V
V. Steven Green Data-verified
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Professor Soil and Water Conservation
faculty
14 h-index
22 pubs
1,602 cited
Research Areas
Links
Biography and Research Information
OverviewAI-generated summary
V. Steven Green is a Professor of Soil and Water Conservation at Arkansas State University. His research focuses on the application of remote sensing technologies in agriculture and conservation. Recent publications investigate the use of unmanned aerial vehicle imagery and deep learning for detecting intra-field variation in rice yield, as well as determining nitrogen deficiencies in maize using various remote sensing indices. Green has also examined thematic trends in remote sensing for conservation agriculture and developed methodological frameworks for cover crop identification using remote sensing data. His work further explores the short-term effects of cover crops and tillage management on soil physical properties. Green's scholarship metrics include an h-index of 14, with 23 total publications and 1,587 total citations.
Metrics
- h-index: 14
- Publications: 22
- Citations: 1,602
Selected Publications
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Satellite Remote Sensing Reveals Voluntary Cover-Crop Adoption and Crop-Rotation Hotspots in the Mississippi Alluvial Plain (2025)
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Analysis of Competency Assessments Used in an Upper-Level Soil Fertility Course (2025)
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Short-Term Effects of Cover Crops and Tillage Management on Soil Physical Properties on Silt Loam Soil (2024)
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Winter-time cover crop identification: A remote sensing-based methodological framework for new and rapid data generation (2023)
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An examination of thematic research, development, and trends in remote sensing applied to conservation agriculture (2023)
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Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learning (2022)
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Determining nitrogen deficiencies for maize using various remote sensing indices (2022)
Collaboration Network
Top Collaborators
Aaron M. Shew
University of Arkansas at Fayetteville
4 shared publications
In database
- Determining nitrogen deficiencies for maize using various remote sensing indices
- An examination of thematic research, development, and trends in remote sensing applied to conservation agriculture
- Winter-time cover crop identification: A remote sensing-based methodological framework for new and rapid data generation
- Satellite Remote Sensing Reveals Voluntary Cover-Crop Adoption and Crop-Rotation Hotspots in the Mississippi Alluvial Plain
Zobaer Ahmed
University of Arkansas at Fayetteville
3 shared publications
In database
- An examination of thematic research, development, and trends in remote sensing applied to conservation agriculture
- Winter-time cover crop identification: A remote sensing-based methodological framework for new and rapid data generation
- Satellite Remote Sensing Reveals Voluntary Cover-Crop Adoption and Crop-Rotation Hotspots in the Mississippi Alluvial Plain
Lawton Lanier Nalley
University of Arkansas at Fayetteville
3 shared publications
In database
- An examination of thematic research, development, and trends in remote sensing applied to conservation agriculture
- Winter-time cover crop identification: A remote sensing-based methodological framework for new and rapid data generation
- Satellite Remote Sensing Reveals Voluntary Cover-Crop Adoption and Crop-Rotation Hotspots in the Mississippi Alluvial Plain
Michael P. Popp
University of Arkansas at Fayetteville
3 shared publications
In database
- An examination of thematic research, development, and trends in remote sensing applied to conservation agriculture
- Winter-time cover crop identification: A remote sensing-based methodological framework for new and rapid data generation
- Satellite Remote Sensing Reveals Voluntary Cover-Crop Adoption and Crop-Rotation Hotspots in the Mississippi Alluvial Plain
Kristofor R. Brye
University of Arkansas at Fayetteville
3 shared publications
In database
- An examination of thematic research, development, and trends in remote sensing applied to conservation agriculture
- Winter-time cover crop identification: A remote sensing-based methodological framework for new and rapid data generation
- Satellite Remote Sensing Reveals Voluntary Cover-Crop Adoption and Crop-Rotation Hotspots in the Mississippi Alluvial Plain
Brayden W. Burns
Arkansas State University
2 shared publications
In database
- Determining nitrogen deficiencies for maize using various remote sensing indices
- Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learning
Ahmed A. Hashem
University of Arkansas System
2 shared publications
In database
- Determining nitrogen deficiencies for maize using various remote sensing indices
- Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learning
Lawson Connor
University of Arkansas at Fayetteville
2 shared publications
In database
- Winter-time cover crop identification: A remote sensing-based methodological framework for new and rapid data generation
- Satellite Remote Sensing Reveals Voluntary Cover-Crop Adoption and Crop-Rotation Hotspots in the Mississippi Alluvial Plain
J.H. Massey
United States Department of Agriculture (US)
1 shared publication
- Determining nitrogen deficiencies for maize using various remote sensing indices
Maria Arlene Adviento‐Borbe
United States Department of Agriculture (US)
1 shared publication
- Determining nitrogen deficiencies for maize using various remote sensing indices
Mohamed Milad
Arkansas State University
1 shared publication
In database
- Determining nitrogen deficiencies for maize using various remote sensing indices
Emily S. Bellis
Arkansas State University
1 shared publication
In database
- Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learning
Jason Causey
Arkansas State University
1 shared publication
In database
- Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learning
Benjamin R. K. Runkle
United States Department of Agriculture
1 shared publication
In database
- Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learning
Beatriz Moreno‐García
United States Department of Agriculture
1 shared publication
In database
- Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learning
Similar Researchers
Based on overlapping research topics
Harrison Smith
University of Arkansas at Fayetteville
Remote Sensing in Agriculture
Agronomic Practices and Intercropping Systems
Soil and Water Nutrient Dynamics
Gregory Lee Pate
Arkansas Agricultural Experiment Station
Remote Sensing in Agriculture
Agronomic Practices and Intercropping Systems
Soil and Water Nutrient Dynamics
D. M O'Brien
Arkansas Agricultural Experiment Station
Remote Sensing in Agriculture
Agronomic Practices and Intercropping Systems
Soil and Water Nutrient Dynamics
E. A. Adee
Arkansas Agricultural Experiment Station
Remote Sensing in Agriculture
Agronomic Practices and Intercropping Systems
Soil and Water Nutrient Dynamics
C. A. Redmond
Arkansas Agricultural Experiment Station
Remote Sensing in Agriculture
Agronomic Practices and Intercropping Systems
Soil and Water Nutrient Dynamics
E. Adee
Arkansas Agricultural Experiment Station
Remote Sensing in Agriculture
Agronomic Practices and Intercropping Systems
Soil and Water Nutrient Dynamics