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Repository for paper "Building(s and) cities:Delineating urban areas with a machine learning algorithm", by Dani Arribas-Bel, Miquel-Angel Garcia-Lopez and Elisabet Viladecans

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Building(s and) Cities

Paper | Working Paper | Map | Data

Cities

Repository for the paper "Building(s and) cities: Delineating urban areas with a machine learning algorithm", forthcoming in the Journal of Urban Economics.

Authors:

Citation

If you use the code and/or data in this repository, we would appreciate if you could cite the original paper as:

@article{ab_gl_vm2019joue,
  title={Building(s and) cities: 
         Delineating urban areas with a machine learning algorithm},
  author={Arribas-Bel, Daniel and 
          Garcia-L\`{o}pez, Miquel-\'{A}ngel and
          Viladecans-Marsal, Elisabet},
  journal={Journal of Urban Economics},
  year={\emph{forthcoming}},
}

Interactive Map

You can explore the city delineations in the interactive map (click on the image):

Map

Data

City and employment centre boundary delineations are available as open data at:

https://figshare.com/articles/Building_s_and_cities_Delineating_urban_areas_with_a_machine_learning_algorithm_-City_Employment_Centre_Boundaries_v1/11384136

Computational Platform

The analysis in this repository was performed on machines running the gds_env platform, v3.0. The project's website is available at:

https://github.com/darribas/gds_env

And you can install the version used for this projec by first installing Docker (the community edition, CE, works fine) and then running:

docker pull darribas/gds:3.0

You can read more background about platforms like gds_env in Chapter 1 of the upcoming book in Geographic Data Science.

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Repository for paper "Building(s and) cities:Delineating urban areas with a machine learning algorithm", by Dani Arribas-Bel, Miquel-Angel Garcia-Lopez and Elisabet Viladecans

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