Daniel Arribas‐Bel

University of Liverpool

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Papers

Citation

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i-10 index

Research Field

Geography and computers: Past, present, and future

Geography Compass (2018)

Daniel Arribas‐Bel Jonathan Reades

Abstract The discipline of Geography has long been intertwined with the use of computers. This close interaction is likely to increase with the embeddedness of computers and concomitant growth of spatially referenced data. To better understand the current situation, and to be able to better speculate about the future, this article provides two parallel perspectives: first, we offer an historical perspective on the relationship between Geography and computers; second, we document developments—in particular the nascent field of data science—that are currently taking place outside of Geography and to which we argue the discipline should be paying close attention. Combining both perspectives, we identify the benefits of tighter integration between Geography and Data Science and argue for the establishment of a new space—that we term Geographic Data Science—in which cross‐pollination could occur to the benefit of both Geography and the larger data community.

Embeddedness

Critical Geography

Time geography

10.1111/gec3.12403

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Citations (38)

GIS and Computational Notebooks

Geoff Boeing Daniel Arribas‐Bel

Researchers and practitioners across many disciplines have recently adopted computational notebooks to develop, document, and share their scientific workflows - and the GIS community is no exception. This chapter introduces computational notebooks in the geographical context. It begins by explaining the computational paradigm and philosophy that underlie notebooks. Next it unpacks their architecture to illustrate a notebook user's typical workflow. Then it discusses the main benefits notebooks offer GIS researchers and practitioners, including better integration with modern software, more natural access to new forms of data, and better alignment with the principles and benefits of open science. In this context, it identifies notebooks as the glue that binds together a broader ecosystem of open source packages and transferable platforms for computational geography. The chapter concludes with a brief illustration of using notebooks for a set of basic GIS operations. Compared to traditional desktop GIS, notebooks can make spatial analysis more nimble, extensible, and reproducible and have thus evolved into an important component of the geospatial science toolkit.

Component (thermodynamics)

10.31235/osf.io/x2p49

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Citations (1)

The validity of the monocentric city model in a polycentric age: US metropolitan areas in 1990, 2000 and 2010

Urban Geography (2014)

Daniel Arribas‐Bel Fernando Sanz

In this article, we use local indicators of spatial association (LISA) and other spatial analysis techniques to analyze the distribution of centers with high employment density within metropolitan areas. We examine the 359 metropolitan areas across the United States at three points in time (1990, 2000, and 2010) to provide a spatio-temporal panoramic of urban spatial structure. Our analysis highlights three key findings. (1) The monocentric structure persists in a majority of metropolitan areas: 56.5% in 1990, 64.1% in 2000, and 57.7% in 2010. (2) The pattern of employment centers remains stable for most metropolitan areas: the number of centers remained the same for 74.9% of metropolitan areas between 1990 and 2000 and for 85.2% between 2000 and 2010. (3) Compared with monocentric metropolitan areas, polycentric metros are larger and more dense, with higher per-capita incomes and lower poverty rates.

10.1080/02723638.2014.940693

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Citations (143)

WooW-II: Workshop on open workflows

REGION (2015)

Daniel Arribas‐Bel Thomas de Graaff

This resource describes WooW-II, a two-day workshop on open workflows for quantitative social scientists. The workshop is broken down in five main parts, where each of them typically consists of an introductionary tutorial and a hands-on assignment. The specific tools discussed in this workshop are Markdown, Pandoc, Git, Github, R, and Rstudio, but the theoretical approach applies to a wider range of tools (e.g., LATEX and Python). By the end of the workshop, participants should be able to reproduce a paper of their own and make it available in an open form applying the concepts and tools introduced.

Python

10.18335/region.v2i2.85

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Citations (3)

Using deep learning to identify (urban) form and function in satellite imagery - the case of Great Britain

Zenodo (CERN European Organization for Nuclear Research) (2022)

Martin Fleischmann Daniel Arribas‐Bel

Satellite broadcasting

10.5281/zenodo.6411621

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“Waiting on the train”: The anticipatory (causal) effects of Crossrail in Ealing

Journal of Transport Geography (2017)

Sam Comber Daniel Arribas‐Bel

This paper estimates the willingness-to-pay for anticipated journey-time savings introduced by the Crossrail intervention in the London Borough of Ealing. Given Crossrail remains under construction, we estimate how the anticipated benefit of Crossrail's announcement enters the house price determination process. Anticipated journey-time savings should enter the home-buyer's pricing equation because these benefits are speculatively internalised even before the service becomes operational. Using a experimental method that accounts for the possibility of a spatial autoregressive process in housing values, we test the hypotheses that the announcement of a new commuter rail service generated a location premium, and that house price appreciation reflected proximity to Crossrail terminals. Our evidence suggests home-buyers significantly valued proximity to planned Crossrail terminals following the post-announcement period.

Borough

10.1016/j.jtrangeo.2017.08.004

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Citations (18)

Tracking coastal change by assimilating from data sources with different spatial and temporal scales

Proceedings of the 39th IAHR World Congress (2022)

Andy Plater Jonathan Higham Ben L. Phillips Nicoletta Leonardi Daniel Arribas‐Bel

Temporal scales

Tracking (education)

10.3850/iahr-39wc2521711920221480

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How Diverse Can Spatial Measures of Cultural Diversity Be? Results from Monte Carlo Simulations of an Agent-Based Model

SSRN Electronic Journal (2014)

Daniel Arribas‐Bel Peter Nijkamp Jacques Poot

Cultural diversity is a complex and multi-faceted concept. Commonly used quantitative measures of the spatial distribution of culturally-defined groups – such as segregation, isolation or concentration indexes – are often only capable of identifying just one aspect of this distribution. The strengths or weaknesses of any measure can only be comprehensively assessed empirically.This paper provides evidence on the empirical properties of various spatial measures of cultural diversity by using Monte Carlo replications of agent-based modeling (MC-ABM) simulations with synthetic data assigned to a realistic and detailed geographical context of the city of Amsterdam. Schelling's classical segregation model is used as the theoretical engine to generate patterns of spatial clustering. The data inputs include the initial population, the number and shares of various cultural groups, and their preferences with respect to co-location. Our MC-ABM data generating process produces output maps that enable us to assess the performance of various spatial measures of cultural diversity under a range of demographic compositions and preferences.We find that, as our simulated city becomes more diverse, stable residential location equilibria are only possible when people, particularly minorities, become more tolerant. We test whether observed measures can be interpreted as revealing unobserved preferences for co-location of individuals with their own group and find that the segregation and isolation measures of spatial diversity are shown to be non-decreasing in increasing preference for within-group co-location, but the Gini coefficient and concentration measures are not.

Isolation

Spatial contextual awareness

10.2139/ssrn.2460154

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Citations (1)

Local urban attributes defining ethnically segregated areas across English cities: A multilevel approach

Cities (2022)

Nikos Patias Francisco Rowe Daniel Arribas‐Bel

The literature of spatial inequalities is currently "fragmented" across ethnic segregation and built environment domains. Inequalities in these dimensions are often considered in isolation one from another. For example, ethnic segregated areas are often more disadvantaged in terms of unemployment, housing conditions and access to services. By using a combination of the most recent Census and a series of openly available datasets related to ambient urban environment characteristics at the Lower Super Output Area (LSOA) for the 12 biggest cities in England, we employed a series of multilevel models to explore the within and between city variations in the relationship across ethnic segregation, and key socioeconomic and built environment features of neighbourhoods. The results showed that ethnic minority segregated areas are associated with distinct and remarkably systematic patterns of socioeconomic characteristics, but do not lack access to good quality schools and public transport compared to the predominant white population communities. Ethnically segregated communities seem to consistently experience higher unemployment, long-term illness, higher average household size, and high exposure to pollution compared to white population groups across English cities. These relationships are remarkably similar across ethnic groups evidencing the extent of systematic persistent disadvantage experienced by minority communities relative to white populations. Moreover, the strength of these relationships varies widely across cities, although the overall systematic pattern prevails.

Disadvantaged

Disadvantage

Spatial mismatch

Urban sprawl

Neighbourhood (mathematics)

10.1016/j.cities.2022.103967

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Citations (22)

Multi-dimensional urban sprawl in Europe: a self-organizing map approach

Daniel Arribas‐Bel Peter Nijkamp H.J. Scholten

The present paper considers urban sprawl in Europe from a multi- dimensional and exploratory point of view. Several literatures on the topic (mainly from urban economics, but also from other fields such as urban planning or regional science) are reviewed to extract the main dimensions of the phenomenon, which are found to be the following six: connectivity, decentralization, density, scattering, accessibility to open space and land- use mix. Several indicators are defined and calculated to measure them for a representative sample of 209 European cities. The data are presented to the self-organizing map (SOM) algorithm to observe how the different dimensions interact with each other and what is their behaviour. The analysis of the SOM reveals very interesting patterns that could not be unveiled otherwise. The paper also presents results of an exploration on the relation to geographical location and population size, characterizing the cities in terms of their degree and variety of sprawl.

Urban sprawl

Sample (material)

Exploratory analysis

Source

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