Levi John Wolf
Biographic Data
| ID | 3584431 |
|---|---|
| NAME | Levi John Wolf |
| GIVEN NAMES | Levi John |
| FAMILY NAME | Wolf |
| SIGNATURE | WOLF L J |
| AFFILIATIONS | University of Bristol |
| ORCID | 0000-0003-0274-599X |
| VERIFIED | Yes |
| TOTAL WORKS | 31 |
| TOTAL CITATIONS | 34 |
| AUTHOR COUNT | 31 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2015 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 3 |
Mapping the long-term trajectories of political violence in Africa
Not so ‘placeless’ after all. Understanding the spatial implications of the digital economy
Empirical studies on the geography of digital economic activities are currently lacking. This is due to digital economic activities remaining largely undefined in official economic statistics. This paper introduces a novel empirical pipeline to examine the spatial characteristics of the digital economy while addressing the challenges of data missingness. Firstly, we identify digital economic activities by using commercial websites and Natural Lan…
Measuring urbanity
Fast and furious
The link between digital technologies and productivity has long intrigued researchers. Key to unpacking this relationship is detailed data connecting internet usage, economic outputs, and places. Using a multilevel modelling framework, we combine firm-level microdata with unique internet speed microdata that reflect end-user experiences, distinguishing upload and download speeds. This approach approximates business internet usage and reveals that…
Beyond open science
EPB turns 50 years old
The history of Environment and Planning B (EPB) over the last 50 years has been described in detail by Batty (2024, this issue) while different eras and topics have been highlighted within the invited commentaries that comprise this 50th anniversary special issue.Harris (2024, this issue), in particular, discusses the recent change in the latter part of the journal's name from Planning and Design to Urban Analytics and City Science.This reflects …
Hopes and dreams for (future) better things
but even more so in the last few years.Of course, the traditional research article is still, and will probably be for a while, our bread and butter.But this is no
Rethinking 'causality' in quantitative human geography
Causality is at the core of much contemporary discussion in social sciences, philosophy, and computer science-from the establishment of basic definitions of causality to developing methods for causal inference, this discussion is increasingly finding voice within geographical literature. However, geographers have long discussed (and differed) about the role "causality" plays in our work. We present a history of contemporary definitions of causali…
Confounded Local Inference
Local statistical analysis has long been of interest to social and environmental scientists who analyze geographic data. Research into local spatial statistics experienced a step-change in the mid-1990s, which provided a large class of local statistical methods and models. The local Moran statistic is one commonly used local indicator of spatial association, able to detect both areas of similarity and observations that are very dissimilar from th…
The Right to Rule by Thumb
Comber et al. provide an important contribution to the future of quantitative geography and Geographical Analysis . The contribution is chiefly in their development of a “GWR Route Map,” a diagram showing the sequence of analytical steps that “successful” specification searches in local modeling tend to follow. Geographically weighted techniques have been rapidly expanding, both in terms of complexity, users, and disciplinary reach. With geograph…
Beyond open science
A spatial-demographic analysis of Africa’s emerging urban geography
We examine Africa’s emerging urban geography from a demographic perspective and discuss implications for development policy. We adopt an approach that defines urbanisation purely in spatial-demographic terms in recognition of the decoupling of urbanization (as a spatial-demographic process) from economic development in Africa. Our analysis uses the most up-to-date gridded population data (WorldPop) to analyse diverse patterns of “urban” settlemen…
The Importance of Null Hypotheses
A recent review noted important differences in the results of the local Moran's statistic depending on the inference method. These differences had significant practical implications. In closing, the authors speculated the differences may be due to local spatial heterogeneity. In this article, we propose that different null hypotheses, not heteroskedasticity, generate these differences. To test this, we examine the null hypotheses implicit in comm…
The PySAL Ecosystem
PySAL is a library for geocomputation and spatial data science. Written in Python, the library has a long history of supporting novel scholarship and broadening methodological impacts far afield of academic work. Recently, many new techniques, methods of analyses, and development modes have been implemented, making the library much larger and more encompassing than that previously discussed in the literature. As such, we provide an introduction t…
Urban data/code
Geosilhouettes
Regionalization, under various guises and descriptions, is a longstanding and pervasive interest of urban studies. With an increasingly large number of studies on urban place detection in language, behavior, pricing, and demography, recent critiques of longstanding regional science perspectives on place detection have focused on the arbitrariness and non-geographical nature of measures of best fit. In this paper, we develop new explicitly geograp…
Scale, Context, and Heterogeneity
This article attempts to identify and separate the role of spatial “context” in shaping voter preferences from the role of other socioeconomic determinants. It does this by calibrating a multiscale geographically weighted regression (MGWR) model of county-level data on percentages voting for the Democratic Party in the 2016 U.S. presidential election. This model yields information on both the spatially heterogeneous nature of the determinants of …
On Spatial and Platial Dependence
Multilevel models have been applied to study many geographical processes in epidemiology, economics, political science, sociology, urban analytics, and transportation. They are most often used to express how the effect of a treatment or intervention might vary by geographical group, a form of spatial process heterogeneity. In addition, these models provide a notion of “platial” dependence: observations that are within the same geographical place …
Inference in Multiscale Geographically Weighted Regression
A recent paper expands the well‐known geographically weighted regression (GWR) framework significantly by allowing the bandwidth or smoothing factor in GWR to be derived separately for each covariate in the model—a framework referred to as multiscale GWR (MGWR). However, one limitation of the MGWR framework is that, until now, no inference about the local parameter estimates was possible. Formally, the so‐called “hat matrix,” which projects the o…
Sensitivity of sequence methods in the study of neighborhood change in the United States
Chris Brunsdon and Lex Comber, An introduction to R for spatial analysis and mapping (second edition)
Quantitative geography III
In the previous two reports in this series, we discussed the history and current status of quantitative geography. In this final report, we focus on the future. We argue that quantitative geographers are most helpful when we can simplify difficult problems using our distinct domain expertise. To do this, we must clarify the theory underpinning core conceptual problems in quantitative geography. Then, we examine the social forces that are shaping …
Measuring Bandwidth Uncertainty in Multiscale Geographically Weighted Regression Using Akaike Weights
Bandwidth, a key parameter in geographically weighted regression models, is closely related to the spatial scale at which the underlying spatially heterogeneous processes being examined take place. Generally, a single optimal bandwidth (geographically weighted regression) or a set of covariate-specific optimal bandwidths (multiscale geographically weighted regression) is chosen based on some criterion, such as the Akaike information criterion (AI…
MGWR
Geographically weighted regression (GWR) is a spatial statistical technique that recognizes that traditional ‘global’ regression models may be limited when spatial processes vary with spatial context. GWR captures process spatial heterogeneity by allowing effects to vary over space. To do this, GWR calibrates an ensemble of local linear models at any number of locations using ‘borrowed’ nearby data. This provides a surface of location-specific pa…
A roundtable discussion
The field of urban analytics and city science has seen significant growth and development in the past 20 years. The rise of data science, both in industry and academia, has put new pressures on urban research, but has also allowed for new analytical possibilities. Because of the rapid growth and change in the field, terminology in urban analytics can be vague and unclear. This paper, an abridged synthesis of a panel discussion among scholars in U…
Scale, Context, and Heterogeneity
This article attempts to identify and separate the role of spatial “context” in shaping voter preferences from the role of other socioeconomic determinants. It does this by calibrating a multiscale geographically weighted regression (MGWR) model of county-level data on percentages voting for the Democratic Party in the 2016 U.S. presidential election. This model yields information on both the spatially heterogeneous nature of the determinants of …
Measuring Bandwidth Uncertainty in Multiscale Geographically Weighted Regression Using Akaike Weights
Bandwidth, a key parameter in geographically weighted regression models, is closely related to the spatial scale at which the underlying spatially heterogeneous processes being examined take place. Generally, a single optimal bandwidth (geographically weighted regression) or a set of covariate-specific optimal bandwidths (multiscale geographically weighted regression) is chosen based on some criterion, such as the Akaike information criterion (AI…
Quantitative methods I
Although pioneering studies using statistical methods in geographical data analysis were published in the 1930s, it was only in the 1960s that their increasing use in human geography led to a claim that a ‘quantitative revolution’ had taken place. The widespread use of quantitative methods from then on was associated with changes in both disciplinary philosophy and substantive focus. The first decades of the ‘revolution’ saw quantitative analyses…
Confounded Local Inference
Local statistical analysis has long been of interest to social and environmental scientists who analyze geographic data. Research into local spatial statistics experienced a step-change in the mid-1990s, which provided a large class of local statistical methods and models. The local Moran statistic is one commonly used local indicator of spatial association, able to detect both areas of similarity and observations that are very dissimilar from th…
On Spatial and Platial Dependence
Multilevel models have been applied to study many geographical processes in epidemiology, economics, political science, sociology, urban analytics, and transportation. They are most often used to express how the effect of a treatment or intervention might vary by geographical group, a form of spatial process heterogeneity. In addition, these models provide a notion of “platial” dependence: observations that are within the same geographical place …
Quantitative geography III
In the previous two reports in this series, we discussed the history and current status of quantitative geography. In this final report, we focus on the future. We argue that quantitative geographers are most helpful when we can simplify difficult problems using our distinct domain expertise. To do this, we must clarify the theory underpinning core conceptual problems in quantitative geography. Then, we examine the social forces that are shaping …
A Spatiotemporal Compactness Pattern Analysis of Congressional Districts to Assess Partisan Gerrymandering
Compactness of a congressional district is a traditional principle in adjudicating gerrymandering claims in political redistricting. During the last decade, many states have used compactness as an important criterion to constrain the presence of gerrymandering in the redistricting process. In this study, we conducted an array of spatiotemporal analyses aiming to evaluate the changes in compactness between the 112th and 113th Congressional distric…
Rethinking 'causality' in quantitative human geography
Causality is at the core of much contemporary discussion in social sciences, philosophy, and computer science-from the establishment of basic definitions of causality to developing methods for causal inference, this discussion is increasingly finding voice within geographical literature. However, geographers have long discussed (and differed) about the role "causality" plays in our work. We present a history of contemporary definitions of causali…
Quantitative methods II
The first of these three reports reprised human geography’s theoretical and quantitative revolutions’ origins, covering the philosophy, focus and methods that dominated their early years. Over the subsequent decades the nature of work categorised as quantitative human geography changed very considerably – in philosophy, focus and methods. This second report summarises those changes, highlighting the main features of the extensive volume of work p…
A spatial-demographic analysis of Africa’s emerging urban geography
We examine Africa’s emerging urban geography from a demographic perspective and discuss implications for development policy. We adopt an approach that defines urbanisation purely in spatial-demographic terms in recognition of the decoupling of urbanization (as a spatial-demographic process) from economic development in Africa. Our analysis uses the most up-to-date gridded population data (WorldPop) to analyse diverse patterns of “urban” settlemen…
A Spatiotemporal Compactness Pattern Analysis of Congressional Districts to Assess Partisan Gerrymandering
Compactness of a congressional district is a traditional principle in adjudicating gerrymandering claims in political redistricting. During the last decade, many states have used compactness as an important criterion to constrain the presence of gerrymandering in the redistricting process. In this study, we conducted an array of spatiotemporal analyses aiming to evaluate the changes in compactness between the 112th and 113th Congressional distric…
Spatial Analysis
Spatial analysis has long been central to solving geographical problems. Broadly speaking, the goal of spatial analysis is to understand, express, and exploit order, pattern and/or structure inherent in geographically distributed phenomena. Formal techniques, relying on geographic information science, statistics, mathematics, and computation, forge a link between geographic data and useful knowledge, and therefore are utilized as part of spatial …
Bradley Efron and Trevor Hastie, Computer age statistical inference
Regional inequality dynamics, stochastic dominance, and spatial dependence
Quantitative methods I
Although pioneering studies using statistical methods in geographical data analysis were published in the 1930s, it was only in the 1960s that their increasing use in human geography led to a claim that a ‘quantitative revolution’ had taken place. The widespread use of quantitative methods from then on was associated with changes in both disciplinary philosophy and substantive focus. The first decades of the ‘revolution’ saw quantitative analyses…
MGWR
Geographically weighted regression (GWR) is a spatial statistical technique that recognizes that traditional ‘global’ regression models may be limited when spatial processes vary with spatial context. GWR captures process spatial heterogeneity by allowing effects to vary over space. To do this, GWR calibrates an ensemble of local linear models at any number of locations using ‘borrowed’ nearby data. This provides a surface of location-specific pa…
A roundtable discussion
The field of urban analytics and city science has seen significant growth and development in the past 20 years. The rise of data science, both in industry and academia, has put new pressures on urban research, but has also allowed for new analytical possibilities. Because of the rapid growth and change in the field, terminology in urban analytics can be vague and unclear. This paper, an abridged synthesis of a panel discussion among scholars in U…
Quantitative methods II
The first of these three reports reprised human geography’s theoretical and quantitative revolutions’ origins, covering the philosophy, focus and methods that dominated their early years. Over the subsequent decades the nature of work categorised as quantitative human geography changed very considerably – in philosophy, focus and methods. This second report summarises those changes, highlighting the main features of the extensive volume of work p…
Inference in Multiscale Geographically Weighted Regression
A recent paper expands the well‐known geographically weighted regression (GWR) framework significantly by allowing the bandwidth or smoothing factor in GWR to be derived separately for each covariate in the model—a framework referred to as multiscale GWR (MGWR). However, one limitation of the MGWR framework is that, until now, no inference about the local parameter estimates was possible. Formally, the so‐called “hat matrix,” which projects the o…
Sensitivity of sequence methods in the study of neighborhood change in the United States
Chris Brunsdon and Lex Comber, An introduction to R for spatial analysis and mapping (second edition)
Quantitative geography III
In the previous two reports in this series, we discussed the history and current status of quantitative geography. In this final report, we focus on the future. We argue that quantitative geographers are most helpful when we can simplify difficult problems using our distinct domain expertise. To do this, we must clarify the theory underpinning core conceptual problems in quantitative geography. Then, we examine the social forces that are shaping …
Measuring Bandwidth Uncertainty in Multiscale Geographically Weighted Regression Using Akaike Weights
Bandwidth, a key parameter in geographically weighted regression models, is closely related to the spatial scale at which the underlying spatially heterogeneous processes being examined take place. Generally, a single optimal bandwidth (geographically weighted regression) or a set of covariate-specific optimal bandwidths (multiscale geographically weighted regression) is chosen based on some criterion, such as the Akaike information criterion (AI…
Urban data/code
Geosilhouettes
Regionalization, under various guises and descriptions, is a longstanding and pervasive interest of urban studies. With an increasingly large number of studies on urban place detection in language, behavior, pricing, and demography, recent critiques of longstanding regional science perspectives on place detection have focused on the arbitrariness and non-geographical nature of measures of best fit. In this paper, we develop new explicitly geograp…
Scale, Context, and Heterogeneity
This article attempts to identify and separate the role of spatial “context” in shaping voter preferences from the role of other socioeconomic determinants. It does this by calibrating a multiscale geographically weighted regression (MGWR) model of county-level data on percentages voting for the Democratic Party in the 2016 U.S. presidential election. This model yields information on both the spatially heterogeneous nature of the determinants of …
On Spatial and Platial Dependence
Multilevel models have been applied to study many geographical processes in epidemiology, economics, political science, sociology, urban analytics, and transportation. They are most often used to express how the effect of a treatment or intervention might vary by geographical group, a form of spatial process heterogeneity. In addition, these models provide a notion of “platial” dependence: observations that are within the same geographical place …
The Importance of Null Hypotheses
A recent review noted important differences in the results of the local Moran's statistic depending on the inference method. These differences had significant practical implications. In closing, the authors speculated the differences may be due to local spatial heterogeneity. In this article, we propose that different null hypotheses, not heteroskedasticity, generate these differences. To test this, we examine the null hypotheses implicit in comm…
The PySAL Ecosystem
PySAL is a library for geocomputation and spatial data science. Written in Python, the library has a long history of supporting novel scholarship and broadening methodological impacts far afield of academic work. Recently, many new techniques, methods of analyses, and development modes have been implemented, making the library much larger and more encompassing than that previously discussed in the literature. As such, we provide an introduction t…
The Right to Rule by Thumb
Comber et al. provide an important contribution to the future of quantitative geography and Geographical Analysis . The contribution is chiefly in their development of a “GWR Route Map,” a diagram showing the sequence of analytical steps that “successful” specification searches in local modeling tend to follow. Geographically weighted techniques have been rapidly expanding, both in terms of complexity, users, and disciplinary reach. With geograph…
Beyond open science
A spatial-demographic analysis of Africa’s emerging urban geography
We examine Africa’s emerging urban geography from a demographic perspective and discuss implications for development policy. We adopt an approach that defines urbanisation purely in spatial-demographic terms in recognition of the decoupling of urbanization (as a spatial-demographic process) from economic development in Africa. Our analysis uses the most up-to-date gridded population data (WorldPop) to analyse diverse patterns of “urban” settlemen…
Beyond open science
EPB turns 50 years old
The history of Environment and Planning B (EPB) over the last 50 years has been described in detail by Batty (2024, this issue) while different eras and topics have been highlighted within the invited commentaries that comprise this 50th anniversary special issue.Harris (2024, this issue), in particular, discusses the recent change in the latter part of the journal's name from Planning and Design to Urban Analytics and City Science.This reflects …
Hopes and dreams for (future) better things
but even more so in the last few years.Of course, the traditional research article is still, and will probably be for a while, our bread and butter.But this is no
Computer Science (20 works) · Geography (15 works) · Mathematics (15 works) · Spatial and Panel Data Analysis (15 works) · Data science (9 works) · Econometrics (9 works) · Statistics (9 works) · Human Mobility and Location-Based Analysis (7 works) · Urban, Neighborhood, and Segregation Studies (7 works) · Data-Driven Disease Surveillance (6 works)