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21 September 2016

Summary: The project involves the development of a new cloud detection algorithm for satellite imagery based on a statistical learning approach. The implementation of this algorithm will operate directly on GA’s NBAR corrected Landsat archive housed at the National Computational Infrastructure (NCI) to produce a new cloud mask product that will be made available through the Australian Geoscience Data Cube v2.

The photo demonstrat the types of difficult images that have a mix of sand, salt lakes, thin cloud, thick cloud, and cloud shadow. The classifier accurately detects the cloud and is not confused by the salt lake.

Extra note: As an extension of this work and for those of you have an interest, CBE researcher Dr. Dale Roberts has started developing an information site on the internet: https://github.com/daleroberts/tv on the tool that turns massive satellite images into text so they can be quickly visualised without needing to download them.

This project is sponsored by Geoscience Australia Research Collaboration.

Updated:   2 March 2017 / Responsible Officer:  CBE Communications and Outreach / Page Contact:  College Web Team