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Prof. Dr. Jonathan C-W Chan

ETRO Professor

Biography Research Publications
Short CV

2014-present Guest Professor/Senior Researcher, ETRO-VUB

2013-2014 Marie Curie Fellow, Fondazione Edmund Mach (TN, Italy)

2011-2012 Senior Researcher, ETRO-VUB

2005-2011 Doctor Assistant, Geography Dept., Vrije Universiteit Brussel (VUB)

2001-2005 Post-doc Engineer, Interuniversity MicroElectronics Centre (IMEC), Leuven, Belgium


Use of machine learning methods for land-cover classification, change detection and information retrieval from remotely sensed data


Jonathan Cheung-Wai Chan is an expert in remote sensing with a special focus on machine learning algorithms for hyperspectral analysis and detailed land cover mapping. Shortly after obtaining his PhD from the University of Hong Kong (1999), he worked as a research scientist at the Geography Department, at University of Maryland, College Park, the United States. He was involved in various NASA projects in relation to global mapping using machine learning algorithms (C5.0, Bagging, Boosting). In 2001, he was hired as a post-doc researcher at InterUniversity MicroElectronics Research Center (IMEC) at Leuven, stationed at the Department of Electronics and Informatics (ETRO), at Vrije Universiteit Brussel (VUB). He worked on European projects which applied remote sensing methods (Thermal continual measurement) for land mines detections as well as risk estimation of a mine-contaminated area using high definition multispectral images (Ikonos, images from unmanned vehicle). From 2005 to 2011, he was a Doctor Assistant at the Geography Department at VUB where he engaged in teachings at bachelor and master levels for courses relating to remote sensing and Geographical Information Science. At the same time, he was leading research topics for exploitation of airborne and spaceborne hyperspectral remote sensing applications include conservation mapping, ecotope mapping for biodiversity and impervious surface estimation for hydrological modeling. His research of applying multi-angle hyperspectral images for superresolution image enhancement is recognized to have important contributions for various applications (Ecotope characterization impervious surface mapping). He organizes remote sensing seminars and teaches introductory remote sensing at the Doctoral School of VUB. He has supervised numerous master and doctoral theses. Students who are interested in pursuing a doctoral degree in related topics are welcome to contact him at

He is part of the Technical and Scientific Committees of IGARSS (IEEE International Geoscience and Remote Sensing Symposium) in 2012 and 2013 and has chaired a special session on Superresolution and Subpixel Classification in IGARSS in 2011 and 2012. He has widely published in topics related to detailed land cover classification using remote sensing data and serves as a regular reviewer for remote sensing journals. In 2012, he has been invited as an expert member for EU COST DC-ICT and TDP and external reviewer for the National Research Council of Romanian Government. In 2012, he is awarded a scholarship as an exchange professor to teach remote sensing courses in S.Seifullin Kazakh Agro Technical University, Kazakhstan.

From 2013-2015, he will spend most of his time at the Research and Innovation Centre, Fondazione Edmund Mach, Italy, to apply advanced remote sensing methods for forest science. This stay is funded under the stream of Marie Curie Industry-Academia Partnerships and Pathways (IAPP) program.


“Synergies of Spaceborne Imaging Spectroscopy with Other Remote Sensing Approaches”

In Surveys in Geophysics

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“Coarse-to-fine salient object detection based on deep convolutional neural networks”

In Signal Processing: Image Communication

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“FOV Expansion of Bio-Inspired Multiband Polarimetric Imagers with Convolutional Neural Networks”

In IEEE Photonics Journal

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other publications ...

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