysis of the results reveals, for the particular watershed, that (1) in sparse networks, location of rain gauges can play a larger role than number of rain gauges in reducing errors in MAP estimates; (2) models based on mean hydrologic data provide nearly as good networks as models based on spatially correlated data; and (3) models yielding the best networks for estimating precipitation for flood predictions are different from the models providing the best precipitation estimates for low flow forecasts.     

Analyzing the Relationship Between Smoking and Coronary Heart Disease at the Small Area Level: A Bayesian Approach to Spatial Modeling

We model the relationship between coronary heart disease and smoking prevalence and deprivation at the small area level using the Poisson log-linear model with and without random effects. Extra-Poisson variability (overdispersion) is handled through the addition of spatially structured and unstructured random effects in a Bayesian framework. In addition, four different measures of smoking prevalence are assessed because the smoking data are obtained from a survey that resulted in quite large differences in the size of the sample across the census tracts. Two of the methods use Bayes adjustments of standardized smoking ratios (local and global adjustments), and one uses a nonparametric spatial averaging technique. A preferred model is identified based on the deviance information criterion. Both smoking and deprivation are found to be statistically significant risk factors, but the effect of the smoking variable is reduced once the confounding effects of deprivation are taken into account. Maps of the spatial variability in relative risk, and the importance of the underlying covariates and random effects terms, are produced. We also identify areas with excess relative risk.