Local Spatial Autocorrelation Statistics: Distributional Issues and an Application

The statistics G_i(d) and G_i*(d), introduced in Getis and Ord (1992) for the study of local pattern in spatial data, are extended and their properties further explored. In particular, nonbinary weights are allowed and the statistics are related to Moran's autocorrelation statistic, I. The correlations between nearby values of the statistics are derived and verified by simulation. A Bonferroni criterion is used to approximate significance levels when testing extreme values from the set of statistics. An example of the use of the statistics is given using spatial-temporal data on the AIDS epidemic centering on San Francisco. Results indicate that in recent years the disease is intensifying in the counties surrounding the city.     

A Generalized Randomization Approach to Local Measures of Spatial Association

This article establishes a unified randomization significance testing framework upon which various local measures of spatial association are commonly predicated. The generalized randomization approach presented is composed of two testing procedures, the extended Mantel test and the generalized vector randomization test. These two procedures employ different randomization assumptions, namely total and conditional randomization, according to the way in which they incorporate local measures. By properly specifying necessary matrices and vectors for a particular local measure of spatial association under a particular randomization assumption, the generalized randomization approach as a whole yields a reliable set of equations for expected values and variances, which then is confirmed by a Monte Carlo simulation utilizing random permutations.     

A Local Indicator of Multivariate Spatial Association: Extending Geary's c

This paper extends the application of the Local Geary c statistic to a multivariate context. The statistic is conceptualized as a weighted distance in multivariate attribute space between an observation and its geographical neighbors. Inference is based on a conditional permutation approach. The interpretation of significant univariate Local Geary statistics is clarified and the differences with a multivariate case outlined. An empirical illustration uses Guerry's classic data on moral statistics in 1830s France.     

Controlling for Doubt and Uncertainty Through Multiple Lines of Evidence: A New Look at the Mesoamerican Nahua Migrations

Nahuatl represents a relatively recent extension of the Uto-Aztecan language family into Mesoamerica. Ethnohistorians have linked Nahuatl's arrival to the historically attested migrations of nomadic people into central Mexico in the last centuries before the Spanish Conquest. Archaeologists have tended to treat migration as an explanation for a change in material culture rather than a social question to be examined theoretically. We approach this migration through the comparison of multiple data sets and conclude that what has previously been treated as a historical event is instead part of a longer term process tying together Mesoamerica's northern periphery with its highland core. While we find that certain themes from migration theory are reflected in this preindustrial migration as well, other variables are unique and bode well for archaeology's ability to address and contribute to theoretical issues relating to migration.     

Applying Local Indicators of Spatial Association to Analyze Longitudinal Data: The Absolute Perspective

Local Indicators of Spatial Association (LISA) are a class of spatial statistical methods that have been widely applied in various scientific fields. When applying LISA to make longitudinal comparisons of spatial data, a common way is to run LISA analysis at each time point, then compare the results to infer the distributional dynamics of spatial processes. Given that LISA hinges on the global mean value that often varies across time, the LISA result generated at time T_i reflects the spatial patterns strictly with respect to T_i. Therefore, the typical comparative cross-sectional analysis with LISA can only characterize the relative distributional dynamics. However, the relative perspective alone is inadequate to comprehend the full picture, as the patterns are not directly associated with the changes of the spatial process’s intensity. We argue that it is important to obtain the absolute distribution dynamics to complement the relative perspective, especially for tracking how spatial processes evolve across time at the local level. We develop a solution that modifies the significance test when implementing LISA analysis of longitudinal data to reveal and visualize the absolute distribution dynamics. Experiments were conducted with Mongolian livestock data and Rwanda population data.     

Regional Coverage Maximization: A New Model to Account Implicitly for Complementary Coverage

Achieving the greatest coverage using limited resources has long been a concern for regional planners. Since the 1970s, a variety of models have been studied and relied upon. Finding ways to best represent geographical space remains a challenge to many researchers. Solutions suggested by models vary greatly with different space representation schemes. For example, in the past, points have been widely adopted to represent spatial demand for coverage. However, this simple abstraction of geographical space could bring about inaccuracies and uncertainties, and often compromises its solution quality. Considering that demand can be area based, which is beyond points, objects of different shapes have been proposed as an alternative for representation. With advances in geographic information systems (GISs), the new representation scheme using objects has recently received much attention. Compared with the straightforward point‐based abstraction, spatial object representation poses considerable challenges to both model formulation and computation capability. This article revisits model development for the problem of regional coverage maximization and proposes a new formulation where coverage of spatial demand is implicitly modeled. Model testing is conducted through an application to warning siren siting in Dublin, Ohio, which has been studied by other researchers. Results demonstrate the effectiveness of the new model when compared with the existing models. Uno de los objetivos comunes en la planificación regional es lograr la máxima cobertura de un servicio con recursos limitados. Desde la década de los 70s se vienen utilizado una serie de modelos conocidos. Sin embargo, la representación adecuada del espacio geográfico de dichos modelos sigue siendo un problemática para muchos investigadores. Las soluciones derivadas de los modelos varían considerablemente de acuerdo a los diferentes esquemas de representación utilizados. El uso de puntos por ejemplo, ha sido ampliamente utilizado en el pasado como esquema de representación espacial de la demanda a ser cubierta por el servicio. Sin embargo, esta simple abstracción del espacio geográfico puede provocar imprecisiones e incertidumbres que a menudo afectan la calidad de la solución matemática del modelo. En contraste, si la demanda se define como un área que abarca una extensión que va más allá de los puntos es posible proponer—como lo han hecho varios recientemente‐ el uso de objetos espaciales (de formas variadas) como una alternativa sensata de representación. Con los avances en los sistemas de información geográfica (SIG), este nuevo esquema de representación ‐que usa objetos especiales‐ han recibido considerable atención. En contraste con esquemas sencillos como el basado en puntos, la representación de objetos espaciales presenta varios desafíos en cuanto a la formulación y computación del modelo. El presente artículo reseña el desarrollo del modelamiento del problema de máxima cobertura regional (problem of regional coverage maximization) y propone una nueva formulación en la cual la cobertura de la demanda en el espacio es modelada de manera implícita. La evaluación del modelo se realiza a través de una aplicación que usa datos de la ubicación sirenas de alarma en Dublín, Ohio. Los resultados demuestran la eficacia del nuevo modelo en comparación con los modelos existentes. 利用有限资源实现最大覆盖一直广受区域规划者关注。自20世纪70年代以来,发展了大量针对这一问题的模型研究。寻找最佳的地理空间表达方式仍是研究者面临的一大挑战。不同模型对于不同的空间表达模式变化很大。比如过去空间覆盖需求多采用点集表达。然而,这种简单的地理空间抽象方法可能会引起不精确性和不确定性,通常也会导致解决方案质量下降。考虑到需求可能是基于区域而非基于点,不同形状的对象已经被当作空间表达可替代的方式。随着GIS技术的进步,基于对象空间表达的新方案近来备受关注。较之于直接基于点的空间抽象,空间对象表达在模型的形式化表达和计算性能上均面临相当大的挑战。本文回顾了区域最大覆盖问题模型研究的发展历程,提出了一个新的蕴含空间覆盖建模需求的模型。以曾被诸多学者研究过的俄亥俄州都柏林的报警器选址问题为例对模型进行检验,结果显示新模型较现有模型更为有效。     

军事志如何记述地方经济与社会内容

军事志作为地方志系列中的一种特殊的专业志,其内容涵盖地方政治、经济、科技、文化和社会等诸多领域。如何客观、准确、恰当地记述好这些内容,直接关系到军事志的质量和价值。通常情况下,军事志在记述地方经济与社会内容时,其资料选用应遵循与军事有关、与主题相符、与地位相称的原则;记述内容应坚持以记述现状、服务军事和反映地域特色为主;记述方法应采取集中记述与穿插记述相结合、客观反映与功能分析相结合、文字记述与图表展示相结合,使军事志在记述地方经济与社会内容时,既遵循志书的基本体例规范,又反映军事专业特点。     

Deconstructing Spatial Planning: Re-interpreting the Articulation of a New Ethos for English Local Planning

This article reviews recent debates about the emergence of “spatial planning” as a new ethos for English planning, suggesting that continued uncertainty around the term's use is partly caused by a failure to consider its emergence as the product of a contested political process. Drawing on an interpretive approach to policy analysis, the article goes on to show how this new organizing principle is a complex articulation of different and potentially contradictory reform impulses. The result is to destabilize the concept of spatial planning, showing how it has been constructed as an “empty signifier”, an unstable and tension-filled discursive stake in an ongoing politics of reform. Finally, it is argued that this has significant implications for the ways in which implementation success and failure should be understood and for analysis of planning reform initiatives and systems more widely.     

The Size-adjusted Critical Region of Moran's I Test Statistics for Spatial Autocorrelation and Its Application to Geographical Areas

In this article, we explore the expression of the asymptotic approximation of the distribution function of Moran's I test statistic for the check of spatial autocorrelation, and we derive a more accurate critical value, which gives the rejection region similar to significant level α to the order of N^?1 (N = sample size). We show that in some cases our procedure effectively finds the significance of positive spatial autocorrelation in the problem testing for the lack of the spatial autocorrelation. Compared with our method, the testing procedure of Cliff and Ord (1971) is clearly ad hoc and should not be applied blindly, as they pointed out. Our procedure is derived from the theory of asymptotic expansion. We numerically analyze four types of county systems with rectangular lattices and three regional areas with irregular lattices.     

A Shape‐Based Local Spatial Association Measure (LISShA): A Case Study in Maritime Anomaly Detection

The explicit consideration of the shape of geographic features has been largely ignored in existing spatial association measures. The primary contribution of this work is the development of a new local spatial association measure—a Local Indicator of Spatial and Shape Association (LISShA). The LISShA measure is modeled after local Geary's Spatial Autocorrelation measure with distance between shapes, calculated using the Small–Le metric, replacing difference between attribute values and the spatial neighborhood defined by Fréchet distance. We provide some explanation of these metrics and show, in detail, how the LISShA and proposed moments are calculated in a one‐dimensional context in a case study of maritime anomaly detection.     

Globalisation,Gentrification and Spatial Hierarchies in and beyond New South Wales: the Local/Global Nexus

Popular visions of globalisation envisage the collapse of physical space as a significant determinant in social relations. The rapid speed at which movements of capital and information occur are touted as evidence that the constraints of physical space are eroding. The emergence of a global network of persons referred to as the transnational elite further supports these popular perceptions. Characterised as highly educated professionals employed in globally aligned industries, the transnational elite seemingly construct their individual and group identities beyond the scale of the local. However, research undertaken in Newcastle and Sydney with gentrifiers actively constructing their ‘global personas’ problematise popular discourses of globalisation as contributing to the decline of space as fundamental to identity construction. As an emergent élite global community, the gentrifiers create complex cognitive maps of spatial desirability reinforcing the significance of specific places. Through this process, places are ranked according to their global significance forming complex spatial hierarchies. Consequently, some places are cast as global and hence desirable, while others are stigmatised as undesirable non-global spaces.     

Relative Variability in Streetscape Skeletons and Spatial Association: Application for Identifying Harmonious and Inharmonious Streetscape Skeletons in Tokyo

Whether or not a streetscape skeleton (defined as the 3D street space) is harmonious depends on the degree of difference between heights and setbacks of adjacent buildings, which is called the relative variability in the streetscape skeleton, but this has generally been overlooked. Because streetscape skeletons are ambiguous, evaluating whether or not they are harmonious is thus conceptually and technically challenging. This article, therefore, considers the relative variability in streetscape skeletons and their spatial associations and answers the following question: where are harmonious or inharmonious streetscape skeletons locally clustered? The relative variability in the streetscape skeletons in the districts of the Tokyo metropolitan region was computed, where building heights and setbacks are directly controlled through streetscape promotion district planning stipulated in the City Planning Act. The spatial association of the relative variability in streetscape skeletons was then visualized to identify where streetscape skeletons are harmonious and inharmonious. The results showed that although harmonious streetscape skeletons are spatially clustered inside the domain bounded by wider streets, such clusters are small and spatially scattered. We, therefore, concluded that the effectiveness of direct controls through streetscape-promoting district planning to maintain and create harmonious streetscape skeletons is spatially limited and thus insufficient.     

口述史在地方志领域的地位与价值

对于地方志和口述史的关系,可以追溯到地方志的源头,地方志在各个发展时期不同程度地运用了口述史成果。口述史方法在地方志领域的运用可以填补文献资料的空白,可以补救文献资料的偏差和讹误,可以完善地方志记述的内容,有利于正确认识并科学反映事物。并探讨口述史对地方志的四点理念启示:一是将历史的讲述权交还给当事者,二是重视第一手资料,三是多元的历史视角,四是关注历史与人的关系。     

The Local Implications of Major Job Transformations in the City: A Spatial Microsimulation Approach

The changing dynamics of regional and local labor markets during the last decades have led to an increasing labor market segmentation and socioeconomic polarization and to a rise of income inequalities at the regional, urban, and intraurban level. These problems call for effective social and local labor market policies. However, there is also a growing need for methods and techniques capable of efficiently estimating the likely impact of social and economic change at the local level. For example, the common methodologies for estimating the impacts of large firm openings or closures operate at the regional level. The best of these models disaggregate the region to the city (Armstrong 1993; Batey and Madden 1983). This paper demonstrates how spatial microsimulation modeling techniques can be used for local labor market analysis and policy evaluation to assess these impacts (and their multiplier effects) at the local level‐to measure the effects on individuals and their neighborhood services. First, we review these traditional macroscale and mesoscale regional modeling approaches to urban and regional policy analysis and we illustrate their merits and limitations. Then, we examine the potential of spatial microsimulation modeling to create a new framework for the formulation, analysis and evaluation of social and local labor market policies at the individual or household level. Outputs from a local labor market microsimulation model for Leeds are presented. We show how first it is possible to investigate the interdependencies between individual's or households labor market attributes at the microscale and to model their accessibilities to job opportunities in different localities. From this base we show how detailed what‐if microspatial analysis can be performed to estimate the impact of major changes in the local labor market through job losses or gains, including local multiplier effects.     

Multiple Trajectories: A Critique of Industrial Restructuring and the New Institutionalism

This article argues that the agrarian studies literature sheds new light on the multiple,nonlinear trajectories of capitalist development occurring in the context of accelerating global integration. Cast in relation to classical political economy, work on agrarian change is centrally concerned with multiple paths of agrarian transformation. It attends both to historically specificforms of social property relations and to the ways that struggles over resources and labor are simultaneously struggles over culturally constructed meanings, definitions, and identities. Accordingly, it goes well beyond the "new institutionalism" that figures prominently in the literature on industrial restructuring. The article draws on recent research in globally linked industrial districts in former bantustan areas of South Africa to illustrate thecontemporary and continuing salience of agrarian histories and concepts. It also suggests how attention to multiple trajectories of sociospatial change can be used to challenge the neoliberal orthodoxy taking hold in post-apartheid South Africa.     

Testing for Local Spatial Autocorrelation in the Presence of Global Autocorrelation

A fundamental concern of spatial analysts is to find patterns in spatial data that lead to the identification of spatial autocorrelation or association. Further, they seek to identify peculiarities in the data set that signify that something out of the ordinary has occurred in one or more regions. In this paper we provide a statistic that tests for local spatial autocorrelation in the presence of the global autocorrelation that is characteristic of heterogeneous spatial data. After identifying the structure of global autocorrelation, we introduce a new measure that may be used to test for local structure. This new statistic Oi is asymptotically normally distributed and allows for straightforward tests of hypotheses. We provide several numerical examples that illustrate the performance of this statistic and compare it with another measure that does not account for global structure.