C Brunsdon

Biographic Data

ID19844
NAMEC Brunsdon
GIVEN NAMESC
FAMILY NAMEBrunsdon
SIGNATUREBRUNSDON C
AFFILIATIONSNational University of Ireland, Maynooth
ORCID0000-0003-4254-1780
VERIFIEDYes
TOTAL WORKS46
TOTAL CITATIONS180
AUTHOR COUNT46
EDITOR COUNT0
FIRST PUBLICATION YEAR1981
LATEST PUBLICATION YEAR2026
H-INDEX7

  • Coarse‐to‐Fine Spatial Modeling

    Open AccessDaisuke Murakami, Alexis Comber et al.ARTICLEGeographical Analysis2026

    This study proposes coarse‐to‐fine spatial modeling (CFSM) as a scalable and machine learning‐compatible alternative to conventional spatial process models. Unlike conventional covariance‐based spatial models, CFSM represents spatial processes using a multiscale ensemble of local models. To ensure stable model training, larger‐scale patterns that are easier to learn are modeled first, followed by smaller‐scale patterns, with training terminated o…

  • Missing Data Can Be a Geographic Phenomenon

    Open AccessDominick Sutton, Anahid Basiri et al.ARTICLEAnnals of the American…2026

    Missing data is a problem across all types of analysis, with survey nonresponses just one example of a universal problem. This is particularly the case with survey questions on sensitive topics, such as ethnicity or income, as these are often not answered. This can introduce bias into the data and present a challenge to analysts, particularly as they can lead to incorrect conclusions and policy recommendations. Accordingly, methods have been deve…

  • New Weighting System for the Ordered Weighted Average Operator and Its Application in the Balanced Expansion of Urban Infrastructures

    Open AccessMatheus Pereira Libório, Petr Ekel et al.ARTICLEUrban Science2025References: 7

    Urban infrastructure, such as water supply networks, sewage systems, and electricity networks, is essential for the functioning of cities and, consequently, for the well-being of citizens. Despite its essentiality, the distribution of infrastructure in urban areas is not homogeneous, especially in cities in developing countries. Socially vulnerable areas often face significant deficiencies in sewage and road paving, exacerbating urban inequalitie…

  • Encapsulating Spatially Varying Relationships with a Generalized Additive Model

    Open AccessAlexis Comber, Paul Harris et al.ARTICLEISPRS International Journal of…2024

    This paper describes the use of Generalized Additive Models (GAMs) to create regression models whose coefficient estimates vary with geographic location—spatially varying coefficient (SVC) models. The approach uses Gaussian Process (GP) splines (smooths) for each predictor variable, which are parameterised with observation location in order to generate SVC estimates. These describe the spatially varying relationships between predictor and respons…

  • Harnessing Spatial Heterogeneity in Composite Indicators through the Ordered Geographically Weighted Averaging ( Ogwa ) Operator

    Open AccessElisa Fusco, Matheus Pereira Libório et al.ARTICLEGeographical Analysis2024

    Spatially heterogeneous weights and a non‐compensatory aggregation scheme, are two important properties needed to construct a composite indicator capable of summarizing properly the multidimensional phenomenon of local spatial units. Such a composite indicator takes into account, on the one hand, the latent characteristics of the specific units related to their location in the territory, and on the other hand, the relative importance of sub‐indic…

  • Ordered weighted averaging for the evaluation of urban inequality in sao Sebastião Do Paraíso

    Open AccessMatheus Pereira Libório, Hamidreza Rabiei-Dastjerdi et al.ARTICLECities2024Cited by: 1References: 51

  • A Route Map for Successful Applications of Geographically Weighted Regression

    Open AccessAlexis Comber, C Brunsdon et al.ARTICLEGeographical Analysis2023

    Geographically Weighted Regression (GWR) is increasingly used in spatial analyses of social and environmental data. It allows spatial heterogeneities in processes and relationships to be investigated through a series of local regression models rather than a single global one. Standard GWR assumes that relationships between the response and predictor variables operate at the same spatial scale, which is frequently not the case. To address this, se…

  • A Rejoinder to the Commentaries on “A Route Map for Successful Applications of Geographically Weighted Regression” by Comber et al. (2022)

    Open AccessAlexis Comber, Paul Harris et al.ARTICLEGeographical Analysis2023

    In brief, the GWR Route Map (RM) by Comber et al. (2022a) argues that an ordinary least squares (OLSs) regression and a multiscale GWR should always be undertaken initially. Then, by examining the outputs and results of these, the final choice of model can be determined by applying some very broad rubrics. We wrote the RM for two main reasons. First, we have witnessed the increased use of GWR and related approaches such as different types of geog…

  • Gwverse

    Open AccessAlexis Comber, Martin Callaghan et al.ARTICLEGeographical Analysis2022

    GWR is a popular approach for investigating the spatial variation in relationships between response and predictor variables, and critically for investigating and understanding process spatial heterogeneity. The geographically weighted (GW) framework is increasingly used to accommodate different types of models and analyses, reflecting a wider desire to explore spatial variation in model parameters and outputs. However, the growth in the use of GW…

  • In memoriam

    Open AccessC Brunsdon, Alexis Comber et al.ARTICLEGeographical Analysis2022

    Martin Edward Charlton (1957–2021) Martin Charlton was one of the leading pioneers of quantitative geography and geocomputation whose work helped inspire the recent resurgence of spatial analysis and geographic data science. He was born in Newcastle upon Tyne, where he attended the Royal Grammar School and subsequently the University of Newcastle upon Tyne, where he gained a First Class (Hons) degree in Town and Country Planning in 1978. After a …

  • Unveiling the relationship between land use types and the temporal signals of crime

    Open AccessC Brunsdon, Jacqueline CorcoranARTICLEEnvironment and Planning B Urban…2022

    Whilst some land uses are highly criminogenic, others remain largely free of crime. This patterning is a reflection of the types and timing of daily activities that take place in a given land use and the opportunities that this presents for crime. While the criminology literature has developed a rigorous understanding of geographic component of crime, relatively less emphasis has been placed on the temporal dimension. Here, we address this throug…

  • Real-time suicide surveillance supporting policy and practice

    Open AccessRuth Benson, C Brunsdon et al.ARTICLECambridge Prisms Global Mental…2022

    Suicide mortality rates are a strong indicator of population mental-health and can be used to determine the efficacy of prevention measures. Monitoring suicide mortality rates in real-time provides an evidence-base to inform targeted interventions in a timely manner and accelerate suicide prevention responses. This paper outlines the importance of real-time suicide surveillance in the context of policy and practice, with a particular focus on pub…

  • The temporality of place

    Open AccessJacqueline Corcoran, Renee Zahnow et al.ARTICLEEnvironment and Planning B Urban…2021

    Well established in criminological scholarship is the way that crime is neither spatially nor temporally uniformly distributed. Rather crime is distributed in a manner that means it is both particular places and particular times that are subject to the majority of crime events. Furthermore, we know that crime varies over the course of a day and week, with periods of time the same place can function as a crime generator, a crime attractor or as a …

  • Robin Lovelace, Jakub Nowosad and Jannes Muenchow. Geocomputation with R

    Open AccessC BrunsdonARTICLEEnvironment and Planning B Urban…2020

    Book Review of: Geocomputation with R. Robin LovelaceJakub Nowosad & Jannes Muenchow . Geocomputation with R. Chapman and Hall/CRC Press: UK, 2019, 335 pp. ISBN: 9781138304512, £66.99 (hbk), ISBN: 9780203730058, £60.29 (eBook) Resources and code: https://geocompr.robinlovelace.net Reviewed by: Chris Brunsdon, National Centre for Geocomputation, Maynooth University, Ireland

  • Modelling epidemics

    Open AccessC BrunsdonARTICLEDialogues in Human Geography2020Cited by: 1References: 1

    This commentary reflects upon my experiences modelling epidemics from a geographical perspective. In particular, I consider different approaches to the modelling of epidemics and other forms of data analysis relevant to the COVID-19 pandemic within a geographical context, especially with respect to the need for ‘just in time’ policy-relevant research

  • The Importance of Scale in Spatially Varying Coefficient Modeling

    Daisuke Murakami, Bin Lu et al.ARTICLEAnnals of the American…2019Cited by: 6References: 68

    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 …

  • Data imputation in a short-run space-time series

    Open AccessLars Pforte, C Brunsdon et al.ARTICLEEnvironment and Planning B Urban…2018

    This paper discusses a project on the completion of a database of socio-economic indicators across the European Union for the years from 1990 onward at various spatial scales. Thus the database consists of various time series with a spatial component. As a substantial amount of the data was missing a method of imputation was required to complete the database. A Markov Chain Monte Carlo approach was opted for. We describe the Markov Chain Monte Ca…

  • Mapping the changing residential geography of White British secondary school children in England using visually balanced cartograms and hexograms

    Open AccessRichard Harris, Martin Charlton et al.ARTICLEJournal of Maps2018

    In the context of debates about segregation within the UK, this paper maps the residential geography of two groups of White British school children, one of which was in secondary school in 2011 and the other in 2017. To present that geography, hexograms are introduced as a complement to visually balanced cartograms, both of which seek to address the problems of invisibility and distortion encountered with more conventional choropleth and cartogra…

  • More bark than bytes? Reflections on 21+ years of geocomputation

    Open AccessRichard Harris, David O’sullivan et al.ARTICLEEnvironment and Planning B Urban…2017

    This year marks the 21st anniversary of the International GeoComputation Conference Series. To celebrate the occasion, Environment and Planning B invited some members of the geocomputational community to reflect on its achievements, some of the unrealised potential, and to identify some of the on-going challenges

  • Quantitative methods III

    Open AccessC BrunsdonARTICLEProgress in Human Geography2017Cited by: 1References: 1

    Stevens’ scales of measurement are often used in texts outlining statistical approaches for geographers. However, it is sometimes overlooked that these are not universally accepted, and indeed the theory surrounding them is contested. This progress report reviews the key ideas of these scales, and discusses a number of the problems they raise – most notably the fact that certain kinds of data are omitted. The value of an axiomatic approach to mea…

  • Balancing visibility and distortion

    Open AccessRichard Harris, Martin Charlton et al.ARTICLEEnvironment and Planning A…2017Cited by: 4

    A perennial problem when mapping demographic, social and other area-based data is that rural areas usually are of greater physical size than their urban counterparts. The consequence is that the places with fewest people dominate the map space, whereas those with the most are rendered small and illegible. A classic example is what happens if the results of the UK election are mapped, in this case for the 2015 election. As the left side of Figure …

  • Quantitative methods II

    Open AccessC BrunsdonARTICLEProgress in Human Geography2016Cited by: 1References: 1

    Although classical significance testing is the most commonly used inferential technique in quantitative geography, it is far from the only choice, and in some circumstances may not be the most appropriate. In the statistical literature and other disciplines, its utility has come under question in a number of contexts. This report overviews current progress in the development of quantitative inferential approaches, and considers their use and appr…

  • GWmodel

    Open AccessIsabella Gollini, Bin Lu et al.ARTICLEJournal of Statistical Software2015

    Spatial statistics is a growing discipline providing important analytical techniques in a wide range of disciplines in the natural and social sciences. In the R package GWmodel we present techniques from a particular branch of spatial statistics, termed geographically weighted (GW) models. GW models suit situations when data are not described well by some global model, but where there are spatial regions where a suitably localized calibration pro…

  • Quantitative methods I

    Open AccessC BrunsdonARTICLEProgress in Human Geography2015Cited by: 15References: 2

    Reproducible quantitative research is research that has been documented sufficiently rigorously that a third party can replicate any quantitative results that arise. It is argued here that such a goal is desirable for quantitative human geography, particularly as trends in this area suggest a turn towards the creation of algorithms and codes for simulation and the analysis of Big Data. A number of examples of good practice in this area are consid…

  • The GWmodel R package

    Open AccessBin Lu, Binbin Lu et al.ARTICLEGeo-spatial Information Science2014

    In this study, we present a collection of local models, termed geographically weighted \n(GW) models, that can be found within the GWmodel R package. A GW model suits \nsituations when spatial data are poorly described by the global form, and for some \nregions the localised fit provides a better description. The approach uses a moving \nwindow weighting technique, where a collection of local models are estimated at target \nlocations. Commonly, …