Course

ENV-408: Sensing and spatial modeling for earth observation

Summary

Students get acquainted with the process of mapping from images (orthophoto and DEM), as well as with methods for monitoring the Earth surface using remotely sensed data. Methods will span from machine learning to geostatistics and model the spatiotemporal variability of processes.

Lectures

Instructors (2)

Devis Tuia

I come from Ticino and studied in Lausanne, between UNIL and EPFL. After my PhD at UNIL in remote sensing, I was postdoc in Valencia (Spain), Boulder (CO) and EPFL, working on model adaptation and prior knowledge integration in machine learning. In 2014 I became Research Assistant Professor at University of Zurich, where I started the 'multimodal remote sensing' group. In 2017, I joined Wageningen University (NL), where I was professor of the GeoInformation Science and Remote Sensing Laboratory. Since 2020, I joined EPFL Valais, to start the ECEO lab, working at the interface between Earth observation, machine learning and environmental sciences.

Jan Skaloud

Expertise Satellite positioning, inertial and integrated navigation Sensor orientation and calibration, attitude determination Mobile mapping, airborne laser scanning Adjustment methods, Kalman Filtering Mission Teaching in 3 EPFL sections and 2 faculties, director of ESO lab. Books / Monographs J. Skaloud and M. Cramer, «Data Capture,» in GIS Handbook, W. Kresse and D. Danko, Eds. Springer, 2011. D. Lichti and J. Skaloud, «Registration and Calibration,» in Airborne and terrestrial laser scanning, H.-G. Ma

Official source

https://edu.epfl.ch/coursebook/en/sensing-and-spatial-modeling-for-earth-observation-ENV-408

Moodle Page

http://go.epfl.ch/ENV-408

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Summary

Lectures

Instructors (2)

Devis Tuia

Jan Skaloud

Official source

https://edu.epfl.ch/coursebook/en/sensing-and-spatial-modeling-for-earth-observation-ENV-408

Moodle Page

http://go.epfl.ch/ENV-408

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