Preliminary spatial model for pasture yield estimates in Vermont using satellite imagery
Abstract
Pasture yield estimates are vital for making informed management decisions regarding grass-fed livestock. Specifically, rotationally grazed livestock operations can benefit from knowing where the highest yields of forage biomass on their farm are. Currently, popular methods for pasture estimation can be cost and time prohibitive for researchers and farmers and often ignore within-field spatial variation. Satellite forage estimates are increasing in popularity, but the calibration of these methods can also ignore in-field variability. GPS-paired ground-truth data analyzed with interpolation methods and spatial regression may be able to better calibrate satellite estimates. Here I present a preliminary spatial model which uses these techniques on data collected from Vermont pastures.
Primary Faculty Mentor Name
Brittany Mosher
Status
Graduate
Student College
Rubenstein School of Environmental and Natural Resources
Program/Major
Environmental Studies
Primary Research Category
Life Sciences
Preliminary spatial model for pasture yield estimates in Vermont using satellite imagery
Pasture yield estimates are vital for making informed management decisions regarding grass-fed livestock. Specifically, rotationally grazed livestock operations can benefit from knowing where the highest yields of forage biomass on their farm are. Currently, popular methods for pasture estimation can be cost and time prohibitive for researchers and farmers and often ignore within-field spatial variation. Satellite forage estimates are increasing in popularity, but the calibration of these methods can also ignore in-field variability. GPS-paired ground-truth data analyzed with interpolation methods and spatial regression may be able to better calibrate satellite estimates. Here I present a preliminary spatial model which uses these techniques on data collected from Vermont pastures.
