Harrison Smith
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
ORISE Postdoctoral Research Fellow, USDA Agricultural Research Service
Also affiliated: Agricultural Research Service (2022); Dale Bumpers Small Farms Research Center (2022); University of Missouri (2023)
Formerly Arkansas Graduate Research Fellow, University of Arkansas through 2026; now ORISE Postdoctoral Research Fellow, USDA Agricultural Research Service.
Research Areas
Biomedical Subjects
Links
Biography and Research Information
OverviewAI-generated summary
Harrison Smith's research focuses on the application of machine learning and geospatial analysis to agricultural and environmental challenges. His work investigates the identification of critical soil values for crop production, utilizing boundary line analysis and predictive models. Smith has also explored the use of ground-penetrating radar and apparent electrical conductivity for soil characterization and delineating field variations within agroforestry and silvopastoral systems. His research extends to evaluating soil suitability for optimized crop production on U.S. tribal lands and assessing environmental drivers of U.S. maize and soybean yield. Furthermore, Smith has studied vegetative recovery and land cover transformation post-reclamation at a superfund site using remote sensing. He has published 16 papers, with an h-index of 5 and 66 citations, and collaborates with several researchers at the University of Arkansas at Fayetteville.
Metrics
- h-index: 5
- Publications: 16
- Citations: 66
Positions
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ORISE Postdoctoral Research Fellow 2026–presentUSDA Agricultural Research Service Poultry Production and Product Safety Research Unit Fayetteville Arkansas ORCID
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Doctoral Academy fellow publications 2015–2026University of Arkansas at Fayetteville Institution web page
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Graduate Research Fellow 2021–2026University of Arkansas at Fayetteville Environmental Dynamics Program ORCID
Selected Publications
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Harvesting insights: interpretable machine learning to understand environmental drivers of U.S. maize and soybean yield (2026)
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Policy-Driven Transfer Learning in Resource-Limited Animal Monitoring (2025)
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Denoised Diffusion for Object-Focused Image Augmentation (2025)
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Predicting spatiotemporal patterns of productivity and grazing from multispectral data using neural network analysis based on system complexity (2024)
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Remote sensing reveals trends in vegetative recovery and land cover transformation post-reclamation at tar creek superfund site (2024)
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Relationships among apparent electrical conductivity and plant and terrain data in an agroforestry system in the Ozark Highlands (2023)
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Boundary line analysis and machine learning models to identify critical soil values for major crops in Guatemala (2023)
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Relationships Among Apparent Electrical Conductivity and Plant and Terrain Data in an Agroforestry System in the Ozark Highlands (2023)
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Applications and Analytical Methods of Ground Penetrating Radar for Soil Characterization in a Silvopastoral System (2022)
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Using Apparent Electrical Conductivity to Delineate Field Variation in an Agroforestry System in the Ozark Highlands (2022)
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GIS-Based Evaluation of Soil Suitability for Optimized Production on U.S. Tribal Lands (2022)
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Human impacts on water systems: Biological assessment of water quality in the Bosque Protector Río Guajalito (BPRG) using aquatic macroinvertebrates (2015)School for International Training Digital Collections (School for International Training) OpenAlex
Collaboration Network
Top Collaborators
- Applications and Analytical Methods of Ground Penetrating Radar for Soil Characterization in a Silvopastoral System
- Using Apparent Electrical Conductivity to Delineate Field Variation in an Agroforestry System in the Ozark Highlands
- Boundary line analysis and machine learning models to identify critical soil values for major crops in Guatemala
- Relationships among apparent electrical conductivity and plant and terrain data in an agroforestry system in the Ozark Highlands
- GIS-Based Evaluation of Soil Suitability for Optimized Production on U.S. Tribal Lands
Showing 5 of 11 shared publications
- Applications and Analytical Methods of Ground Penetrating Radar for Soil Characterization in a Silvopastoral System
- Using Apparent Electrical Conductivity to Delineate Field Variation in an Agroforestry System in the Ozark Highlands
- Boundary line analysis and machine learning models to identify critical soil values for major crops in Guatemala
- Relationships among apparent electrical conductivity and plant and terrain data in an agroforestry system in the Ozark Highlands
- GIS-Based Evaluation of Soil Suitability for Optimized Production on U.S. Tribal Lands
Showing 5 of 11 shared publications
- Using Apparent Electrical Conductivity to Delineate Field Variation in an Agroforestry System in the Ozark Highlands
- Relationships among apparent electrical conductivity and plant and terrain data in an agroforestry system in the Ozark Highlands
- Relationships Among Apparent Electrical Conductivity and Plant and Terrain Data in an Agroforestry System in the Ozark Highlands
- Using Apparent Electrical Conductivity to Delineate Field Variation in an Agroforestry System in the Ozark Highlands
- Relationships among apparent electrical conductivity and plant and terrain data in an agroforestry system in the Ozark Highlands
- Relationships Among Apparent Electrical Conductivity and Plant and Terrain Data in an Agroforestry System in the Ozark Highlands
- Using Apparent Electrical Conductivity to Delineate Field Variation in an Agroforestry System in the Ozark Highlands
- Relationships among apparent electrical conductivity and plant and terrain data in an agroforestry system in the Ozark Highlands
- Relationships Among Apparent Electrical Conductivity and Plant and Terrain Data in an Agroforestry System in the Ozark Highlands
- Relationships among apparent electrical conductivity and plant and terrain data in an agroforestry system in the Ozark Highlands
- Relationships Among Apparent Electrical Conductivity and Plant and Terrain Data in an Agroforestry System in the Ozark Highlands
- Boundary line analysis and machine learning models to identify critical soil values for major crops in Guatemala
- Remote sensing reveals trends in vegetative recovery and land cover transformation post-reclamation at tar creek superfund site
- Relationships among apparent electrical conductivity and plant and terrain data in an agroforestry system in the Ozark Highlands
- Predicting spatiotemporal patterns of productivity and grazing from multispectral data using neural network analysis based on system complexity
- Policy-Driven Transfer Learning in Resource-Limited Animal Monitoring
- Denoised Diffusion for Object-Focused Image Augmentation
- Policy-Driven Transfer Learning in Resource-Limited Animal Monitoring
- Denoised Diffusion for Object-Focused Image Augmentation
- Policy-Driven Transfer Learning in Resource-Limited Animal Monitoring
- Denoised Diffusion for Object-Focused Image Augmentation
- Policy-Driven Transfer Learning in Resource-Limited Animal Monitoring
- Denoised Diffusion for Object-Focused Image Augmentation
- Boundary line analysis and machine learning models to identify critical soil values for major crops in Guatemala
- Boundary line analysis and machine learning models to identify critical soil values for major crops in Guatemala
- Boundary line analysis and machine learning models to identify critical soil values for major crops in Guatemala
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