Hail Damage Classification in Barley using Drone Imagery
This research performed for Agriculture Financial Services Corporation (AFSC) was a proof of concept exploring whether various formats of imagery captured by drone mounted cameras and LiDAR equipment could be used to classify simulated hail damaged areas within a barley crop. Various patterns and levels of damage were applied to the barley crop using a hail simulator with imagery collected using drones immediately after the hail simulation and 5 days later. Supervised and unsupervised classification and various GIS overlay methods were used in an attempt to automatically (or semi-automatically) determine damaged areas in the field.
CEU Credits: 0.5
Bio: George Gaeke, Olds College
George Gaeke is a Land Use Planning and Geographic Information Systems (GIS) instructor at Olds College with the Werklund School of Agriculture Technology. He has been teaching there since the fall of 2013. Prior to that, he was a surveying, civil engineering and GIS technologies consultant and instructor. George is currently involved in research at the College using UAV’s and multiple types of sensors for agriculture remote sensing applications.
Bio: Bob Hoffos, Olds College
Bob Hoffas is a GIS and technology instructor with the Werklund School of Agriculture Technology. Bob is passionate about mapping technologies and over the last 20 years has taught hundreds of Land and Agricultural students how to navigate and collect data with GPS, create maps, analyze spatial information and perform statistical analysis. Bob is currently involved in research at the College using UAV’s and multiple types of sensors for agriculture remote sensing applications.