Evidence map›Paper›PMID 40128215›Full record

ArticleScientific data2025

An enhanced national-scale urban tree canopy cover dataset for the United States.

Lucila M Corro, Kenneth J Bagstad, Mehdi P Heris, Peter C Ibsen, Karen G Schleeweis, Jay E Diffendorfer, Austin Troy, Kevin Megown, Jarlath P M O'Neil-Dunne

Abstract read
PubMed Full text at PMC Publisher
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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

9 authors.

Lucila M CorroU.S. Geological Survey, Geosciences and Environmental Change Science Center, Denver, CO, 80225, USA. lcorro@usgs.gov.ORCID http://orcid.org/0000-0001-5718-6713
Kenneth J BagstadU.S. Geological Survey, Geosciences and Environmental Change Science Center, Denver, CO, 80225, USA.
Mehdi P HerisHunter College, Urban Policy & Planning, New York, NY, 10065, USA.
Peter C IbsenU.S. Geological Survey, Geosciences and Environmental Change Science Center, Denver, CO, 80225, USA.
Karen G SchleeweisForest Inventory and Analysis, U.S. Forest Service, Rocky Mountain Research Station, Riverdale, UT, 84405, USA.
Jay E DiffendorferU.S. Geological Survey, Geosciences and Environmental Change Science Center, Denver, CO, 80225, USA.
Austin TroyCollege of Architecture and Planning, University of Colorado Denver, University of Colorado Denver, Denver, CO, 80202, USA.
Kevin MegownGeospatial Technology and Applications Center, U.S. Forest Service, National Forest System, Salt Lake City, UT, 84138, USA.
Jarlath P M O'Neil-DunneSpatial Analysis Laboratory, Rubenstein School of Environment & Natural Resources, University of Vermont, Burlington, VT, 05405, USA.

Funding

Department of the Interior | U.S. Geological Survey (United States Geological Survey) N/A
6 · The paper itself

Abstract

Moderate-resolution (30-m) national map products have limited capacity to represent fine-scale, heterogeneous urban forms and processes, yet improvements from incorporating higher resolution predictor data remain rare. In this study, we applied random forest models to high-resolution land cover data for 71 U.S. urban areas, moderate-resolution National Land Cover Database (NLCD) Tree Canopy Cover (TCC), and additional explanatory climatic and structural data to develop an enhanced urban TCC dataset for U.S. urban areas. With a coefficient of determination (R

Indexed as

TreesCitiesDatasets as TopicUnited States

Identifiers

PMID40128215
PMCPMC11933301

What OpenQuestion holds

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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.