Jan Skaloud

EPFL ENAC SSIE-GE
GC C2 397 (Bâtiment GC)
Station 18
1015 Lausanne

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. Maas and G. Vosselman, Eds. Whittles Publishing, 2010. J. Skaloud, «Reliability of direct georeferencing phase 1: An overview of the current approaches and possibilities,» in Checking and Improving of Digital Terrain Models / Reliability of Direct Georeferencing, EuroSDR Official Publication 51, 2006. K. Legat, J. Skaloud, and R. Schmidt, «Reliability of direct georeferencing phase 2: A case study on practical problems and solutions.,» in Checking and Improving of Digital Terrain Models / Reliability of Direct Georeferencing., EuroSDR Official Publication 51, 2006.

Editorial

• ISPRS Journal of Photogrammetry and Remote Sensing, 2012-current, editorial board • IEEE – Transaction on Vehicular Technology • IEEE – Transaction on Aerospace and Electronic Systems • IEEE – Transaction on Radar, Sonar & Navigation • IEEE – Transaction on Robotics and Autonomous Systems • IEEE – Transaction on Instrumentation and Measurement • IEEE – Transaction on Pattern Recognition • IEEE – Transaction on Signal Processing • IEEE – Geoscience and Remote Sensing Letters • ISPRS Journal of Photogrammetry and Remote Sensing • Photogrammetry Engineering and Remote Sensing • Canadian Aeronautics and Space Journal • Canadian Journal on Remote Sensing • Geomatica • Photogrammetry Records • Advances in Space Research • Measurement Science and Technology • Remote Sensing • Journal of photogrammetry, remote sensing and geo-information processing (PFG) • Survey Review

Awards

Samuel Gamble Award, carrier contribution in photogrammetry & sensing

International Society for Photogrammetry and Remote Sensing

2021

big U.V. Helava Award - best paper in J ISPRS over 2016-2019 period

International Society for Photogrammetry and Remote Sensing

2020

Best Demo Award - 4th IEEE International Workshop on Metrology & Aerospace

IEEE

2017

Hansa Luftbild Award - best-paper of the year in PFG journal

PFG Journal

2014

Karl Kraus Medal - best textbook in Photogrammetry, Remote Sensing and GIS

International Society for Photogrammetry and Remote Sensing

2012

GNSS Leader to Watch - Innovation Award

GPS World journal

2009

Infoscience

Teaching & PhD

PhD Students

Aurélien Arnaud Brun, Jesse Ray Murray Lahaye, Antoine Paul Carreaud, Nicola Antonio Santacroce, Simon Gilgien

Past EPFL PhD Students

Adrian Ulrich Wägli, Philipp Schär, Yannick Stebler, Martin Rehak, Mehran Khaghani, Philipp Clausen, Emmanuel Clédat, Omar Garcia Crespillo, Gabriel François Laupré, Pasquale Longobardi, Aman Sharma, Kenneth Joseph Paul, Kyriaki Mouzakidou

Past EPFL PhD Students as codirector

Kevin Sylvain Barbieux

Courses

Estimation methods

ENG-267

The students treat observations affected by uncertainty in a rigorous manner. They master the main methods to adjust measurements and to estimate parameters. They apply specific models to real-world problems encountered in various experimental sciences.

Inference for large-scale time series with application to sensor fusion

CIVIL-606

Large-scale time series analysis is performed by a new statistical tool that is superior to other estimators of complex state-space models. The identified stochastic dependences can be used for sensor fusion by Bayesian (e.g. Kalman) filtering or for studying changes in natural/biological phenomena.

Robotics practicals

MICRO-453

The goal of this lab series is to practice the various theoretical frameworks acquired in the courses on a variety of robots, ranging from industrial robots to autonomous mobile robots, to robotic devices, all the way to interactive robots.

Sensing and spatial modeling for earth observation

ENV-408

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.

Sensor orientation

ENV-548

Determination of spatial orientation (i.e. position, velocity, attitude) via integration of inertial sensors with satellite positioning. Prerequisite for applications related to remote sensing, environmental monitoring, mobile mapping, robotics, space exploration, smart-phone navigation, etc.