Evidence map›Paper›PMID 41943827›Full record

ArticleJournal of city climate policy and economy2025

Harnessing Geospatial Data for Urban Climate Resilience: Insights from a Fine Scale Ambient Temperature Analysis in an Urban Heat Island.

Alina M McIntyre, M Patricia Fabian, Amruta Nori-Sarma, Marc Healy, Beverly Ge, Jeffrey A Geddes, Bianca Bowman, Patrick Kinney, Roseann Bongiovanni, Madeleine K Scammell

Abstract read
In one paragraph

Article in Journal of city climate policy and economy, 2025. 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

10 authors.

Alina M McIntyreDepartment of Environmental Health, Boston University School of Public Health, Boston, Massachusetts, United States.
M Patricia FabianDepartment of Environmental Health, Boston University School of Public Health, Boston, Massachusetts, United States.
Amruta Nori-SarmaDepartment of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States.
Marc HealyThe Nature Conservancy, Conshohocken, Pennsylvania, United States.
Beverly GeDepartment of Environmental Health, Boston University School of Public Health, Boston, Massachusetts, United States.
Jeffrey A GeddesDepartment of Earth and Environment, Boston University College of Arts and Sciences, Boston, Massachusetts, United States.
Bianca BowmanGreenRoots, Inc., Chelsea, Massachusetts, United States.
Patrick KinneyDepartment of Environmental Health, Boston University School of Public Health, Boston, Massachusetts, United States.
Roseann BongiovanniGreenRoots, Inc., Chelsea, Massachusetts, United States.
Madeleine K ScammellDepartment of Environmental Health, Boston University School of Public Health, Boston, Massachusetts, United States.

Funding

Environmental Epidemiology in Community SettingsT32ES014562 · NIEHS · BOSTON UNIVERSITY MEDICAL CAMPUS · PI Birgit Gunhild Claus Henn · 2006 to 2026
$7.7M
NIEHS NIH HHS T32 ES014562
6 · The paper itself

Abstract

Background: Cities face increasing risks from the urban heat island effect. Our ability to assess fine-scale differentials in urban heat is limited to the sparse spatial density of temperature monitoring. This study aims to assess ambient temperature variations at high resolution within an urban heat island in the northeastern United States, focusing on spatial disparities in heat exposure and implications for local climate planning and policy. Methods: The authors carried out a community-based research project in which 60-80 ambient temperature sensors were deployed in the city of Chelsea, Massachusetts, from 2015 to 2023 and compared to the National Weather Service temperature data from Logan International Airport. Data were analyzed for warm seasons, hot weeks, and heat waves. Warm season, yearly, and day-night ambient heat was analyzed and mapped using geospatial regression and kriging, incorporating natural/built environment variables. Results: Local sensors were up to 10°F (5.6°C) higher than National Weather Service readings during hot weeks with heat waves. Within Chelsea, spatial analyses identified approximately 5°F or 2.8° C (average) and 9°F or 5.0°C (maximum) higher temperatures in hot spots compared to cooler areas. Neighbourhoods with higher temperatures were in the more residential, urbanized areas of Chelsea. Day-night mapping further highlighted areas with prolonged heat exposure, crucial for health implications. Conclusion: This study highlights the value of local fine spatial ambient temperature data in urban climate planning. Geospatial modelling of outputs can assist policymakers in developing climate interventions. The research supports targeted efforts to mitigate urban heat, underscoring the importance of integrating environmental data with local insights for effective and equitable heat management strategies.

Indexed as

climate actionenvironmental justiceextreme heatfine-scale datageospatial

Identifiers

PMID41943827
PMCPMC13050554

What OpenQuestion holds

Textmetadata
LicenceTDM
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.