Evidence map›Paper›PMID 37719470›Full record

ArticleRemote sensing2022

What you see is what you breathe? Estimating air pollution spatial variation using street level imagery.

Esra Suel, Meytar Sorek-Hamer, Izabela Moise, Michael von Pohle, Adwait Sahasrabhojanee, Ata Akbari Asanjan, Raphael E Arku, Abosede S Alli, Benjamin Barratt, Sierra N Clark and 7 more

Abstract read
In one paragraph

Article in Remote sensing, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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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

17 authors.

Esra SuelImperial College London.
Meytar Sorek-HamerUniversities Space Research Association (USRA).
Izabela MoiseImperial College London.
Michael von PohleUniversities Space Research Association (USRA).
Adwait SahasrabhojaneeUniversities Space Research Association (USRA).
Ata Akbari AsanjanUniversities Space Research Association (USRA).
Raphael E ArkuUniversity of Massachusetts Amherst.
Abosede S AlliUniversity of Massachusetts Amherst.
Benjamin BarrattImperial College London.
Sierra N ClarkImperial College London.
Ariane MiddelArizona State University.
Emily DeardorffUniversities Space Research Association (USRA).
Violet LingenfelterUniversities Space Research Association (USRA).
Nikunj OzaNASA Ames Research Center.
Nishant YadavUniversities Space Research Association (USRA).
Majid EzzatiImperial College London.
Michael BrauerUniversity of British Columbia.

Funding

Medical Research Council MR/S003983/1Medical Research Council MR/S019669/1Wellcome Trust 209376Wellcome Trust 209376/Z/17/Z
6 · The paper itself

Abstract

High spatial resolution information on urban air pollution levels is unavailable in many areas globally, partially due to high input data needs of existing estimation approaches. Here we introduce a computer vision method to estimate annual means for air pollution levels from street level images. We used annual mean estimates of NO

Indexed as

air pollutionComputer visiondata sciencedeep learningstreet imagestransferabilityurban pollution

Identifiers

PMID37719470
PMCPMC7615101

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.