Daniel A Griffith
Datos Biográficos
| ID | 1340696 |
|---|---|
| NOMBRE | Daniel A Griffith |
| NOMBRES | Daniel A |
| APELLIDO | Griffith |
| FIRMA | GRIFFITH D A |
| AFILIACIONES | The University of Texas at Dallas |
| ORCID | 0000-0001-5125-6450 |
| VERIFICADO | Sí |
| TOTAL DE OBRAS | 74 |
| TOTAL DE CITAS | 251 |
| TOTAL COMO AUTOR | 74 |
| TOTAL COMO EDITOR | 0 |
| PRIMER AÑO DE PUBLICACIÓN | 1975 |
| AÑO MÁS RECIENTE DE PUBLICACIÓN | 2026 |
| ÍNDICE H | 8 |
Spatial Autocorrelation Latent in Geographic Theory
This paper exposes the latent but potent role of seemingly hidden spatial autocorrelation (SA) in all geographic theories, highlighting that it is everywhere, matters, and is a fundamental property of geotagged phenomena. This narrative examines and extends the literature about the inescapable nature of the SA paradigm and the near-universal mixing of positive and negative SA. This study summary transcends the widespread but often implicit treatm…
Explicitly Studying Time in Historical Geography
Modern quantitative historical geography shoulders responsibility for cultivating and conserving knowledge about past geographies, in either their originating or interim context, or their impacts that percolate forward into the present and future. A defensible quantitative revolution recoil attributable to genuine numerical data setbacks, however, narrowed the scope of historical geography to work reinstating old, obscure, mysterious, incomplete …
Spatial Autocorrelation Is Everywhere—Even in Poetry
An Efficient Solution Approach for the p -Median Problems with Spatially Autocorrelated Weights
The p-median problem (PMP) is a classical location-allocation problem that involves simultaneously determining the locations of facilities and allocating demand points (nonfacilities) in a discrete space. The PMP is known to be NP-hard. Given its wide applicability, obtaining optimal solutions for large instances, particularly when multiple optimal solutions exist, remains computationally challenging. Nevertheless, there is a continuing and consi…
Emerging Trends and Issues in Geo-Spatial Environmental Health
This opinion piece postulates that quantitative environmental research and public health spatial analysts unknowingly tolerate certain spatial statistical model specification errors, whose remedies constitute some of the urgent emerging trends and issues in this subfield (e.g., forecasting disease spreading). Within this context, this paper addresses misspecifications affiliated with omitted variable bias complications arising from ignoring, and …
Delineations for Police Patrolling on Street Network Segments with p-Median Location Models
Police patrolling intends to enhance traffic safety by mitigating the risks associated with vehicle crashes and accidents. From a view of operations, patrolling requires an effective distribution of resources and often involves area delineations for this distribution purpose. Given constraints such as budget and human resources for traffic safety, delineating geographic areas optimally for police patrol areas is an important agenda item. This pap…
Spatial Autocorrelation and Political Redistricting
An important quantitative geography application area derives from the periodically repeating apportionment process of redrawing legislative district boundaries to guarantee equal voter representation through identical or equivalent population counts, a situation confronting the U.S. Supreme Court with gerrymandering rulings on a decennial basis. This remains a small geographic sample size domain, with states having between one and fifty-two (i.e.…
Sub‐Model Aggregation for Scalable Eigenvector Spatial Filtering
This study proposes a method for aggregating/synthesizing global and local sub‐models for fast and flexible spatial regression modeling. Eigenvector spatial filtering (ESF) was used to model spatially varying coefficients and spatial dependence in the residuals by sub‐model, while the generalized product‐of‐experts method was used to aggregate these sub‐models. The major advantages of the proposed method are as follows: (i) it is highly scalable …
Beyond Auto‐Models
This year is the 50th anniversary of Besag's classic auto‐models publication, a cornerstone in the development of modern‐day spatial statistics/econometrics. Besag struggled for nearly two decades to make his conceptualization collectively successful across a wide suite of random variables. But only his auto‐normal, and to a lesser degree his auto‐logistic/binomial, were workable. Others, like his auto‐Poisson, were effectively failures, whereas …
Graph Theory and Geography
Theoretical, methodological, and empirical contributions regarding networks within the context of graph theory constitute a valuable interface between geography and mathematics. Seeking to assess mathematical network geography’s past, present, and future, this article addresses such research and literature by discussing new knowledge produced from networked geographic phenomena—especially Erdös collaboration graphs depicting mentorships or author…
The Majority Theorem for the Single ( p = 1) Median Problem and Local Spatial Autocorrelation
Except for about a half dozen papers, virtually all (co)authored by Griffith, the existing literature lacks much content about the interface between spatial optimization, a popular form of geographic analysis, and spatial autocorrelation, a fundamental property of georeferenced data. The popular p ‐median location‐allocation problem highlights this situation: the empirical geographic distribution of demand virtually always exhibits positive spati…
Balancing Spatial and Non‐Spatial Variation in Varying Coefficient Modeling
This study discusses the importance of balancing spatial and non‐spatial variation in spatial regression modeling. Unlike spatially varying coefficients (SVC) modeling, which is popular in spatial statistics, non‐spatially varying coefficients (NVC) modeling has largely been unexplored in spatial fields. Nevertheless, as we will explain, consideration of non‐spatial variation is needed not only to improve model accuracy but also to reduce spuriou…
Art, Geography/GIScience, and Mathematics
Do any of the known synergies existing between either geography and art or mathematics and art bridge all three of these disciplines? The geo-humanities and the math-humanities literatures describe only these two individual synergies. A new quantitative geography methodology exploits a sophisticated mathematical concept to analyze remotely sensed satellite images, which, when extended to artistic paintings, indeed spans all three disciplines. The…
Interpreting Moran Eigenvector Maps with the Getis-Ord G i * Statistic
Spatial weights matrices used in quantitative geography furnish maps with their individual latent eigenvectors, whose geographic distributions portray distinct spatial autocorrelation (SA) components. These polygon patterns on maps have specific meaning, partially in terms of geographic scale, which this article describes. The goal of this description is to enable spatial analysts to better understand and interpret these maps individually, as wel…
Modeling Community Health with Areal Data
Epidemiologists and health geographers routinely use small-area survey estimates as covariates to model areal and even individual health outcomes. American Community Survey (ACS) estimates are accompanied by standard errors (SEs), but it is not yet standard practice to use them for evaluating or modeling data reliability. ACS SEs vary systematically across regions, neighborhoods, socioeconomic characteristics, and variables. Failure to consider p…
Soil Sample Assay Uncertainty and the Geographic Distribution of Contaminants
A research team collected 3609 useful soil samples across the city of Syracuse, NY; this data collection fieldwork occurred during the two consecutive summers (mid-May to mid-August) of 2003 and 2004. Each soil sample had fifteen heavy metals (As, Cr, Cu, Co, Fe, Hg, Mo, Mn, Ni, Pb, Rb, Se, Sr, Zn, and Zr), measured during its assaying; errors for these measurements are analyzed in this paper, with an objective of contributing to the geography of…
A Moran eigenvector spatial filtering specification of entropy measures
Temperature and assault in an urban environment
A Spatial Analysis of Selected Art
This exposition presents little-known connections between geography, through geographic information systems (GISs), mathematics, through matrix algebra, and art, through paintings and images, adding to the geo-humanities, spatial humanities, and humanistic mathematics literature. To this end, findings summarized for spatial statistical analyses of selected Susie Rosmarin paintings (which are reminiscent of visualizations of certain mathematical q…
Deeper Spatial Statistical Insights into Small Geographic Area Data Uncertainty
Small areas refer to small geographic areas, a more literal meaning of the phrase, as well as small domains (e.g., small sub-populations), a more figurative meaning of the phrase. With post-stratification, even with big data, either case can encounter the problem of small local sample sizes, which tend to inflate local uncertainty and undermine otherwise sound statistical analyses. This condition is the opposite of that afflicting statistical sig…
Space-time cluster detection with cross-space-time relative risk functions
Space-time kernel density estimation (STKDE) commonly is used for space-time cluster detection. But, this technique might be limited because it does not take into account an underlying population at risk for observed events. A space-time relative risk function (STRRF) can help overcome this limitation by allowing a comparison of each kernel density of observations with that of controls. This paper proposes a cross-STRRF to identify spatio-tempora…
The Importance of Scale in Spatially Varying Coefficient Modeling
Although spatially varying coefficient (SVC) models have attracted considerable attention in applied science, they have been criticized as being unstable. The objective of this study is to show that capturing the “spatial scale” of each data relationship is crucially important to make SVC modeling more stable and, in doing so, adds flexibility. Here, the analytical properties of six SVC models are summarized in terms of their characterization of …
Space-Time Statistical Insights about Geographic Variation in Lung Cancer Incidence Rates
The geographic distribution of lung cancer rates tends to vary across a geographic landscape, and covariates (e.g., smoking rates, demographic factors, socio-economic indicators) commonly are employed in spatial analysis to explain the spatial heterogeneity of these cancer rates. However, such cancer risk factors often are not available, and conventional statistical models are unable to fully capture hidden spatial effects in cancer rates. Introd…
Uncertainty and Context in Geography and GIScience
One of the conference themes for the 2017 American Association of Geographers (AAG) annual meeting was “Uncertainty and Context in Geography and GIScience.” It included a triplet of special sessions cosponsored by the Spatial Analysis and Modeling (SAM) and the Health & Medical Geography (HMG) specialty groups. One session dealt with spatial autocorrelation, another featured spatial sampling, and a third focused on public health data. A conceptua…
Measuring Spatial Dependence
Measuring spatial dependence is an essential process for diagnosing if conventional statistical approaches would produce proper results, and/or if spatial statistical methods need to be employed. It involves an operational framework in which spatial dependence is captured, numerical indices and their statistical properties that are used for a significance test, and graphics to visually portray spatial dependence. Because methods measuring spatial…
Do Spatial Effecfs Really Matter in Regression Analysis
Those gravity parameters again
Curry L., Griffith D. A. and Sheppard E. S. (1975) Those gravity parameters again, Reg. Studies 9, 289–296. The arguments presented in a recent paper by Cliff et al. (1974) as regards the relation between gravity parameters and map pattern are reassessed. First, the experimental simulation model designed to support their assertions is examined and found wanting in several fundamental aspects. Second, their statistical argument is evaluated, and i…
Modelling urban population density in a multi-centered city
A final comment on mis-specification and autocorrelation in those gravity parameters
(1976). A final comment on mis-specification and autocorrelation in those gravity parameters. Regional Studies: Vol. 10, No. 3, pp. 337-339
Spatial-Filtering-Based Contributions to a Critique of Geographically Weighted Regression (GWR)
Interaction terms are constructed with georeferenced attribute variables and spatial filter eigenvectors, and then used to compute geographically varying regression coefficients. These coefficients, which are analogous to geographically weighted regression (GWR) coefficients, display preferable properties, and this specification is used to critique selected features of GWR. Comparisons are illustrated with the Georgia data appearing in the standa…
Explorations into the Relationship between Spatial Structure and Spatial Interaction
This paper explores the relationship between spatial structure and spatial interaction at the intraurban level. To examine this relationship an experimental framework is designed based on the application of a doubly constrained entropy-type gravity model to journey-to-work data for twenty-four Canadian urban areas. The study demonstrates that distance-decay exponents are strongly influenced by geographic structure and the geometry of origins and …
Semiparametric Filtering of Spatial Autocorrelation
In the context of spatial regression analysis, several methods can be used to control for the statistical effects of spatial dependencies among observations. Maximum likelihood or Bayesian approaches account for spatial dependencies in a parametric framework, whereas recent spatial filtering approaches focus on nonparametrically removing spatial autocorrelation. In this paper we propose a semiparametric spatial filtering approach that allows rese…
A Variance-Stabilizing Coding Scheme for Spatial Link Matrices
In spatial statistics and spatial econometrics two coding schemes are used predominately. Except for some initial work, the properties of both coding schemes have not been investigated systematically. In this paper we do so for significant spatial processes specified as either a simulta-neous autoregressive or a moving average process. Results show that the C-coding scheme emphasizes spatial objects with relatively large numbers of connections, s…
Modeling Network Autocorrelation in Space–Time Migration Flow Data
Gravity-type spatial interaction models have been popularly utilized in modeling cross-sectional migration data, but their misspecification also has been raised in the literature. This misspecification issue principally concerns an insufficient accounting of underlying effects of spatial structure, including the presence of network autocorrelation among migration flows. Recent studies reveal that spatial interaction models are significantly impro…
Spatial Autocorrelation and Eigenfunctions of the Geographic Weights Matrix Accompanying Geo‐referenced Data
Gaining a better understanding of spatial data and a deeper meaning of spatial statistical results gleaned from geo‐referenced data requires a more complete knowledge of properties of the underlying geometry. This paper addresses these two topics by further investigating important geometric features of spatial data. The importance of this work is expressed in the geographic information system literature regarding representations of geographic spa…
A Tale of Two Swaths
A growing body of research documents various prominent and important geographic dimensions to pediatric lead poisoning. This paper uses the Onondaga County Health Department database for 1992–1995 and the 1990 Census of Population and Housing data to analyze the spatial distribution of blood-lead levels in Syracuse, New York. Analyses are conducted at the individual, census block, census block group, and census tract resolutions. Regardless of ge…
The Problem of Missing Data on Spatial Surfaces
Although the problem of missing data arises in most branches of the discipline, it has received little systematic treatment in the geographical literature. In an effort to overcome this deficiency, this paper reviews a number of methods for approaching the problem. Of the three classes of solutions—ad hoc, cartographic interpolation, and statistical—the statistical approaches appear to be preferable. In this review a modified version of the Orcha…
The Importance of Scale in Spatially Varying Coefficient Modeling
Although spatially varying coefficient (SVC) models have attracted considerable attention in applied science, they have been criticized as being unstable. The objective of this study is to show that capturing the “spatial scale” of each data relationship is crucially important to make SVC modeling more stable and, in doing so, adds flexibility. Here, the analytical properties of six SVC models are summarized in terms of their characterization of …
Effective Geographic Sample Size in the Presence of Spatial Autocorrelation
As spatial autocorrelation latent in georeferenced data increases, the amount of duplicate information contained in these data also increases. This property suggests the research question asking what the number of independent observations, say , is that is equivalent to the sample size, n, of a data set. This is the notion of effective sample size. Intuitively speaking, when zero spatial autocorrelation prevails, ; when perfect positive spatial a…
Metropolis
Geometry and Spatial Interaction
This paper explores the relations between regional shape geometry and internal regional geometry affiliated with spatial interaction. Because properties of these two geometries are difficult to measure, various indices are calculated. Using the canonical correlation technique, the study then analyzes the relationship between these two geometries. This yields two interesting findings: (1) that a relationship does exist between the two types of geo…
A Spatial Filtering Specification for the Autologistic Model
The autologistic model describes binary correlated data; its spatial version describes georeferenced binary data exhibiting spatial dependence. The conventional specification of a spatial autologistic model involves difficult-to-nearly-impossible computations to ensure that appropriate sets of probabilities sum to 1. Work summarized here accounts for spatial autocorrelation by including latent map pattern components as covariates in a model speci…
Urban Dominance, Spatial Structure, and Spatial Dynamics
Three dimensions of urban systems are investigated in this paper. The first is urban dominance, which refers to the network of influences certain urban places maintain within a system of cities. The second is interurban spatial structure, which refers to the pattern of links existing in a network of urban dominance, together with the nature and degree of those influences pulsating along these links. And, the third is spatial dynamics, which refer…
Error Propagation Modeling in Raster GIS
The purpose of this paper is to identify error properties arising when source maps that individually contain error are added or when the ratio of one map with respect to another is computed. The research approach to the problem combines mathematical analysis and simulation where source maps and error processes have been constructed with specified properties. Geman and Geman's corruption model is used to represent error in individual source maps. …
Spatial Econometrics
Using Spatial Autocorrelation Analysis to Guide Mixed Methods Survey Sample Design Decisions
Mixed methods researchers share a commitment to knowing their sampling frames and minimizing discovery failure, especially when using surveys. Notwithstanding advances in sampling strategies, the geographic clustering of perceptions has not been fully considered for its relevance to sampling. This article examines the value of spatial autocorrelation analysis to guide sampling decisions. Spatial autocorrelation refers to the clustering of (dis)si…
Establishing Qualitative Geographic Sample Size in the Presence of Spatial Autocorrelation
Sample size is a crucial feature of all research projects, especially affecting generalizability and manipulation or control in quantitative studies and transferability and discovery in qualitative studies. Selecting a minimum number of observations helps ensure the adequacy of a sampling strategy. In general, sample sizes for quantitative studies tend to be relatively large, whereas those for qualitative studies tend to be relatively small, high…
Statistical Analysis of Spatial Data in the Presence of Missing Observations
In this paper a simple introduction and guide to a widely applicable method for estimating missing data in fields of enquiry such as census maps or LANDSAT images are presented. The method given is a maximum likelihood procedure. This is argued to have the particularly favourable characteristics (1) that its distribution properties are known, (2) it is applicable both to regularly and to irregularly spaced observations, (3) it can handle differen…
Dynamic Characteristics of Spatial Economic Systems
The space-time path of the Manitoba grain handling system is explored in order to identify behavioral characteristics of a multi-locational economic activity undergoing spatial consolidation. Descriptive hypotheses regarding spatial trends as well as temporal trends are formulated and then tested. The Manitoba data set used in this testing consists of 388 locations and 32 time periods. Findings include: (a) closures occur in a quasi-concentric fa…
Art, Geography/GIScience, and Mathematics
Do any of the known synergies existing between either geography and art or mathematics and art bridge all three of these disciplines? The geo-humanities and the math-humanities literatures describe only these two individual synergies. A new quantitative geography methodology exploits a sophisticated mathematical concept to analyze remotely sensed satellite images, which, when extended to artistic paintings, indeed spans all three disciplines. The…
Those gravity parameters again
Curry L., Griffith D. A. and Sheppard E. S. (1975) Those gravity parameters again, Reg. Studies 9, 289–296. The arguments presented in a recent paper by Cliff et al. (1974) as regards the relation between gravity parameters and map pattern are reassessed. First, the experimental simulation model designed to support their assertions is examined and found wanting in several fundamental aspects. Second, their statistical argument is evaluated, and i…
Spatial Structure and Spatial Interaction
This paper is a review of the literature of that area of spatial interaction which attempts to accommodate the affects of spatial structure. A brief history of this problem is presented, together with criticisms of suggested alternative solutions. Next, spatial interaction in a Christaller K = 3 hierarchy is outlined and its principal components evaluated. Finally, some tentative conclusions as well as several areas for subsequent research are me…
A final comment on mis-specification and autocorrelation in those gravity parameters
(1976). A final comment on mis-specification and autocorrelation in those gravity parameters. Regional Studies: Vol. 10, No. 3, pp. 337-339
Urban Dominance, Spatial Structure, and Spatial Dynamics
Three dimensions of urban systems are investigated in this paper. The first is urban dominance, which refers to the network of influences certain urban places maintain within a system of cities. The second is interurban spatial structure, which refers to the pattern of links existing in a network of urban dominance, together with the nature and degree of those influences pulsating along these links. And, the third is spatial dynamics, which refer…
Explorations into the Relationship between Spatial Structure and Spatial Interaction
This paper explores the relationship between spatial structure and spatial interaction at the intraurban level. To examine this relationship an experimental framework is designed based on the application of a doubly constrained entropy-type gravity model to journey-to-work data for twenty-four Canadian urban areas. The study demonstrates that distance-decay exponents are strongly influenced by geographic structure and the geometry of origins and …
Modelling urban population density in a multi-centered city
Geometry and Spatial Interaction
This paper explores the relations between regional shape geometry and internal regional geometry affiliated with spatial interaction. Because properties of these two geometries are difficult to measure, various indices are calculated. Using the canonical correlation technique, the study then analyzes the relationship between these two geometries. This yields two interesting findings: (1) that a relationship does exist between the two types of geo…
Dynamic Characteristics of Spatial Economic Systems
The space-time path of the Manitoba grain handling system is explored in order to identify behavioral characteristics of a multi-locational economic activity undergoing spatial consolidation. Descriptive hypotheses regarding spatial trends as well as temporal trends are formulated and then tested. The Manitoba data set used in this testing consists of 388 locations and 32 time periods. Findings include: (a) closures occur in a quasi-concentric fa…
Reexamining the Question ‘are Locations Unique?’
The Problem of Missing Data on Spatial Surfaces
Although the problem of missing data arises in most branches of the discipline, it has received little systematic treatment in the geographical literature. In an effort to overcome this deficiency, this paper reviews a number of methods for approaching the problem. Of the three classes of solutions—ad hoc, cartographic interpolation, and statistical—the statistical approaches appear to be preferable. In this review a modified version of the Orcha…
Evolving Geographic Structures
Central Place Structures Using Constant Elasticity of Substitution Demand Cones
Historically the problem of negative demand has been encountered in constructing spatial demand cones due to the use of linear demand functions. One solution to this problem is explored in this pap
Teaching spatial autocorrelation by simulation
A computer simulation game to help teach spatial autocorrelation is presented. Its use assumes that students have a minimal background in introductory statistics and its focus is on efficiently and effectively searching through a sampling distribution, seeking map patterns with particular levels of spatial autocorrelation. The sampling distribution is constructed using randomisation, and the search process is guided by calculations of Geary's con…
Do Spatial Effecfs Really Matter in Regression Analysis
Geographical Systems and Systems of Geography
Spatial Autocorrelation
Spatial Econometrics
Advanced Spatial Statistics
Metropolis
Statistical Analysis of Spatial Data in the Presence of Missing Observations
In this paper a simple introduction and guide to a widely applicable method for estimating missing data in fields of enquiry such as census maps or LANDSAT images are presented. The method given is a maximum likelihood procedure. This is argued to have the particularly favourable characteristics (1) that its distribution properties are known, (2) it is applicable both to regularly and to irregularly spaced observations, (3) it can handle differen…
Simplifying the Normalizing Factor in Spatial Autoregressions for Irregular Lattices
Simplifying the normalizing factor in spatial autoregressions for irregular lattices
Teaching spatial statistics to geographers using Minitab
This paper surveys computer software for spatial statistics, emphasising its educational advantages. Initially this software was written in FORTRAN code accessing the International Mathematical and Statistics Library (IMSL) package of commercial subroutines (a counterpart to the NAG package in the United Kingdom). Accompanying programming skills proved too demanding for many geography students and staff. Consequently, spatial statistics analysis …
Exploring relationships between semi-variogram and spatial autoregressive models
Exploring Relationships Between Semi‐variogram and Spatial Autoregressive Models
Geography (48 obras) · Mathematics (44 obras) · Computer Science (43 obras) · Spatial and Panel Data Analysis (42 obras) · Statistics (36 obras) · Spatial analysis (31 obras) · Econometrics (28 obras) · Autocorrelation (16 obras) · Cartography (16 obras) · Regional Economics and Spatial Analysis (15 obras)