This study examines the relative effects of distance‐dependent versus localized amenities in changing urban spatial structure of residential location values within urban areas. We also investigate the spatio‐temporal patterns of neighborhood value, which is the sum of distance‐dependent and localized amenity effects, at a local community scale. We use a hedonic housing price model that controls for

Tobler’s first law of geography is widely recognized as reflecting broad empirical realities in geography. Its key concepts of “near” and “related” are intuitive in a univariate setting. However, when moving to the joint consideration of spatial patterns among multiple variables, the combination of attribute similarity and geographical similarity that underlies the concept of spatial autocorrelation

Simultaneous studies of multiple health conditions over geographic areas can be enhanced by the principal component analysis (PCA). However, the presence of spatial autocorrelation may induce nonlinearity that compromises PCA. This article presents an approach that combines the residual standardization method in PCA with a spatial regression method to account for spatial autocorrelation. It first estimates

The urban structure of large Chinese cities has been well researched, but a systematic analysis of polycentric urban development and the determinants of subcenter formation across municipal districts in cities at the prefectural level and above (PLACMD) is lacking. Using geospatial big data and spatial analysis methods, we measure the urban spatial structure of all 294 PLACMDs to determine the polycentric

In this article, we propose a new approach for assessing the extent to which schools are successful in mixing students from different backgrounds. It is based on a comparison of variation in the composition of the student population in small‐scale residential neighborhoods with variation in the composition of the student population at local schools. From this we compute a measure that corresponds to

This article examines the characteristics of residents moving into new rail transit neighborhoods using longitudinal, individual‐level data from the Housing Mortgage Disclosure Act. To disentangle the role of transit from other neighborhood amenities that may give rise to shifts in the socioeconomic or demographic profile of homebuyers, an exploratory text analysis is first performed on property advertisements

This article examines macro‐level contextual parameters and individual‐based factors deemed in the literature to directly influence individuals’ daily mobility practices. It considers the urban structure, place of residence, situation in the social hierarchy, and position in the life course. Taking its inspiration from approaches highlighting segregation at destination place and studies focusing on

In a 2020 Geographical Analysis paper, Pazitka, Wójcik, and Knight aimed to examine and challenge the validity of office‐location approaches for modeling intercity business flows. Their argument proceeded in three steps: (1) critique the office location approach and specifically the interlocking world city network model (IWCNM), (2) introduce their own inter‐organizational project approach (IOPA) as

In this commentary, I evaluate the potential of bipartite network projections of multilocational corporations in quantitative structural analyses of world/global cities. My starting point is that the Geographical Analysis paper by Pazitka, Wójcik, and Knight (2020) paper provides a number of useful critical observations in this regard, but their analysis is also incomplete and at points potentially

Geographically weighted quantile regression (GWQR) has been proposed as a spatial analytical technique to simultaneously explore two heterogeneities, one of spatial heterogeneity with respect to data relationships over space and one of response heterogeneity across different locations of the outcome distribution. However, one limitation of GWQR framework is that the existing inference procedures are

This article assesses the locally varying effects of gun ownership levels on total and gun homicide rates in the contiguous United States using cross‐sectional county data for the period 2009–2015. Employing a multiscale geographically weighted instrumental variables regression that takes into account spatial nonstationarity in the processes and the endogenous nature of gun ownership levels, estimates

Detection of changes in spatial processes has long been of interest to quantitative geographers seeking to test models, validate theories, and anticipate change. Given the current “data‐rich” environment of today, it may be time to reconsider the methodological approaches used for quantifying change in spatial processes. New tools emerging from computer vision research may hold particular potential

The interlocking world city network model and other office location approaches (OLAs) have become the most widely used empirical models of the world city network (WCN). Despite numerous methodological improvements, they continue to rely on a legacy of using data on office locations of firms to indirectly estimate intercity business flows. To advance the dialogue about how to improve on existing empirical

This article proposes a novel method for data‐driven identification of spatiotemporal homogeneous regions and their dynamics, enabling the exploration of their composition and extents. Using a simple network representation, the method enables temporal regionalization without the need for geographical harmonization. To allow for a transparent corroboration of our method, we use it as a basis for an

The subtitle of Geographical Analysis is “An International Journal of Theoretical Geography”, yet in fifty years of publication little has been published in the journal that fits that remit. In this short commentary I reflect on the nature of theory and explanation in geography and call for more sustained engagement with these themes in the pages of the journal in the years to come.

Due to the complexity and multidimensional characteristics of human activities, assessing the similarity of human activity patterns and classifying individuals with similar patterns remains highly challenging. This paper presents a new and unique methodology for evaluating the similarity among individual activity patterns. It conceptualizes multidimensional sequence alignment (MDSA) as a multiobjective

Social scientists characterize social life as a hierarchy of environments, from the micro level of an individual's knowledge and perceptions to the macro level of large-scale social networks. In accordance with this typology, individuals are typically thought to reside in micro- and macro-level structures, composed of multifaceted relations (e.g., acquaintanceship, friendship, and kinship). This article

Areal interpolation transforms data for a variable of interest from a set of source zones to estimate the same variable's distribution over a set of target zones. One common practice has been to guide interpolation by using ancillary control zones that are related to the variable of interest's spatial distribution. This guidance typically involves using source zone data to estimate the density of the

This article discusses options to allow comparative analysis of inequalities in the distribution of health workers (HWs) across and within countries using a single summary measure of the distribution. Income inequality generally is measured across individuals, but inequalities in the dispersion of HWs must use geographical areas or population groupings as units of analysis. The article first shows

In recent years, techniques have been developed to explore spatial non-stationarity and to model the entire distribution of a regressand. The former is mainly addressed by geographically weighted regression (GWR), and the latter by quantile regression (QR). However, little attention has been paid to combining these analytical techniques. The goal of this article is to fill this gap by introducing geographically

This article summarizes a spatial econometric analysis of local population and employment growth in the Netherlands, with specific reference to impacts of gender and space. The simultaneous equations model used distinguishes between population- and gender-specific employment groups, and includes autoregressive and cross-regressive spatial lags to detect relations both within and among these groups

One of the main tasks in analyzing pedestrian movement is to detect places where pedestrians stop, as those places usually are associated with specific human activities, and they can allow us to understand pedestrian movement behavior. Very few approaches have been proposed to detect the locations of stops in positioning data sets, and they often are based on selecting the location of candidate stops

The analysis of health data and putative covariates, such as environmental, socioeconomic, demographic, behavioral, or occupational factors, is a promising application for geostatistics. Transferring methods originally developed for the analysis of earth properties to health science, however, presents several methodological and technical challenges. These arise because health data are typically aggregated

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

Basic health system data such as the number of patients utilising different health facilities and the types of illness for which they are being treated are critical for managing service provision. These data requirements are generally addressed with some form of national Health Management Information System (HMIS) which coordinates the routine collection and compilation of data from national health

This paper presents a geostatistical methodology which accounts for spatially varying population size in the processing of cancer mortality data. The approach proceeds in two steps: (1) spatial patterns are first described and modeled using population-weighted semivariogram estimators, (2) spatial components corresponding to nested structures identified on semivariograms are then estimated and mapped

The Cox proportional hazard model is one of the most popular tools in analyzing time‐to‐event data in public health studies. When outcomes observed in clinical data from different regions yield a varying pattern correlated with location, it is often of great interest to investigate spatially varying effects of covariates. In this paper, we propose a geographically weighted Cox regression model for

Empirical applications of the Markov chain model and its spatial extensions suffer from issues induced by the sparse transition probability matrix, which usually results from adopting maximum likelihood estimators (MLEs). Two discrete kernel estimators with cross‐validated parameters are proposed for reducing the sparsity in the estimated transition probability matrix. Monte Carlo experiments suggest

The scientific method is predicated on the assumption that research designs and results can be reproduced and replicated. However, recent findings in some disciplines suggest that many studies fail to reach this standard, moving issues surrounding reproducibility and replicability forward into the research agenda of those fields. While the topic has yet to become a point of controversy in geography

Accessibility, measuring the ease of reaching potential destinations, is increasingly being considered as an effective indicator to evaluate the performance of transport and land use interactions. Primal accessibility, a generalization of the first accessibility formulation proposed by Hansen, has been widely used in many studies and demonstrated to be a reliable tool for project, program, and policy

A range of data is of geographic interest but is not available at a small area level from existing data sources. Small area estimation (SAE) offers techniques to estimate population parameters of target variables to detailed scales based on relationships between those target variables and relevant auxiliary variables. The resulting indirect small area estimate can deliver a lower mean squared error

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

The article analyzes area‐wide alcohol‐related driving crash rates, with an emphasis on neighborhood effects, edge effects, and spatial effects arising from shared roadways that traverse area boundaries. Using township data for the state of Indiana, spatial Durbin models of alcohol‐related driving crash rates are presented. The results suggest that a township's population composition and its abundance

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

We discuss a simple methodology to enable a statistical comparison of human population with the vegetation of North America over the past 13,000 years. Nonparametric kernel methods are applied for temporal and spatial smoothing of point data obtained from the Neotoma Paleoecology Database and the Canadian Archaeological Radiocarbon Database, which results in sequences of maps showing the development

This study examines issues of Small Area Estimation that are raised by reliance on the American Community Survey (ACS), which reports tract‐level data based on much smaller samples than the decennial census long‐form that it replaced. We demonstrate the problem using a 100% transcription of microdata from the 1940 census. By drawing many samples from two major cities, we confirm a known pattern: random

This article proposes a continuous approximation model for determining the number of hierarchical facilities when lower level facilities are subject to failures. The average distance from customers to the nearest open facility is derived for two types of customer behavior. The optimal number of facilities that minimizes the average distance is then obtained. The analytical expression for the optimal

To accommodate network allocation, population polygons are frequently transformed into singular, weighted centroids which are then integrated into the network either by snapping each centroid to the nearest network segment or by generating an artificial connector that becomes part of the network. In this article, an investigation of the connection method of network allocation is undertaken with two

This paper considers the past and future of the journal Geographical Analysis (GA), as well as the broader field of spatial analysis. From my experiences as a former editor of GA, I first identify three external trends that I feel will provide the backdrop for the future evolution of spatial analysis. These surround the rise of artificial intelligence, machine learning, and data science as disciplines

Movement is the driving force behind the form and function of many ecological and human systems. Identification and analysis of movement patterns that may relate to the behavior of individuals and their interactions is a fundamental first step in understanding these systems. With advances in IoT and the ubiquity of smart connected sensors to collect movement and contextual data, we now have access

The fiftieth anniversary of Geographical Analysis occurs for many quantitative human geographers at an exciting era of new and exciting sources of data and computational advancements. However, it also represents a crossroads where excitement to quickly capitalize upon these new data sources and methods risks reverting the discipline back to its abstraction‐rich and overly generalized roots, erasing

This paper investigates the effect of daily wind direction and speed on the spatio‐temporal distribution of particulate matter, . Interdependencies between the values of different monitoring sites are characterized by incorporating time‐varying anisotropic spatial weighting matrices. These weights are parameterized with respect to wind direction, speed and a range that marks the bandwidth of admissible

This article is concerned with the semantics associated with the statistical analysis of spatial data. It takes the simplest case of the prediction of variable y as a function of covariate(s) x, in which predicted y is always an approximation of y and only ever a function of x, thus, inheriting many of the spatial characteristics of x, and illustrates several core issues using “synthetic” remote sensing

Prompted by a series of panel sessions at a recent American Association of Geographers annual meeting entitled “A Globe‐Shaped Crystal Ball: The Next Fifty Years of Geographical Analysis,” participants were asked to speculate on the future of the journal, which of course has broader implications for spatial and geographic analytics. In what follows, I provide my thoughts on the journal as a reader

We develop a variant of the flow interception problem (FIP) in which it is more desirable for travelers to be intercepted as early as possible in their trips. In addition, we consider flows being intercepted probabilistically instead of the deterministic view of coverage assumed in the FIP literature. We call the proposed model the probabilistic minisum FIP (PMFIP); it involves minimizing the sum of

Technological progress has widely been acknowledged as a key driver in the achievement of environmental sustainability, and a new concern has recently arisen for assessing the role of differences in regional innovation performances with respect to the pursuit of pollution targets. We investigate the impact of innovative activities on environmental efficiency at the regional level, adopting a spatial

Despite the prevalence of polycentricity as a normative strategy in planning documents, a lengthy and inconclusive debate regarding its definition in academic research persists. The aim of this article is to eliminate the conceptual confusion surrounding functional polycentricity from a geographical perspective. By classifying different approaches to polycentricity, we outline the properties that characterize

Local analysis can provide specific information about individual observations that is often useful in understanding nonstationary interactions among variables. This paper extends the application of Wartenberg’s Multivariate Spatial Correlation (MSC) method to a local setting. The original MSC can be considered as an adaptation of Principal Component Analysis for spatial effects with respect to spatial

It is widely acknowledged that the emergence of “Big Data” is having a profound and often controversial impact on the production of knowledge. In this context, Data Science has developed as an interdisciplinary approach that turns such “Big Data” into information. This article argues for the positive role that Geography can have on Data Science when being applied to spatially explicit problems; and

Scholars frequently use counts of populations aggregated into geographic units like census tracts to represent measures of neighborhood context. Decades of research confirm that variation in how individuals are aggregated into geographic units can dramatically alter analyses conducted with these units. While most researchers are aware of the problem, they have lacked the tools to determine its magnitude

How urban characteristics change with total population, their scaling behavior, has become an important research field since one needs to better understand the challenges of urban densification. Yet urban scaling research is largely disconnected from intra‐urban structure, and this seriously limits its operationalization. In contrast, the monocentric model of Alonso provides a residential choice‐based

This paper expands upon a GA 50th Anniversary panel presentation made at the 2018 New Orleans American Association of Geographers meeting. It notes that retrospectives for this topic already exist, both in terms of the journal and the sub‐discipline. This paper presents discussion about the following selected prominent transitional themes bridging the past and the future of geographical analysis: space–time