Harrison Smith Source Confirmed

Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.

Researcher

University of Arkansas at Fayetteville

faculty

4 h-index 13 pubs 46 cited

Research Areas

Remote Sensing in Agriculture Soil and Water Nutrient Dynamics Agronomic Practices and Intercropping Systems Geological and Geochemical Analysis Ecology and Vegetation Dynamics Studies Natural Language Processing Techniques Advanced Neural Network Applications

Links

ORCID

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OverviewAI-generated summary

Harrison Smith's research focuses on the application of geospatial technologies and data analysis to understand and optimize agricultural and environmental systems. His work investigates the use of techniques such as apparent electrical conductivity, ground penetrating radar, and geographic information systems (GIS) to characterize soil properties and delineate field variations. Smith has explored the relationships between these measurements and crop or vegetative data within agroforestry and silvopastoral systems, particularly in regions like the Ozark Highlands and Guatemala.

His research also extends to evaluating soil and crop suitability for optimized production on U.S. Tribal Lands. Furthermore, Smith has utilized remote sensing to analyze land cover transformation and vegetative recovery following reclamation efforts at superfund sites. He also employs machine learning models to interpret environmental drivers influencing crop yields, such as maize and soybean production.

Metrics

  • h-index: 4
  • Publications: 13
  • Citations: 46

Selected Publications

  • Harvesting insights: interpretable machine learning to understand environmental drivers of U.S. maize and soybean yield (2026) DOI
  • Predicting spatiotemporal patterns of productivity and grazing from multispectral data using neural network analysis based on system complexity (2024) DOI
  • Remote sensing reveals trends in vegetative recovery and land cover transformation post-reclamation at tar creek superfund site (2024) DOI
  • Relationships among apparent electrical conductivity and plant and terrain data in an agroforestry system in the Ozark Highlands (2023) DOI
  • Boundary line analysis and machine learning models to identify critical soil values for major crops in Guatemala (2023) DOI
  • Relationships Among Apparent Electrical Conductivity and Plant and Terrain Data in an Agroforestry System in the Ozark Highlands (2023) DOI
  • Applications and Analytical Methods of Ground Penetrating Radar for Soil Characterization in a Silvopastoral System (2022) DOI
  • Using Apparent Electrical Conductivity to Delineate Field Variation in an Agroforestry System in the Ozark Highlands (2022) DOI
  • GIS-Based Evaluation of Soil Suitability for Optimized Production on U.S. Tribal Lands (2022) DOI

Collaborators

Researchers in the database who share publications

Amanda J. Ashworth University of Arkansas at Fayetteville 3 shared publications Aurelie M. Poncet University of Arkansas at Fayetteville 3 shared publications Shane Ylagan University of Arkansas at Fayetteville 3 shared publications Lawton Lanier Nalley University of Arkansas at Fayetteville 2 shared publications Kristofor R. Brye University of Arkansas at Fayetteville 2 shared publications D. Philipp University of Arkansas at Fayetteville 2 shared publications Jason A. Tullis University of Arkansas at Fayetteville 1 shared publication

Similar Researchers

Based on overlapping research topics

Rebecca I. Cooper Arkansas State University
Remote Sensing in Agriculture Soil and Water Nutrient Dynamics Agronomic Practices and Intercropping Systems
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V. Steven Green Arkansas State University
Remote Sensing in Agriculture Soil and Water Nutrient Dynamics Agronomic Practices and Intercropping Systems
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D. Philipp University of Arkansas at Fayetteville
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Kristofor R. Brye University of Arkansas at Fayetteville
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Matt Fryer University of Arkansas at Fayetteville
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Good match 3 shared topics
Beatriz Moreno‐García University of Arkansas at Fayetteville
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Good match 4 shared topics