支持环境正义的地球观测数据:将未经许可的家禽经营与社会脆弱性指数联系起来。

IF 4.3 2区 医学 Q2 ENVIRONMENTAL SCIENCES
Geohealth Pub Date : 2024-12-18 DOI:10.1029/2024GH001179
Mirela G. Tulbure, Júlio Caineta, Brooke Cox, Stephen V. Stehman, Ayse Ercumen, Rebecca Witter, Ryan Emanuel, Dana E. Powell, Kemp Burdette, Sherri White-Williamson, Shea Tuberty
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引用次数: 0

摘要

集中式动物饲养操作(cafo)将大量未经处理的废物倾倒到附近的农田,在美国一些地区,集中式动物饲养操作对猪的环境健康造成了严重影响,并且靠近弱势社区。大多数记录CAFO影响的研究几乎完全依赖于从不完整的公共记录中已知的CAFO位置。家禽饲养场产生干废物,在没有联邦许可的情况下运作;因此,它们对环境正义(EJ)的影响是没有记录的。北卡罗来纳州(NC),一个主要的家禽生产商,已经看到家禽CAFO显著增加,特别是自1997年猪CAFO暂停以来。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CAFO位置进行了细化,在启发式调整后,将家禽CAFO密度的高估率降低了54%。我们在NC中删除了51.8%的错误分类特征,在美国删除了61.5%,显著提高了数据集的准确性。包括空间关联局部指标在内的空间分析显示,家禽cafo通常聚集在社会脆弱性指数(SVI)得分较高的人口普查区,表明存在潜在的EJ问题。值得注意的是,北卡州三分之一家禽CAFO密度高的人口普查区也有高SVI,主要是在东部农村地区。在美国南部和东南部也观察到了类似的模式。然而,并不是所有的CAFO高密度区域都具有较高的SVI,这表明CAFO的位置与社区脆弱性之间存在复杂的关系。本研究强调,迫切需要使用人工智能算法获得关于未经许可的家禽cafo的全面、高质量数据,以充分了解其对社区的影响,并准确地为EJ评估提供信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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

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

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.

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来源期刊
Geohealth
Geohealth Environmental Science-Pollution
CiteScore
6.80
自引率
6.20%
发文量
124
审稿时长
19 weeks
期刊介绍: GeoHealth will publish original research, reviews, policy discussions, and commentaries that cover the growing science on the interface among the Earth, atmospheric, oceans and environmental sciences, ecology, and the agricultural and health sciences. The journal will cover a wide variety of global and local issues including the impacts of climate change on human, agricultural, and ecosystem health, air and water pollution, environmental persistence of herbicides and pesticides, radiation and health, geomedicine, and the health effects of disasters. Many of these topics and others are of critical importance in the developing world and all require bringing together leading research across multiple disciplines.
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