Evidence map›Paper›PMID 39697399›Full record

ArticleGeoHealth2024

Earth Observation Data to Support Environmental Justice: Linking Non-Permitted Poultry Operations to Social Vulnerability Indices.

Mirela G Tulbure, Júlio Caineta, Brooke Cox, Stephen V Stehman, Ayse Ercumen, Rebecca Witter, Ryan Emanuel, Dana E Powell, Kemp Burdette, Sherri White-Williamson and 1 more

Abstract read
In one paragraph

Article in GeoHealth, 2024. 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

11 authors.

Mirela G TulbureCenter for Geospatial Analytics North Carolina State University Raleigh NC USA.ORCID https://orcid.org/0000-0003-1456-183X
Júlio CainetaCenter for Geospatial Analytics North Carolina State University Raleigh NC USA.
Brooke CoxCenter for Geospatial Analytics North Carolina State University Raleigh NC USA.
Stephen V StehmanCollege of Environmental Science and Forestry State University of New York Syracuse NY USA.
Ayse ErcumenDepartment of Forestry and Environmental Resources North Carolina State University Raleigh NC USA.
Rebecca WitterDepartment of Sustainable Development Appalachian State University Boone NC USA.
Ryan EmanuelNicholas School of the Environment Duke University Durham NC USA.ORCID https://orcid.org/0000-0002-2166-1698
Dana E PowellGraduate Institute of Medical Humanities Taipei Medical University Taipei Taiwan.
Kemp BurdetteCape Fear Riverkeeper Wilmington NC USA.
Sherri White-WilliamsonEnvironmental Justice Community Action Network Clinton NC USA.
Shea TubertyDepartment of Biology Appalachian State University Boone NC USA.

Funding

Translational Research Support CoreP30ES025128 · NIEHS · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI Sue Fenton · 2015 to 2026
$18.3M
NIEHS NIH HHS P30 ES025128
6 · The paper itself

Abstract

Concentrated Animal Feeding Operations (CAFOs) apply massive amounts of untreated waste to nearby farmlands, with severe environmental health impacts of swine CAFOs and proximity to disadvantaged communities well documented in some US regions. Most studies documenting the impacts of CAFOs rely almost exclusively on CAFO locations known from incomplete public records. Poultry CAFOs generate dry waste and operate without federal permits; thus, their environmental justice (EJ) impacts are undocumented. North Carolina (NC), a leading poultry producer, has seen a significant increase in poultry CAFOs, particularly since the 1997 swine CAFO moratorium. Using literature-derived heuristics, this study refined the locations of poultry CAFOs derived based on Earth Observation (EO) data and deep learning, reducing the overestimation of poultry CAFO density by 54% after heuristic adjustments. We removed 51.8% of misclassified features in NC and 61.5% across the US, significantly improving data set accuracy. Spatial analysis, including Local Indicators of Spatial Association, revealed that poultry CAFOs often cluster in census tracts with high Social Vulnerability Index (SVI) scores, indicating potential EJ issues. Notably, one-third of NC's census tracts with high poultry CAFO density also have high SVI, primarily in rural eastern regions. Similar patterns were observed in the South and Southeast of the US. However, not all high-density CAFO areas correspond with high SVI, suggesting a complex relationship between CAFO locations and community vulnerabilities. This study highlights the critical need for comprehensive, high-quality data on unpermitted poultry CAFOs derived using AI algorithms to fully understand their impacts on communities and accurately inform EJ evaluations.

Indexed as

Earth observation dataenvironmental justiceLISA clusterslocalized indicator of spatial analysismachine learning‐ready data setMoran's Ipoultry CAFOssocial vulnerability

Identifiers

PMID39697399
PMCPMC11652945

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.