Mollie Kemp
Master’s student Mollie Kemp is developing multiple-scale validation tools to quantify forage mass and production in rangeland ecosystems using drone-based imagery.
“Forage mass is an essential component to calculate proper stocking rates for healthy rangelands,” Kemp said. “Traditionally, forage mass estimations are conducted by collecting a number of samples in the field, which can be labor- and time-intensive.”
Kemp said that remote sensing offers alternatives to field-based biomass sampling, but spatial and temporal resolution can limit their applicability at the ranch scale. Drone-based imagery provides new opportunities to develop scalable estimations at the ranch scale. This information can be used to validate broader-scale platforms, such as the Rangeland Analysis Platform (RAP).
“My goal is to use field data, drone-based imagery and RAP data to better inform forage estimations in the Southern Great Plains,” she said. “The objective of this research is to quantify forage mass and forage production for rangelands at a fine scale and at an operational scale.”
Kemp collected RGB drone imagery with a 42-megapixel camera to generate a canopy height model at a resolution of 7cm by 7cm across two Texas locations. Field vegetation samples for forage mass estimates were also taken. Forage mass estimates were calculated using both methods, and their relationships were analyzed using linear regression.
Kemp said preliminary results indicate that on-the-ground forage biomass can explain up to 86% of the variability in drone-estimated volume. Further analysis and image classification will work to exclude woody cover and calculate adjusted forage production.
“Ultimately, we aim to establish a relationship between drone-based imagery estimates and RAP values,” she said. “Our results will provide information on forage mass and production at an operational scale using drone-based imagery.”
