Evidence map›Paper›PMID 40301363›Full record

ArticleScientific data2025

Biennial sub-meter tree coverage dataset of Orlando (2013-2021).

Danlu Cai, Leiqiu Hu, Janak Parajuli

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. 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.

Danlu CaiDepartment of Atmospheric and Earth Science, University of Alabama in Huntsville, Huntsville, AL, 35899, USA.ORCID http://orcid.org/0000-0002-8986-1354
Leiqiu HuDepartment of Atmospheric and Earth Science, University of Alabama in Huntsville, Huntsville, AL, 35899, USA. leiqiu.hu@uah.edu.ORCID http://orcid.org/0000-0002-1867-2521
Janak ParajuliDepartment of Atmospheric and Earth Science, University of Alabama in Huntsville, Huntsville, AL, 35899, USA.ORCID http://orcid.org/0000-0003-2343-113X

Funding

National Aeronautics and Space Administration (NASA) 80NSSC21K0430National Aeronautics and Space Administration (NASA) 80NSSC23K0306
6 · The paper itself

Abstract

Rapid urban development often comes at the cost of significant vegetation loss, and the loss of urban trees is a particularly concerning issue. Many cities have recognized the crucial role of tree canopy cover in addressing a range of pressing environmental challenges, and have set goals in their development plans. However, the lack of resources for monitoring its spatiotemporal changes directly undermines efforts of cities to balance urban growth with environmental sustainability. We developed high-resolution biennial tree canopy maps (2013-2021) for the Orlando metropolitan area using National Agricultural Imagery Program (NAIP) orthoimagery. Our approach addresses challenges such as sensor inconsistencies, shadows, variable observation times, and environmental factors. Extensive ground-truth validation demonstrates 78%-89% accuracy in tree detection, outperforming existing products. This dataset provides the crucial link between planning and action, and supports urban forest management and has broader applications in urban planning, environmental and public health monitoring, and education programs.

Identifiers

PMID40301363
PMCPMC12041544

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.