Crime Risk Maps: A Multivariate Spatial Analysis of Crime Data

In crime analyses, maps showing the degree of risk help police departments to make decisions on operational matters, such as where to patrol or how to deploy police officers. This study statistically models spatial crime data for multiple crime types in order to produce joint crime risk maps. To effectively model and map the spatial crime data, we consider two important characteristics of crime occurrences: the spatial dependence between sites, and the dependence between multiple crime types. We reflect both characteristics in the model simultaneously using a generalized multivariate conditional autoregressive model. As a real‐data application, we examine the number of incidents of vehicle theft, larceny, and burglary in 83 census tracts of San Francisco in 2010. Then, we employ a Bayesian approach using a Markov chain Monte Carlo method to estimate the model parameters. Based on the results, we detect the crime hotspots, thus demonstrating the advantage of using a multivariate spatial analysis for crime data.     

桂林旅游景区书法景观符号效应分析

书法景观是具有中国特色的特殊文化景观和文化符号,广泛应用于旅游景区而成为旅游景观的一种重要类型.本文以桂林旅游景区的书法景观为案例进行研究,结果表明,书法景观作为旅游景区的重要人文景观,旅游者总体上对其具有较高的认知和鉴赏兴趣;书法景观对旅游者产生了一定程度的符号效应,具体表现在书法鉴赏、文化象征、审美引导3个方面,对应于外在行为、文化环境知觉、景观审美活动3个层次的行为效应.书法景观的符号效应在书法鉴赏方面存在显著差异,而在文化象征和审美引导方面无显著差异.书法景观符号效应研究对于揭示人们的地方感和环境行为与书法景观之间的关系、旅游景区书法景观的设计和景区文化氛围的营造等具有指导意义.     

An Operator of Smoothing and Measures of Homogeneity of Linearly Ordered Geographical Structures

Geographical structures consisting of a sequence of ratios are examined from the point of view of homogeneity. Several measures of homogeneity are introduced. It is shown that any two such structures are not necessarily comparable in terms of homogeneity and their measures of homogeneity do not necessarily agree. One way of achieving agreement among homogeneity measures is to link the homogeneity of structures to the operation of smoothing, based on one of the properties stated by C. E. Shannon for entropy in information theory.     

Bosnia: The Crime of Appeasement

Few international journalists have been as intimately involved in the conflict in former Yugoslavia as Ed Vulliamy. In this vivid personal account of the war years he argues that the international community's response to Serbian claims amounted to nothing less than appeasement.     

Applying Geostatistical Analysis to Crime Data: Car-Related Thefts in the Baltic States

Geostatistical methods have rarely been applied to area-level offense data. This article demonstrates their potential for improving the interpretation and understanding of crime patterns using previously analyzed data about car-related thefts for Estonia, Latvia, and Lithuania in 2000. The variogram is used to inform about the scales of variation in offense, social, and economic data. Area-to-area and area-to-point Poisson kriging are used to filter the noise caused by the small number problem. The latter is also used to produce continuous maps of the estimated crime risk (expected number of crimes per 10,000 habitants), thereby reducing the visual bias of large spatial units. In seeking to detect the most likely crime clusters, the uncertainty attached to crime risk estimates is handled through a local cluster analysis using stochastic simulation. Factorial kriging analysis is used to estimate the local- and regional-scale spatial components of the crime risk and explanatory variables. Then regression modeling is used to determine which factors are associated with the risk of car-related theft at different scales.     

The Persistence of Theocracy: Hawthorne's The Scarlet Letter

This article argues that Nathaniel Hawthorne's The Scarlet Letter can provide insight into the persistent appeal of the moral and political certitudes that theocracy offers and that can serve as a corrective to liberal secularism's often myopic tendency to downplay the continuing moral and political appeal of religious belief and authority. Focusing on three puzzles raised in the structure and narrative of The Scarlet Letter, the article explores Hawthorne's consideration of theocracy as a foundation in the past, as an antidote to the modern tendency toward materialism, and as a persistent alternative that deserves continued reflection.     

Analyzing Space–Time Crime Incidents Using Eigenvector Spatial Filtering: An Application to Vehicle Burglary

Poisson models generally are utilized in analyzing spatial patterns of crime count data. When spatial autocorrelation is present, these models are extended to account for it. Among various methods, eigenvector spatial filtering (ESF) furnishes an efficient means of analysis. However, because space–time crime data have temporal components as well as spatial components, Poisson models need to be further adjusted to reflect the two types of components simultaneously. This article discusses how the ESF method can be utilized to model space–time crime data, extending the generalized linear mixed model specification for it. This approach is illustrated with an application to space–time vehicle burglary incidents in the city of Plano, Texas, during 2004–2009. Los modelos de Poisson generalmente se utilizan en el análisis de los patrones espaciales de los datos de recuento de crimen. Cuando hay autocorrelación espacial, estos modelos son modificados para dar cuenta de ello. Entre los diversos métodos existentes, el método Eigenvector (autovector, vector propio) de filtrado espacial (Eigenvector Spatial Filtering‐ESF) proporciona un medio eficaz para dicho análisis. Sin embargo, dado que los datos de criminalidad espacio‐temporales tienen tanto componentes temporales como espaciales, los modelos tipo Poisson requieren de un ajuste adicional para reflejar ambos tipos de componentes de manera simultánea. El artículo presente expone cómo el método ESF puede ser utilizado para modelar datos espacio‐temporales sobre delitos mediante la modificación del modelo mixto lineal generalizado (Generalized Linear Mixed Model‐GLMM). El procedimiento propuesto se ilustra con el caso de incidentes espacio‐temporales de robos de vehículos en la ciudad de Plano, Texas, durante 2004–2009. 泊松模型一般用于犯罪计数数据的空间模式分析中,当空间自相关关系呈现时,这类模型可扩展以解释潜在的分布特征。在各种模型中,特征向量空间滤波（ESF）提供了一种有效的分析方法。然而,由于时空犯罪数据包含时间和空间组分,因此泊松模型需要进一步调整以同时反映这两种不同类型的数据。本文讨论了如何利用特征向量空间滤波(ESF)模型对时空犯罪数据进行建模,并采用扩展广义线性混合模型(GLMM)进行规范。最后,以德克萨斯州普莱诺市2004‐2009年的车辆盗窃案数据进行了实证验证。     

An Information-theoretic Analysis: An Application to Soviet-COMECON Trade Flows

This paper develops a classificatory methodology designed to assign geographic entities to groupings based upon the multivariate flow profiles displayed by the entities and a dispersion statistic designed to detect dynamic shifts in these flow profiles over time. Information statistic, provide the mathematical basis of the analysis and the changing trade profiles of the member nations of COMECON provide an illustrative case study.     

Dendrochronological Flood-frequency Analysis: An Australian Application

Dendrochronological studies have received little attention in Australia and it appears that the methodology is not well understood. This paper describes dendrochronological techniques available in riparian environments and applies them to a small reach of the Hawkesbury River. Results of field investigations into the relationships between flooding and associated tree-ring variability were used to reconstruct partial duration flood-frequency data. The ring-width chronologies of 39 trees were transformed into three indices that made interpretation with respect to flooding possible: (1) a width-index: (2) an annual-sensitivity (AS) index; and (3) a tilting vector. It was assumed that floods would either suppress growth or alter the annual distribution of new wood about the tree bole. Width-indicies and tilting vectors provided the most reliable flooding information. Much reduced growth rates at low elevations supported initial hypotheses and led to the establishment of a relationship between growth-rate and frequency of inundation. The reconstructed flood-frequency curve closely matched the historical data-set although underestimation occured at higher levels due to limited sample size. Analyses indicate that dendrochronological investigations of exotic riparian trees provide detailed flooding information, but techniques may also be used to provide minimum dates of fluvial landforms and date recent channel changes.     

Categories of Local Economic Development: An Empirical Analysis

In examining local economic development incentives, scholars have found it useful to employ typologies of development practices. Such typologies have been based on assumptions that techniques reflect functional categories, such as marketing and financial incentives, or can be organized by the nature of costs and benefits, or by the nature of incentive goals. While useful heuristic devices, little effort has been made to test these typologies empirically. This research note provides an empirically based typology of local economic development incentives, using data from 967 cities collected by the International City Management Association.     

中国古代文明可持续发展的原因分析

中国古代文明持续发展,在世界文明史上是极为少见的。究其原因为,一方面是地理环境的基础作用,独特地理位置、封闭而又复杂的地理环境使其然;另一方面,中国古代大一统的历史和文化起着决定性的作用。相对封闭、完整且一脉相承的文化是其内在动因;人口、土地开发和技术水平三者关系的协调是其前提;先进的农耕制对土地资源的保护是其基础;文明中心随环境而变迁,保证了古代文明的持续发展。     

GeoDa : An Introduction to Spatial Data Analysis

This article presents an overview of GeoDa™, a free software program intended to serve as a user-friendly and graphical introduction to spatial analysis for non-geographic information systems (GIS) specialists. It includes functionality ranging from simple mapping to exploratory data analysis, the visualization of global and local spatial autocorrelation, and spatial regression. A key feature of GeoDa is an interactive environment that combines maps with statistical graphics, using the technology of dynamically linked windows. A brief review of the software design is given, as well as some illustrative examples that highlight distinctive features of the program in applications dealing with public health, economic development, real estate analysis, and criminology.     

Analyzing Hotspots of Crime Using a Bayesian Spatiotemporal Modeling Approach: A Case Study of Violent Crime in the Greater Toronto Area

Conventional methods used to identify crime hotspots at the small‐area scale are frequentist and employ data for one time period. Methodologically, these approaches are limited by an inability to overcome the small number problem, which occurs in spatiotemporal analysis at the small‐area level when crime and population counts for areas are low. The small number problem may lead to unstable risk estimates and unreliable results. Also, conventional approaches use only one data observation per area, providing limited information about the temporal processes influencing hotspots and how law enforcement resources should be allocated to manage crime change. Examining violent crime in the Regional Municipality of York, Ontario, for 2006 and 2007, this research illustrates a Bayesian spatiotemporal modeling approach that analyzes crime trend and identifies hotspots while addressing the small number problem and overcoming limitations of conventional frequentist methods. Specifically, this research tests for an overall trend of violent crime for the study region, determines area‐specific violent crime trends for small‐area units, and identifies hotspots based on crime trend from 2006 to 2007. Overall violent crime trend was found to be insignificant despite increasing area‐specific trends in the north and decreasing area‐specific trends in the southeast. Posterior probabilities of area‐specific trends greater than zero were mapped to identify hotspots, highlighting hotspots in the north of the study region. We discuss the conceptual differences between this Bayesian spatiotemporal method and conventional frequentist approaches as well as the effectiveness of this Bayesian spatiotemporal approach for identifying hotspots from a law enforcement perspective.