Straulino, Daniel;
Saldarriaga, Juan C;
Gómez, Jairo A;
Duque, Juan C;
O'Clery, Neave;
(2022)
Uncovering commercial activity in informal cities.
Royal Society Open Science
, 9
(11)
, Article 211841. 10.1098/rsos.211841.
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Abstract
Knowledge of the spatial organisation of economic activity within a city is key to policy concerns. However, in developing cities with high levels of informality, this information is often unavailable. Recent progress in machine learning together with the availability of street imagery offers an affordable and easily automated solution. Here we propose an algorithm that can detect what we call 'visible firms' using street view imagery. Using Medell\'in, Colombia as a case study, we illustrate how this approach can be used to uncover previously unseen economic activity. Applying spatial analysis to our dataset we detect a polycentric structure with five distinct clusters located in both the established centre and peripheral areas. Comparing the density of visible and registered firms, we find that informal activity concentrates in poor but densely populated areas. Our findings highlight the large gap between what is captured in official data and the reality on the ground.
| Type: | Article |
|---|---|
| Title: | Uncovering commercial activity in informal cities |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1098/rsos.211841 |
| Publisher version: | https://doi.org/10.1098/rsos.211841 |
| Language: | English |
| Additional information: | © 2022 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited. |
| Keywords: | Labour informality, data for development, computer vision |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Centre for Advanced Spatial Analysis |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10158964 |
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