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支持环境正义的地球观测数据:将未经许可的家禽养殖场与社会脆弱性指数相联系

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

作者信息

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

机构信息

Center for Geospatial Analytics North Carolina State University Raleigh NC USA.

College of Environmental Science and Forestry State University of New York Syracuse NY USA.

出版信息

Geohealth. 2024 Dec 18;8(12):e2024GH001179. doi: 10.1029/2024GH001179. eCollection 2024 Dec.

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.

摘要

集中式动物饲养场(CAFOs)向附近农田施用大量未经处理的废物,在美国一些地区,养猪集中式动物饲养场对环境健康的严重影响以及其与弱势社区的临近关系已有充分记录。大多数记录集中式动物饲养场影响的研究几乎完全依赖于从不完整公共记录中已知的集中式动物饲养场位置。家禽集中式动物饲养场产生干废物且运营无需联邦许可;因此,它们对环境正义(EJ)的影响尚无记录。北卡罗来纳州(NC)是主要的家禽生产州,自1997年暂停养猪集中式动物饲养场建设以来,家禽集中式动物饲养场数量显著增加。本研究利用文献启发法,对基于地球观测(EO)数据和深度学习得出的家禽集中式动物饲养场位置进行了优化,经启发式调整后,将家禽集中式动物饲养场密度的高估率降低了54%。我们消除了北卡罗来纳州51.8%的误分类特征以及全美61.5%的误分类特征,显著提高了数据集的准确性。空间分析,包括空间自相关局部指标分析,表明家禽集中式动物饲养场往往聚集在社会脆弱性指数(SVI)得分较高的人口普查区,这表明存在潜在的环境正义问题。值得注意的是,北卡罗来纳州家禽集中式动物饲养场密度高的人口普查区中有三分之一的SVI也很高,主要集中在东部农村地区。在美国南部和东南部也观察到了类似模式。然而,并非所有高密度集中式动物饲养场区域都与高SVI相对应,这表明集中式动物饲养场位置与社区脆弱性之间存在复杂关系。本研究强调了迫切需要利用人工智能算法获取关于未经许可的家禽集中式动物饲养场的全面、高质量数据,以充分了解它们对社区的影响,并为环境正义评估提供准确信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c8b/11652945/256f7ff68ba9/GH2-8-e2024GH001179-g001.jpg

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