Publications
Selected publications
- Remote sensing-based measurement of Living Environment Deprivation: Improving classical approaches with machine learning (Journal article - 2017)
- Accidental, open and everywhere: Emerging data sources for the understanding of cities (Journal article - 2014)
- Geographic Data Science (Journal article - 2019)
- Building(s and) cities: Delineating urban areas with a machine learning algorithm (Journal article - 2019)
- The PySAL Ecosystem: Philosophy and Implementation (Journal article - 2022)
2024
Decoding (urban) form and function using spatially explicit deep learning
Fleischmann, M., & Arribas-Bel, D. (2024). Decoding (urban) form and function using spatially explicit deep learning. Computers, Environment and Urban Systems, 112, 102147. doi:10.1016/j.compenvurbsys.2024.102147
Inequalities in experiencing urban functions. An exploration of human digital (geo-)footprints
Calafiore, A., Samardzhiev, K., Rowe, F., Fleischmann, M., & Arribas-Bel, D. (2024). Inequalities in experiencing urban functions. An exploration of human digital (geo-)footprints. Environment and Planning B: Urban Analytics and City Science, 51(7), 1463-1477. doi:10.1177/23998083231208507
Digital twins on trial: Can they actually solve wicked societal problems and change the world for better?
Malleson, N., Franklin, R., Arribas-Bel, D., Cheng, T., & Birkin, M. (n.d.). Digital twins on trial: Can they actually solve wicked societal problems and change the world for better?. Environment and Planning B: Urban Analytics and City Science. doi:10.1177/23998083241262893
EPB turns 50 years old: An analytical tour of the last five decades
Crooks, A., Jiang, N., See, L., Alvanides, S., Arribas-Bel, D., Wolf, L., & Batty, M. (2024). EPB turns 50 years old: An analytical tour of the last five decades. Environment and Planning B: Urban Analytics and City Science, 51(5), 1028-1037. doi:10.1177/23998083241246928
Hopes and dreams for (future) better things: Medium, data, and ideas
Wolf, L. J., & Arribas-Bel, D. (2024). Hopes and dreams for (future) better things: Medium, data, and ideas. Environment and Planning B: Urban Analytics and City Science, 51(5), 1023-1027. doi:10.1177/23998083241249551
Geographic data science: a manifesto
Arribas-Bel, D., & Graser, A. (2024). Geographic data science: a manifesto. In A Research Agenda for Spatial Analysis (pp. 85-96). Edward Elgar Publishing. doi:10.4337/9781802203233.00013
Extracting Features from Satellite Imagery to Understand the Size and Scale of Housing Sub-Markets in Madrid
Kenyon, G. E., Arribas-Bel, D., & Robinson, C. (n.d.). Extracting Features from Satellite Imagery to Understand the Size and Scale of Housing Sub-Markets in Madrid. Land, 13(5), 575. doi:10.3390/land13050575
Intra-urban house prices in Madrid following the financial crisis: an exploration of spatial inequality
Kenyon, G. E., Arribas-Bel, D., Robinson, C., Gkountouna, O., Arbués, P., & Rey-Blanco, D. (2024). Intra-urban house prices in Madrid following the financial crisis: an exploration of spatial inequality. npj Urban Sustainability, 4(1). doi:10.1038/s42949-024-00161-0
In praise of (spatial) bundles
Arribas-Bel, D., & Fleischmann, M. (2024). In praise of (spatial) bundles. Environment and Planning B: Urban Analytics and City Science, 51(1), 3-6. doi:10.1177/23998083231224151
2023
Author Correction: Geographical characterisation of British urban form and function using the spatial signatures framework.
Fleischmann, M., & Arribas-Bel, D. (2023). Author Correction: Geographical characterisation of British urban form and function using the spatial signatures framework.. Scientific data, 10(1), 846. doi:10.1038/s41597-023-02773-0
Synthetic population Catalyst: A micro-simulated population of England with circadian activities
Salat, H., Carlino, D., Benitez-Paez, F., Zanchetta, A., Arribas-Bel, D., & Birkin, M. (2023). Synthetic population Catalyst: A micro-simulated population of England with circadian activities. ENVIRONMENT AND PLANNING B-URBAN ANALYTICS AND CITY SCIENCE. doi:10.1177/23998083231203066
Tracking the Transit Divide: A Multilevel Modelling Approach of Urban Inequalities and Train Ridership Disparities in Chicago
Owen, D., Arribas-Bel, D., & Rowe, F. (2023). Tracking the Transit Divide: A Multilevel Modelling Approach of Urban Inequalities and Train Ridership Disparities in Chicago. SUSTAINABILITY, 15(11). doi:10.3390/su15118821
Forecasting the UN Sustainable Development Goals
Alharbi, Y., Arribas-Bel, D., & Coenen, F. (2023). Forecasting the UN Sustainable Development Goals. In Communications in Computer and Information Science (pp. 88-110). Springer Nature Switzerland. doi:10.1007/978-3-031-37320-6_5
Geographic Data Science with Python
Rey, S., Arribas-Bel, D., & Wolf, L. J. (n.d.). Geographic Data Science with Python. Chapman and Hall/CRC. doi:10.1201/9780429292507
Local urban attributes defining ethnically segregated areas across English cities: A multilevel approach
Patias, N., Rowe, F., & Arribas-Bel, D. (2023). Local urban attributes defining ethnically segregated areas across English cities: A multilevel approach. Cities, 132, 103967. doi:10.1016/j.cities.2022.103967
Spatial-temporal variability: characterisation of a beach system using high resolution radar data
Murphy, J., Plater, A., Bird, C., & Arribas-Bel, D. (2023). Spatial-temporal variability: characterisation of a beach system using high resolution radar data. FRONTIERS IN MARINE SCIENCE, 10. doi:10.3389/fmars.2023.1142077
Urban exodus? Understanding human mobility in Britain during the COVID‐19 pandemic using Meta‐Facebook data
Rowe, F., Calafiore, A., Arribas‐Bel, D., Samardzhiev, K., & Fleischmann, M. (n.d.). Urban exodus? Understanding human mobility in Britain during the COVID‐19 pandemic using Meta‐Facebook data. Population, Space and Place. doi:10.1002/psp.2637
2022
An image library: The potential of imagery in (quantitative) social sciences
An image library: The potential of imagery in (quantitative) social sciences (2022). In Handbook of Spatial Analysis in the Social Sciences (pp. 528-543). Edward Elgar Publishing. doi:10.4337/9781789903942.00042
Assessing the value of user-generated images of urban surroundings for house price estimation
Chen, M., Liu, Y., Arribas-Bel, D., & Singleton, A. (2022). Assessing the value of user-generated images of urban surroundings for house price estimation. Landscape and Urban Planning, 226, 104486. doi:10.1016/j.landurbplan.2022.104486
Understanding (urban) spaces through form and function
Arribas-Bel, D., & Fleischmann, M. (2022). Understanding (urban) spaces through form and function. HABITAT INTERNATIONAL, 128. doi:10.1016/j.habitatint.2022.102641
Geographical characterisation of British urban form and function using the spatial signatures framework
Fleischmann, M., & Arribas-Bel, D. (2022). Geographical characterisation of British urban form and function using the spatial signatures framework. SCIENTIFIC DATA, 9(1). doi:10.1038/s41597-022-01640-8
Dynamic-IMD (D-IMD): Introducing activity spaces to deprivation measurement in London, Birmingham and Liverpool
Comber, S., Park, S., & Arribas-Bel, D. (2022). Dynamic-IMD (D-IMD): Introducing activity spaces to deprivation measurement in London, Birmingham and Liverpool. CITIES, 127. doi:10.1016/j.cities.2022.103733
Functional signatures in Great Britain: A dataset
Samardzhiev, K., Fleischmann, M., Arribas-Bel, D., Calafiore, A., & Rowe, F. (2022). Functional signatures in Great Britain: A dataset. DATA IN BRIEF, 43. doi:10.1016/j.dib.2022.108335
Estimating generalized measures of local neighbourhood context from multispectral satellite images using a convolutional neural network
Singleton, A., Arribas-Bel, D., Murray, J., & Fleischmann, M. (2022). Estimating generalized measures of local neighbourhood context from multispectral satellite images using a convolutional neural network. Computers, Environment and Urban Systems, 95, 101802. doi:10.1016/j.compenvurbsys.2022.101802
The PySAL Ecosystem: Philosophy and Implementation
Rey, S. J., Anselin, L., Amaral, P., Arribas-Bel, D., Cortes, R. X., Gaboardi, J. D., . . . Wolf, L. J. (2022). The PySAL Ecosystem: Philosophy and Implementation. GEOGRAPHICAL ANALYSIS, 54(3), 467-487. doi:10.1111/gean.12276
Trajectories of neighbourhood inequality in Britain: Unpacking inter‐regional socioeconomic imbalances, 1971−2011
Patias, N., Rowe, F., & Arribas‐Bel, D. (n.d.). Trajectories of neighbourhood inequality in Britain: Unpacking inter‐regional socioeconomic imbalances, 1971−2011. The Geographical Journal. doi:10.1111/geoj.12420
Urban Exodus? Understanding Human Mobility in Britain During the COVID-19 Pandemic Using Facebook Data
Tracking Coastal Change by Assimilating from Data Sources with Different Spatial and Temporal Scales
Higham, J., Plater, A., Phillips, B., Leonardi, N., Arribas-Bel, D., & Bird, C. (2022). Tracking Coastal Change by Assimilating from Data Sources with Different Spatial and Temporal Scales. In Proceedings of the IAHR World Congress (pp. 4115-4120). doi:10.3850/IAHR-39WC2521716X20221480
Tracking coastal change by assimilating from data sources with different spatial and temporal scales
Plater, A., Higham, J., Phillips, B., Leonardi, N., Arribas-Bel, D., & Bird, C. (2022). Tracking coastal change by assimilating from data sources with different spatial and temporal scales. In Proceedings of the 39th IAHR World Congress (pp. 4115-4120). International Association for Hydro-Environment Engineering and Research (IAHR). doi:10.3850/iahr-39wc2521711920221480
2021
Urban data/code: A new EP-B section
Arribas-Bel, D., Alvanides, S., Batty, M., Crooks, A., See, L., & Wolf, L. (2021). Urban data/code: A new EP-B section. ENVIRONMENT AND PLANNING B-URBAN ANALYTICS AND CITY SCIENCE, 48(9), 2517-2519. doi:10.1177/23998083211059670
Open data products-A framework for creating valuable analysis ready data
Arribas-Bel, D., Green, M., Rowe, F., & Singleton, A. (2021). Open data products-A framework for creating valuable analysis ready data. JOURNAL OF GEOGRAPHICAL SYSTEMS, 23(4), 497-514. doi:10.1007/s10109-021-00363-5
Sustainable Development Goal Relational Modelling and Prediction
Alharbi, Y., Arribas-Bel, D., & Coenen, F. (n.d.). Sustainable Development Goal Relational Modelling and Prediction. Journal of Data Intelligence, 2(3), 348-367. doi:10.26421/jdi2.3-3
Sustainable urban development indicators in Great Britain from 2001 to 2016
Patias, N., Rowe, F., Cavazzi, S., & Arribas-Bel, D. (2021). Sustainable urban development indicators in Great Britain from 2001 to 2016. LANDSCAPE AND URBAN PLANNING, 214. doi:10.1016/j.lurbplan.2021.104148
Assuring safe port navigation by assimilating from data sources with different spatial and temporal scales
Phillips, B., Higham, J., Plater, A., Leonardi, N., Arribas-Bel, D., Bird, C., & Sinclair, A. (2021). Assuring safe port navigation by assimilating from data sources with different spatial and temporal scales. doi:10.5194/egusphere-egu21-15491
Identifying and understanding road-constrained areas of interest (AOIs) through spatiotemporal taxi GPS data: A case study in New York City
Liu, Y., Singleton, A., Arribas-bel, D., & Chen, M. (2021). Identifying and understanding road-constrained areas of interest (AOIs) through spatiotemporal taxi GPS data: A case study in New York City. COMPUTERS ENVIRONMENT AND URBAN SYSTEMS, 86. doi:10.1016/j.compenvurbsys.2020.101592
On Spatial and Platial Dependence: Examining Shrinkage in Spatially Dependent Multilevel Models
Wolf, L. J., Anselin, L., Arribas-Bel, D., & Mobley, L. R. (2021). On Spatial and Platial Dependence: Examining Shrinkage in Spatially Dependent Multilevel Models. Annals of the American Association of Geographers, 1-13. doi:10.1080/24694452.2020.1841602
GIS and Computational Notebooks
Boeing, G., & Arribas-Bel, D. (n.d.). GIS and Computational Notebooks. Geographic Information Science & Technology Body of Knowledge, 2021(Q1). doi:10.22224/gistbok/2021.1.2
GIS and Computational Notebooks
A geographic data science framework for the functional and contextual analysis of human dynamics within global cities
Calafiore, A., Palmer, G., Comber, S., Arribas-Bel, D., & Singleton, A. (2021). A geographic data science framework for the functional and contextual analysis of human dynamics within global cities. COMPUTERS ENVIRONMENT AND URBAN SYSTEMS, 85. doi:10.1016/j.compenvurbsys.2020.101539
GIS and Computational Notebooks
Modelling and Prediction.
Sustainable Development Goals Monitoring and Forecasting using Time Series Analysis
Alharbi, Y., Arribas-Bel, D., & Coenen, F. (2021). Sustainable Development Goals Monitoring and Forecasting using Time Series Analysis. In Proceedings of the 2nd International Conference on Deep Learning Theory and Applications (pp. 123-131). SCITEPRESS - Science and Technology Publications. doi:10.5220/0010546100002996
Sustainable Development Goals Monitoring and Forecasting using Time Series Analysis
Alharbi, Y., Arribas-Bel, D., & Coenen, F. (2021). Sustainable Development Goals Monitoring and Forecasting using Time Series Analysis. In PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON DEEP LEARNING THEORY AND APPLICATIONS (DELTA) (pp. 123-131). doi:10.5220/0010546101230131
2020
The Potential of Notebooks for Scientific Publication, Reproducibility and Dissemination
Rowe, F., Maier, G., Arribas-Bel, D., & Rey, S. (2020). The Potential of Notebooks for Scientific Publication, Reproducibility and Dissemination. REGION, 7(3), E1-E5. doi:10.18335/region.v7i3.357
How sensitive is city size distribution to the definition of city? The case of Spain
Puente-Ajovin, M., Ramos, A., Sanz-Gracia, F., & Arribas-Bel, D. (2020). How sensitive is city size distribution to the definition of city? The case of Spain. ECONOMICS LETTERS, 197. doi:10.1016/j.econlet.2020.109643
Who Counts? Gender, Gatekeeping, and Quantitative Human Geography
Franklin, R., Houlden, V., Robinson, C., Arribas-Bel, D., Delmelle, E., Demšar, U., . . . O'Sullivan, D. (2020). Who Counts? Gender, Gatekeeping, and Quantitative Human Geography. The Professional Geographer. doi:10.1080/00330124.2020.1828944
Using convolutional autoencoders to extract visual features of leisure and retail environments
Comber, S., Arribas-Bel, D., Singleton, A., & Dolega, L. (2020). Using convolutional autoencoders to extract visual features of leisure and retail environments. LANDSCAPE AND URBAN PLANNING, 202. doi:10.1016/j.landurbplan.2020.103887
Sustainable Development Goal Relational Modelling: Introducing the SDG-CAP Methodology
Coenen, F., Alharbi, Y., & Arribas-Bel, D. (2020). Sustainable Development Goal Relational Modelling: Introducing the SDG-CAP Methodology. In Lecture Notes in Computer Science Vol. 12393 (pp. 183-196). Bratislava, Slovakia: Springer Nature.
Key questions for modelling COVID-19 exit strategies.
Thompson, R. N., Hollingsworth, T. D., Isham, V., Arribas-Bel, D., Ashby, B., Britton, T., . . . Restif, O. (2020). Key questions for modelling COVID-19 exit strategies.. Proceedings. Biological sciences, 287(1932), 20201405. doi:10.1098/rspb.2020.1405
Classification and Regression via Integer Optimization for Neighborhood Change
Olson, A. W., Zhang, K., Calderon-Figueroa, F., Yakubov, R., Sanner, S., Silver, D., & Arribas-Bel, D. (2020). Classification and Regression via Integer Optimization for Neighborhood Change. Geographical Analysis. doi:10.1111/gean.12252
Sustainable Development Goal Relational Modelling: Introducing the SDG-RMF Methodology
Alharbi, Y., Coenen, F., & Arribas-Bel, D. (2020). Sustainable Development Goal Relational Modelling: Introducing the SDG-RMF Methodology. Retrieved from https://crcs.seas.harvard.edu/
Building Hierarchies of Retail Centers Using Bayesian Multilevel Models
Comber, S., Arribas-Bel, D., Singleton, A., Dong, G., & Dolega, L. (2020). Building Hierarchies of Retail Centers Using Bayesian Multilevel Models. ANNALS OF THE AMERICAN ASSOCIATION OF GEOGRAPHERS, 110(4), 1150-1173. doi:10.1080/24694452.2019.1667219
Building Hierarchies of Retail Centers Using Bayesian Multilevel Models
Arribas-Bel, D., Comber, S., Dong, G., Singleton, A., & Dolega, L. (n.d.). Building Hierarchies of Retail Centers Using Bayesian Multilevel Models. Annals of the Association of American Geographers. doi:10.1080/24694452.2019.1667219
Professor Ronald John Johnston OBE, FAcSS, FBA (1941-2020) Obituary
See, L., Batty, M., Alvanides, S., Arribas-Bel, D., & Wolf, L. (2020). Professor Ronald John Johnston OBE, FAcSS, FBA (1941-2020) Obituary. ENVIRONMENT AND PLANNING B-URBAN ANALYTICS AND CITY SCIENCE, 47(6), 937-938. doi:10.1177/2399808320943989
Who Counts? Gender, Gatekeeping, and Quantitative Human Geography
Considering context and dynamics: A classification of transit-orientated development for New York City
Liu, Y., Singleton, A., & Arribas-Bel, D. (2020). Considering context and dynamics: A classification of transit-orientated development for New York City. JOURNAL OF TRANSPORT GEOGRAPHY, 85. doi:10.1016/j.jtrangeo.2020.102711
Quantifying the Characteristics of the Local Urban Environment through Geotagged Flickr Photographs and Image Recognition
Chen, M., Arribas-Bel, D., & Singleton, A. (2020). Quantifying the Characteristics of the Local Urban Environment through Geotagged Flickr Photographs and Image Recognition. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 9(4). doi:10.3390/ijgi9040264
splot - visual analytics for spatial statistics
Lumnitz, S., Arribas-Bell, D., Cortes, R., Gaboardi, J., Griess, V., Kang, W., . . . Rey, S. (2020). splot - visual analytics for spatial statistics. Journal of Open Source Software, 5(47), 1882. doi:10.21105/joss.01882
A reproducible notebook to acquire, process and analyse satellite imagery
Chen, M., Fahrner, D., Arribas-Bel, D., & Rowe, F. (n.d.). A reproducible notebook to acquire, process and analyse satellite imagery. REGION, 7(2), R15-R46. doi:10.18335/region.v7i2.295
2019
Building(s and) cities: Delineating urban areas with a machine learning algorithm
Arribas-Bel, D., Garcia-Lopez, M. -A., & Viladecans-Marsal, E. (2019). Building(s and) cities: Delineating urban areas with a machine learning algorithm. Journal of Urban Economics. doi:10.1016/j.jue.2019.103217
A Hierarchical Urban Forest Index Using Street-Level Imagery and Deep Learning
Stubbings, P., Peskett, J., Rowe, F. R., & Arribas-Bel, D. (2019). A Hierarchical Urban Forest Index Using Street-Level Imagery and Deep Learning. Remote Sensing, 11(12). doi:10.3390/rs11121395
A principal component analysis (PCA)-based framework for automated variable selection in geodemographic classification
Liu, Y., Singleton, A., & Arribas-Bel, D. (2019). A principal component analysis (PCA)-based framework for automated variable selection in geodemographic classification. Geo-Spatial Information Science. doi:10.1080/10095020.2019.1621549
A course on Geographic Data Science
Arribas-Bel, D. (2019). A course on Geographic Data Science. Journal of Open Source Education, 2(14), 42. doi:10.21105/jose.00042
Machine learning innovations in address matching: A practical comparison of word2vec and CRFs
Comber, S., & Arribas-Bel, D. (2019). Machine learning innovations in address matching: A practical comparison of word2vec and CRFs. Transactions in GIS, 23(2), 334-348. doi:10.1111/tgis.12522
Geographic Data Science
Singleton, A., & Arribas-Bel, D. (2019). Geographic Data Science. Geographical Analysis: an international journal of theoretical geography, Special Issue(0), 1-15. doi:10.1111/gean.12194
Buy online collect in-store: Exploring grocery click & collect using a national case study
Davies, A. E., Dolega, L., & Arribas-Bel, D. (2019). Buy online collect in-store: Exploring grocery click & collect using a national case study. International Journal of Retail & Distribution Management, 47(3), 278-291. doi:10.1108/IJRDM-01-2018-0025
Understanding the dynamics of urban areas of interest through volunteered geographic information
Chen, M., Arribas-Bel, D., & Singleton, A. (2019). Understanding the dynamics of urban areas of interest through volunteered geographic information. JOURNAL OF GEOGRAPHICAL SYSTEMS, 21(1), 89-109. doi:10.1007/s10109-018-0284-3
Policy Brief: Neighbourhood Change and Trajectories of Inequality in Britain, 1971-2011
Rowe, F. R., Patias, N., & Arribas-Bel, D. (2019). Policy Brief: Neighbourhood Change and Trajectories of Inequality in Britain, 1971-2011.
Inferring neighbourhood quality with property transaction records by using a locally adaptive spatial multi-level model
Dong, G., Wolf, L., Alexiou, A., & Arribas-Bel, D. (2019). Inferring neighbourhood quality with property transaction records by using a locally adaptive spatial multi-level model. COMPUTERS ENVIRONMENT AND URBAN SYSTEMS, 73, 118-125. doi:10.1016/j.compenvurbsys.2018.09.003
Introduction to new Editors
Arribas-Bel, D., & Alvanides, S. (2019). Introduction to new Editors. ENVIRONMENT AND PLANNING B-URBAN ANALYTICS AND CITY SCIENCE, 46(1), 8. doi:10.1177/2399808318820153
Statistics, Modelling, and Data Science
Arribas-Bel, D. (2019). Statistics, Modelling, and Data Science. In Digital Geographies (pp. 129-140). SAGE Publications Ltd. doi:10.4135/9781529793536.n12
Sustainable Development Goal Attainment Prediction: A Hierarchical Framework using Time Series Modelling
Alharbi, Y., Arribas-Be, D., & Coenen, F. (2019). Sustainable Development Goal Attainment Prediction: A Hierarchical Framework using Time Series Modelling. In KDIR: PROCEEDINGS OF THE 11TH INTERNATIONAL JOINT CONFERENCE ON KNOWLEDGE DISCOVERY, KNOWLEDGE ENGINEERING AND KNOWLEDGE MANAGEMENT - VOL 1: KDIR (pp. 297-304). doi:10.5220/0008067202970304
2018
Spatial dynamics of cultural diversity in the Netherlands
Arribas-Bel, D., & Bakens, J. (2018). Spatial dynamics of cultural diversity in the Netherlands. ENVIRONMENT AND PLANNING B-URBAN ANALYTICS AND CITY SCIENCE, 45(6), 1142-1156. doi:10.1177/2399808318783748
Geography and computers: Past, present, and future
Arribas-Bel, D., & Reades, J. (2018). Geography and computers: Past, present, and future. GEOGRAPHY COMPASS, 12(10). doi:10.1111/gec3.12403
Use and validation of location-based services in urban research: An example with Dutch restaurants
Arribas-Bel, D., & Bakens, J. (2018). Use and validation of location-based services in urban research: An example with Dutch restaurants. Urban Studies. doi:10.1177/0042098018779554
On Spatial and Platial Dependence: Examining Shrinkage in Spatially-Dependent Multilevel Models
Big Urban Data: Challenges and Opportunities for Geographical Analysis
Arribas-Bel, D., & Tranos, E. (2018). Big Urban Data: Challenges and Opportunities for Geographical Analysis. GEOGRAPHICAL ANALYSIS, 50(2), 123-124. doi:10.1111/gean.12157
Characterizing the Spatial Structure(s) of Cities “on the fly”: the Space-Time Calendar
Arribas-Bel., & Tranos, E. (n.d.). Characterizing the Spatial Structure(s) of Cities “on the fly”: the Space-Time Calendar. Geographical Analysis: an international journal of theoretical geography. doi:10.1111/gean.12137
Demographic Aging and Employment Dynamics in German Regions: Modeling Regional Heterogeneity
de Graaff, T., Arribas-Bel, D., & Ozgen, C. (2018). Demographic Aging and Employment Dynamics in German Regions: Modeling Regional Heterogeneity. In MODELLING AGING AND MIGRATION EFFECTS ON SPATIAL LABOR MARKETS (pp. 211-231). doi:10.1007/978-3-319-68563-2_11
Stochastic Efficiency of Bayesian Markov Chain Monte Carlo in Spatial Econometric Models: An Empirical Comparison of Exact Sampling Methods
Wolf, L. J., Anselin, L., & Arribas-Bel, D. (2018). Stochastic Efficiency of Bayesian Markov Chain Monte Carlo in Spatial Econometric Models: An Empirical Comparison of Exact Sampling Methods. GEOGRAPHICAL ANALYSIS, 50(1), 97-119. doi:10.1111/gean.12135
2017
“Waiting on the train”: The anticipatory (causal) effects of Crossrail in Ealing
Arribas-Bel., & Comber, S. (n.d.). “Waiting on the train”: The anticipatory (causal) effects of Crossrail in Ealing. Journal of Transport Geography. doi:10.1016/j.jtrangeo.2017.08.004
More bark than bytes? Reflections on 21+ years of geocomputation
Arribas-Bel., Richard Harris., David O'Sullivan., Mark Gahegan., Martin Charlton., Lex Comber., . . . Andy Evans. (2017). More bark than bytes? Reflections on 21+ years of geocomputation. Environment and Planning B: Planning and Design. doi:10.1177/2399808317710132
Remote sensing-based measurement of Living Environment Deprivation: Improving classical approaches with machine learning
Arribas-Bel, D., Patino, J. E., & Duque, J. C. (2017). Remote sensing-based measurement of Living Environment Deprivation: Improving classical approaches with machine learning. PLoS One, 12(5). doi:10.1371/journal.pone.0176684
Review of: London: The Information Capital: 100 Maps and Graphics That Will Change How You View the City. James Cheshire and Oliver Uberti. London: Particular Books (Penguin), 2014. 240. Hardcover, £18.75. ISBN-101846148472.
Arribas-Bel, D. (2017). London: The Information Capital: 100 Maps and Graphics That Will Change How You View the City. PAPERS IN REGIONAL SCIENCE, 96(1), 223-224. doi:10.1111/pirs.12281
Looking at John Snow's Cholera Map from the Twenty First Century: A Practical Primer on Reproducibility and Open Science
Arribas-Bel, D., de Graaff, T., & Rey, S. J. (2017). Looking at John Snow's Cholera Map from the Twenty First Century: A Practical Primer on Reproducibility and Open Science. In REGIONAL RESEARCH FRONTIERS, VOL. 2: METHODOLOGICAL ADVANCES, REGIONAL SYSTEMS MODELING AND OPEN SCIENCES (pp. 283-306). doi:10.1007/978-3-319-50590-9_17
2016
How diverse can measures of segregation be? Results from Monte Carlo simulations of an agent-based model
Arribas-Bel, D., Nijkamp, P., & Poot, J. (2016). How diverse can measures of segregation be? Results from Monte Carlo simulations of an agent-based model. ENVIRONMENT AND PLANNING A, 48(10), 2046-2066. doi:10.1177/0308518X16653402
Spatial Variation in the Quality of American Community Survey Estimates
Folch, D. C., Arribas-Bel, D., Koschinsky, J., & Spielman, S. E. (2016). Spatial Variation in the Quality of American Community Survey Estimates. DEMOGRAPHY, 53, 1535-1554. doi:10.1007/s13524-016-0499-1
The sociocultural sources of urban buzz
Arribas-Bel, D., Kourtit, K., & Nijkamp, P. (2016). The sociocultural sources of urban buzz. ENVIRONMENT AND PLANNING C-GOVERNMENT AND POLICY, 34(1), 188-204. doi:10.1177/0263774X15614711
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Arribas-Bel, D. (2016). <citation type="book" xml:id="jors12244-cit-0003"><bookTitle>Geocomputation: A Practical Primer</bookTitle>, edited by <author><givenNames>Chris</givenNames> <familyName>Brunson</familyName></author> and <author><givenNames>Alex</givenNames> <familyName>Singleton</familyName></author>. <pubYear year="2015">2015</pubYear>. <publisherLoc>London</publisherLoc>: <publisherName>Sage Publication Ltd</publisherName>. 369+xx. ISBN: 9781446272930. $52.00.</citation>. Journal of Regional Science, 56(1), 176-178.
Geocomputation: A Practical Primer
Arribas-Bel, D. (2016). Geocomputation: A Practical Primer. JOURNAL OF REGIONAL SCIENCE, 56(1), 176-178. doi:10.1111/jors.12244
2015
Cyber Cities: Social Media as a Tool for Understanding Cities
Arribas-Bel, D., Kourtit, K., Nijkamp, P., & Steenbruggen, J. (2015). Cyber Cities: Social Media as a Tool for Understanding Cities. APPLIED SPATIAL ANALYSIS AND POLICY, 8(3), 231-247. doi:10.1007/s12061-015-9154-2
WooW-II: Workshop on open workflows
Arribas-Bel, D., & De Graaff, T. (n.d.). WooW-II: Workshop on open workflows. REGION, 2(2), R1-R2. doi:10.18335/region.v2i2.85
From manufacturing belt, to rust belt, to college country: a visual narrative of US urban growth
Arribas-Bel, D., & Gerritse, M. (2015). From manufacturing belt, to rust belt, to college country: a visual narrative of US urban growth. ENVIRONMENT AND PLANNING A-ECONOMY AND SPACE, 47(6), 1241-1253. doi:10.1068/a140387p
From manufacturing belt, to rust belt, to college country: a visual narrative of US urban growth
Arribas-Bel, D., & Gerritse, M. (2015). From manufacturing belt, to rust belt, to college country: a visual narrative of US urban growth. Unknown Journal, 47(6), 1241-1253.
Review: Creative Economies in Post-Industrial Cities; Manufacturing a (Different) Scene, Simulation of Complex Systems in GIS, the Data Revolution: Big Data, Open Data, Data Infrastructures and Their Consequences
Brydges, T., Arribas-Bel, D., & Cinnamon, J. (2015). Review: Creative Economies in Post-Industrial Cities; Manufacturing a (Different) Scene, Simulation of Complex Systems in GIS, the Data Revolution: Big Data, Open Data, Data Infrastructures and Their Consequences. Environment and Planning B: Planning and Design, 42(3), 564-567. doi:10.1068/b4203rev
Migrant Entrepreneurs as Urban 'Health Angels' - Contrasts in Growth Strategies
Kourtit, K., Nijkamp, P., & Arribas-Bel, D. (2015). Migrant Entrepreneurs as Urban 'Health Angels' - Contrasts in Growth Strategies. INTERNATIONAL PLANNING STUDIES, 20(1-2), 71-86. doi:10.1080/13563475.2014.942496
The Size Distribution of Employment Centers within the US Metropolitan Areas
Arribas-Bel, D., Ramos, A., & Sanz-Gracia, F. (2015). The Size Distribution of Employment Centers within the US Metropolitan Areas. Unknown Journal, 42(1), 23-39.
Simulation of Complex Systems in GIS
Arribas-Bel, D. (2015). Simulation of Complex Systems in GIS. ENVIRONMENT AND PLANNING B-PLANNING & DESIGN, 42(3), 565-566. Retrieved from https://www.webofscience.com/
The size distribution of employment centers within the US Metropolitan Areas
Arribas-Bel, D., Ramos, A., & Sanz-Gracia, F. (2015). The size distribution of employment centers within the US Metropolitan Areas. ENVIRONMENT AND PLANNING B-PLANNING & DESIGN, 42(1), 23-39. doi:10.1068/b39038
The spoken postcodes
Arribas-Bel, D. (2015). The spoken postcodes. REGIONAL STUDIES REGIONAL SCIENCE, 2(1), 458-461. doi:10.1080/21681376.2015.1067151
2014
The validity of the monocentric city model in a polycentric age: US metropolitan areas in 1990, 2000 and 2010
Arribas-Bel, D., & Sanz-Gracia, F. (2014). The validity of the monocentric city model in a polycentric age: US metropolitan areas in 1990, 2000 and 2010. Urban Geography, 35(7), 980-997. doi:10.1080/02723638.2014.940693
How Diverse can Spatial Measures of Cultural Diversity be? Results from Monte Carlo Simulations on an Agent-Based Model
Arribas-Bel, D., Nijkamp, P., & Poot, J. (2014). How Diverse can Spatial Measures of Cultural Diversity be? Results from Monte Carlo Simulations on an Agent-Based Model.
Spatial data, analysis, and regression - a mini course
Arribas-Bel, D. (n.d.). Spatial data, analysis, and regression - a mini course. REGION, 1(1), R1. doi:10.18335/region.v1i1.42
How Diverse Can Spatial Measures of Cultural Diversity Be? Results from Monte Carlo Simulations on an Agent-Based Model
Arribas-Bel, D., Nijkamp, P., & Poot, J. (2014). How Diverse Can Spatial Measures of Cultural Diversity Be? Results from Monte Carlo Simulations on an Agent-Based Model.
Accidental, open and everywhere: Emerging data sources for the understanding of cities
Arribas-Bel, D. (2014). Accidental, open and everywhere: Emerging data sources for the understanding of cities. APPLIED GEOGRAPHY, 49, 45-53. doi:10.1016/j.apgeog.2013.09.012
2013
Testing for spatial error dependence in probit models
Amaral, P. V., Anselin, L., & Arribas-Bel, D. (2013). Testing for spatial error dependence in probit models. Letters in Spatial and Resource Sciences, 6(2), 91-101. doi:10.1007/s12076-012-0089-9
Benchmarking of world cities through Self-Organizing Maps
Arribas-Bel, D., Kourtit, K., & Nijkamp, P. (2013). Benchmarking of world cities through Self-Organizing Maps. Cities, 31, 248-257. doi:10.1016/j.cities.2012.06.019
Spatial fixed effects and spatial dependence in a single cross‐section
Anselin, L., & Arribas-Bel, D. (2013). Spatial fixed effects and spatial dependence in a single cross‐section. Papers in Regional Science, 92(1), 3-18. doi:10.1111/j.1435-5957.2012.00480.x
The creative urban diaspora economy: a disparity analysis among migrant entrepreneurs
Kourtit, K., Nijkamp, P., & Arribas- Bel, D. (2013). The creative urban diaspora economy: a disparity analysis among migrant entrepreneurs. In Handbook of Research Methods and Applications in Urban Economies. Edward Elgar Publishing. doi:10.4337/9780857934628.00029
Self-Organizing Maps and the US Urban Spatial Structure
Arribas-Bel, D., & Schmidt, C. R. (2013). Self-Organizing Maps and the US Urban Spatial Structure. Environment and Planning B: Planning and Design, 40(2), 362-371. doi:10.1068/b37014
2012
Featured Graphic. Monocentricity? Commuting Flows Visually
Arribas-Bel, D., & Gerritse, M. (2012). Featured Graphic. Monocentricity? Commuting Flows Visually. Environment and Planning A: Economy and Space, 44(9), 2041-2042. doi:10.1068/a44561
Improving the multi-dimensional comparison of simulation results: a spatial visualization approach
Arribas-Bel, D., Koschinsky, J., & Amaral, P. V. (2012). Improving the multi-dimensional comparison of simulation results: a spatial visualization approach. Letters in Spatial and Resource Sciences, 5(2), 55-63. doi:10.1007/s12076-011-0064-x
High performers in complex spatial systems: a self-organizing mapping approach with reference to The Netherlands
Kourtit, K., Arribas-Bel, D., & Nijkamp, P. (2012). High performers in complex spatial systems: a self-organizing mapping approach with reference to The Netherlands. The Annals of Regional Science, 48(2), 501-527. doi:10.1007/s00168-011-0483-z
2011
Multidimensional urban sprawl in Europe: A self-organizing map approach
Arribas-Bel, D., Nijkamp, P., & Scholten, H. (2011). Multidimensional urban sprawl in Europe: A self-organizing map approach. Computers, Environment and Urban Systems, 35(4), 263-275. doi:10.1016/j.compenvurbsys.2010.10.002
Measuring Spatial Dynamics in Metropolitan Areas
Rey, S. J., Anselin, L., Folch, D. C., Arribas-Bel, D., Sastré Gutiérrez, M. L., & Interlante, L. (2011). Measuring Spatial Dynamics in Metropolitan Areas. Economic Development Quarterly, 25(1), 54-64. doi:10.1177/0891242410383414