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Machine Learning Technologies for Enabling Earth Observation

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thesis
posted on 05.07.2021, 06:08 by BENJAMIN MICHAEL LUCAS
Machine learning plays a vital role in the field of Earth observation. This role is sometimes a direct application of an existing machine learning methods, but more often than not, a novel approach is required owing to the individual nature of the application and the data. My research explores and develops machine learning technologies to automate the production of land cover maps of the Earth’s surface. Using satellite imagery as data, the algorithms developed facilitate the production of maps at unprecedented accuracy and scale.

History

Campus location

Australia

Principal supervisor

Francois

Additional supervisor 1

Geoffrey Webb

Additional supervisor 2

Daniel Schmidt

Additional supervisor 3

Charlotte Peletier

Year of Award

2021

Department, School or Centre

Clayton School of IT

Course

Doctor of Philosophy

Degree Type

DOCTORATE