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Snider, J.L
Barlage, M
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Authors
Mahoney, W
Barlage, M
Gochis, D
Chen, F
Pokhrel, A
Virk, S
Snider, J.L
Vellidis, G
Parkash, V
Topics
Spatial Variability in Crop, Soil and Natural Resources
Applications of Unmanned Aerial Systems
Type
Oral
Year
2014
2022
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1. Developing A High-Resolution Land Data Assimilation And Forecast System For Agricultural Decision Support

Technological advances in weather and climate forecasting and land surface and hydrology modeling have led to an increased ability to predict soil temperature, and soil moisture, near-surface weather elements. These variables are critical building blocks to the development of high-level agriculture-specific models such as pest models and crop yield models. The National Center for Atmospheric Research (NCAR) has developed a high-resolution agriculture-oriented land-data assimilation... W. Mahoney, M. Barlage, D. Gochis, F. Chen

2. Potential of UAS Multispectral Imagery for Predicting Yield Determining Physiological Parameters of Cotton

The use of unmanned aerial systems (UAS) in precision agriculture has increased rapidly due to the availability of reliable, low-cost, and high-resolution sensors as well as advanced image processing software. Lint yield in cotton is the product of three physiological parameters: photosynthetically active radiation intercepted by canopy (IPAR), the efficiency of converting intercepted active radiation to biomass (RUE), and the ratio of economic yield to total dry matter (HI). The relationships... A. Pokhrel, S. Virk, J.L. Snider, G. Vellidis, V. Parkash