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Fusing multiple data sources to obtain temporally and spatially accurate Solar-Induced Fluorescence (SIF) Product

To begin meaningful analysis of the role and efficiency of photosynthesis under a multitude of conditions, accurate and timely data must first be acquired. By measuring the SIF product, we can directly evaluate the carbon flux of a geographic footprint. We will be using SIF data taken from the GOME-2 and OCO-2 satellites in orbit. However each have opposing weaknesses and strengths in resolution and frequency, leading to less-than-desired coverage and accuracy. The goal of this research will be to establish a procedure to fuse data from both satellites by down-scaling via a mathematical approach, utilizing machine learning and computer vision, or a combination of both.

Author: 
Nishant Maniam
School: 
University of Illinois at Urbana-Champaign
Department: 
Computer Science
Research Advisor: 
Dr. Kaiyu Guan
Department of Research Advisor: 
Natural Resources & Environmental Sciences
Year of Publication: 
2017