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Advancing Community Driven Environmental Health Equity Research with Indigenous Communities Using Geospatial Big & Small Data
Abstract:
<p>The complex spatio-temporal relationships between the environment, society, and health/health disparities remain an interdisciplinary research challenge. More than 160,000 abandoned hard rock mines throughout the western U.S. Contamination from these industrial sites has created a legacy of chronic exposure to metal mixtures in neighboring Native American communities. To advance the research to understand better and address environmental health disparities in these communities, challenges, and gaps exist, including but not limited to environmental exposure risk monitoring and assessment from the environment (e.g. water, air, soil, and plants), to livestock animals as traditional food sources, to humans. This paper applies geospatial thinking to address community-identified needs that center on understanding environmental exposure and health impacts among Native American communities leveraging geospatial big and small data. Several projects are discussed here: (1) a geospatial model of potential environmental exposure to abandoned uranium mines that considers wind pattern, topography, vegetation, proximity to mine sites, downslope drainage of mine sites, and groundwater contamination; (2) a spatiotemporal model for individual livestock exposure potential assessment based on GPS data using fuzzy logic, machine learning methods based on community input; and (3) a study to improve infrastructure for Native American communities through installation meteorological stations and PM monitors for air quality monitoring and air dispersion modeling. </p>
Keywords: Community-based research; Geospatial Big data; Native Americans; Environmental Health
Authors:
Yan Lin, University of New Mexico; Submitting Author / Primary Presenter
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Advancing Community Driven Environmental Health Equity Research with Indigenous Communities Using Geospatial Big & Small Data
Category
In-Person Paper Abstract