Automatic production of environmental indicators from freely available remote sensing data: from a global to a local scale

2021, Computer Science, diiP, Masters Internship

2021

Masters Projects

@Computer Science

+Earth Sciences/Geosciences

+Demography

 

#Remote sensing

#Deep learning

#Sentinel 2

#Local climate zones

#Africa

Project Summary

This collaborative project aims at studying the feasibility of automatically producing repeatable indicators from remote sensing data in Africa to allow for spatially complete and temporally up-to-date information. To this effect, we will use freely available Sentinel 2 images (produced by the European Space Agency) to produce standardised environmental indicators, in the form of local climate zones. The student will study the relevance of a convolutional neural network-based method for this task. She will also explore the possibility of embedding spatio-temporal relations in such a model, and quantify the benefits. Finally, a reflection on the relevance of these results for demographic studies will be conducted, as well as a graphical user interface allowing to produce such indicators given a remote sensing image.

 

Sylvain Lobry

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