Evidence map›Paper›PMID 41837205›Full record

ArticleEPJ data science2026

Not your mean green: beyond averages in mapping socio-spatial inequities in urban greenery for smart cities.

Jenny Martinez, Javier Argota Sánchez-Vaquerizo, Sachit Mahajan

Abstract read
In one paragraph

Article in EPJ data science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Jenny Martinez *Institute of Sustainable Development (INE), School of Engineering (SoE), Zurich University of Applied Sciences (ZHAW), Technoparkstrasse 2, Winterthur, 8400 Switzerland.
Javier Argota Sánchez-VaquerizoComputational Social Science, ETH Zurich, Stampfenbachstrasse 48, Zurich, 8092 Switzerland.
Sachit Mahajan *Computational Social Science, ETH Zurich, Stampfenbachstrasse 48, Zurich, 8092 Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As data-driven "smart city" agendas expand across Latin America, most urban performance metrics remain focused on infrastructure, connectivity, and aggregate efficiency, often neglecting who truly benefits. Urban greenery, a vital determinant of health and climate resilience, is one such blind spot. While some frameworks now consider "green space," they do so at a coarse, citywide scale, overlooking how access is distributed across neighborhoods and social groups. This obscures critical equity gaps, particularly in cities marked by deep socio-spatial segregation. In this study, we develop a fully reproducible geospatial pipeline that integrates high-resolution canopy height models, public park data, gridded population estimates, and socioeconomic strata to assess how greenery is distributed, not just how much exists. Applied to Bogotá and Medellín, the method reveals stark disparities: population-weighted canopy coverage rises significantly between the lowest and highest strata, while access to public parks also shows measurable inequality, especially in high-density, underserved neighborhoods. These inequities persist despite progressive greening policies, revealing the limits of optimization when legacy segregation is ignored. Our open-source pipeline enables finer-grained, justice-oriented audits that go beyond averages to identify where greenery and its benefits are most lacking. By enabling fine-grained equity assessments, this approach underscores the importance of greenery distribution, not just quantity, as a critical indicator for inclusive and equitable smart cities.

Indexed as

Canopy heightColombiaEnvironmental justiceSmart citiesSpatial inequalityUrban greenery

Identifiers

PMID41837205
PMCPMC12979267

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.