Remote Sensing & Machine Learning for Large Scale Coral Reef Monitoring
This project is aimed at developing novel methods to monitor coral reefs using remote sensing technologies and machine learning. Recent years have brought an exponential increase of data available from remote sensing technologies such as satellites and airborne systems. The advent of these massive datasets has sparked research on how to extract relevant information for monitoring our environment in unprecedented scale & temporal resolution.
In particular, machine learning & deep learning promise to be powerful tools for making sense of these sources of massive datasets at various scales: from 3D reconstruction of large scale underwater imagery to monitoring time series of satellite images. The project is a collaboration between the Environmental Computational Science & Earth Observation (ECEO) laboratory at EPFL Valais, and the Laboratory for Biological Geochemistry through its Transnational Red Sea Center (TRSC) activities. A key requirement on the developed methods are that they are scalable & repeatable, in order to be suitable for missions of the TRSC.
