Dr. S.L.M. (Stef) Lhermitte

profile

Biography

Stef Lhermitte is a remote sensing scientist with specific interest in the use of multi-source remote sensing and land surface modelling to assess cryosphere, atmosphere and ecosystem dynamics. Since 2016 he is assistant professor Geoscience & Remote Sensing at TUDelft, after obtaining a PhD in bioscience engineering at KULeuven, Belgium, and several international post-docs positions (CEAZA, KNMI, KULeuven), where he worked on broad range of remote sensing technologies in a variety of applications ranging from cryospheric and atmospheric sciences to ecology and hydrology. Now he focuses on the development of innovative remote sensing methods for assessing land-atmosphere interactions in order to assess the effect of climate (change) on the cryosphere, ecosystem dynamics, the hydrological cycle, sea level rise, etc. and their feedbacks on (future) climate.

Expertise

The earthmapps.io team under supervision of Stef Lhermitte, focuses on the use of multi-source satellite imagery to assess land-atmosphere interactions. Our research aims at developing innovative remote sensing methods for quantifying the effect of climate (change) on snow/ice, vegetation dynamics, etc. and determine their (climate) feedbacks. We work on big data solutions and machine learning techniques to bridge the gap between remote sensing technology and its (scientific) applications.
Technologically we work on the interface between multi-source satellite imagery, radiative transfer models, land-surface models (e.g. snowmodels) and climate models. Within this framework we aim at developing and integrating innovative methodologies to assess the Earth's surface properties, mainly snow/ice and vegetation related, and understand their complex spatio-temporal response to climate. These methodologies range from improved data processing and data machine learning, to big data solutions and time series analysis (e.g. tipping points)

publications
Publications in Pure
subjects
2016 - Methodology of Geophysics and Remote Sensing
2017 - Methodology of Geophysics and Remote Sensing
2017 - Cryosphere: Remote Sensing and Modelling
2017 - Cryosphere: Remote Sensing and Modelling
2017 - Earth Observation
2017 - Simulation and visualization
2018 - Methodology of Geophysics and Remote Sensing
2018 - Simulation and visualization
2018 - Cryosphere: Remote Sensing and Modelling
2016 - Earth Observation
2018 - Earth Observation
2020 - Applied Machine Learning
2020 - Methodology of Geophysics and Remote Sensing
2018 - Cryosphere: Remote Sensing and Modelling
2020 - Climate Change: Science & Ethics
2020 - Climate Change: Science and Ethics
2020 - Remote Sensing and Big Data
2020 - Climate Impacts and Engineering
2019 - Advanced project on GRS
2019 - Simulation and visualization
2019 - Cryosphere: Remote Sensing and Modelling
2019 - Cryosphere: Remote Sensing and Modelling
2019 - Earth Observation
2019 - Methodology of Geophysics and Remote Sensing
2018 - Advanced project on GRS
2019 - Climate Change: Science & Ethics
2019 - Climate Impacts and Engineering
2020 - Simulation and visualization
2020 - Cryosphere: Remote Sensing and Modelling
2020 - Cryosphere: Remote Sensing and Modelling