Evidence map›Paper›PMID 40659661›Full record

ArticleScientific data2025

Spatial Access of America: Multiple indicators of accessibility to opportunities.

Rajat Verma, Shagun Mittal, Satish V Ukkusuri

Abstract read
In one paragraph

Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Rajat VermaLyles School of Civil and Construction Engineering, Purdue University, West Lafayette, IN, 47907, USA.ORCID http://orcid.org/0000-0002-2273-8706
Shagun MittalLyles School of Civil and Construction Engineering, Purdue University, West Lafayette, IN, 47907, USA.ORCID http://orcid.org/0000-0003-2195-7197
Satish V UkkusuriLyles School of Civil and Construction Engineering, Purdue University, West Lafayette, IN, 47907, USA. sukkusur@purdue.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Spatial measures of accessibility are widely used in urban and transportation planning to understand the impact of the transportation system on influencing people's access to places, but publicly available large-scale datasets are rare and limited. This paper presents a highly parametric dataset containing values of spatial accessibility measured by combinations of multiple metrics, travel modes, types of opportunity (including jobs and amenities like schools, hospitals, and electric vehicle charging stations), and travel time thresholds. This includes both cumulative opportunities types of measures as well as competition metrics. A total of 600 accessibility values are computed for each zone at three administrative levels for the 50 most populous urban areas of the United States. Additionally, the dataset also includes the travel time matrix files for each of these urban areas by three travel modes - driving, walking, and bicycling - to facilitate self-validation. Further, comparisons with similar travel time and accessibility datasets show a high degree of similarity with our dataset.

Identifiers

PMID40659661
PMCPMC12260004

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.