CEU Credits: 0.5
Enhanced Satellite Data Brings Value to Agriculture
The benefits of hyperspectral imagery are becoming increasingly recognized within the agricultural sector. However, there is currently no singular product which can simultaneously provide high spatial, spectral, and temporal resolution. Moreover, existing sensors are complicated and expensive to manufacture, making them inaccessible to the general public. To address this problem, we have developed an approach to recover hyperspectral imagery from existing multispectral platforms such as those aboard the Landsat and Sentinel-2 satellite missions.
Joshua Billison, Research Assistant, University of Alberta – Multimedia Research Centre
Joshua Billson is an incoming MSc in Computing Science student at the University of Alberta and a recent graduate with a BSc in Computing Science. His work with the Multimedia Research Center, under the supervision of Dr. Irene Cheng, focuses on agricultural and environmental applications for satellite imagery. Currently, he is exploring methods to make hyperspectral imaging more accessible to both industry and research. His areas of interest include machine learning, computer vision, and remote sensing.
Karansinh Padhiar, Student, University of Alberta – Multimedia Research Centre
Karansinh Padhiar is an MSc Computing Science student at the University of Alberta, working with Dr. Irene Cheng at the Multimedia Research Centre. His research focuses on computer vision, machine learning, and pattern recognition. Currently, he is working with a team to improve satellite image resolution. Karan is a recipient of the Mitacs Globalink Graduate Fellowship. He graduated from India with a Bachelor of Technology in Computer Science and Engineering. His long-term goals include a career that gives him rich exposure to cutting-edge technologies and being a part of a team that works towards the improvement of society.