ForEM Ph.D. Oral Examination Odysseas Vlachopoulos-FR

Event Details:

CROP FIELD MONITORING AND DAMAGE ASSESSMENT WITH UNMANNED AIRCRAFT SYSTEMS AND MACHINE LEARNING

The purpose of this dissertation is to examine and develop novel Machine Learning (ML) pipelines for crop field monitoring and damage assessment using Unmanned Aircraft Systems (UAS) equipped with a multispectral MicaSense RedEdge optical sensor for precision agriculture and insurance purposes. The crop fields were prepared for or planted with barley, corn, potato, oat, and soybean crops. The multispectral imagery from the UAS was radiometrically corrected and mosaicked. The multispectral reflectance orthomosaics from each surveyed field were used as input features in various algorithms along with associated vegetation index rasters.

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