行知论坛213:Research perspectives in Earth Observation hyperspectral remote sensing

时间:2019-07-11浏览:294设置

行知论坛213Research perspectives in Earth Observation hyperspectral remote sensing 

地点:南京理工大学计算机科学与工程学院 4042会议室

时间:2019716日上午 9:30- 12:00

报告人:Jonathan Cheung-Wai Chan

报告题目: Research perspectives in Earth Observation hyperspectral remote sensing 

摘要:Hyperspectral data has been proven to be more effective in various challenging applications. To this date, there are no full stretch (350-2400nm) hyperspectral satellites that monitor with regular revisiting time. In the near future, several national/international initiatives will provide hyperspectral data at global scale, EnMAP from Germany is exemplary. While there have been significant developments in analytical methods/tools for hyperspectral data, we might still need more for the unprecedented newly available global hyperspectral data sets. Bear in mind most of the concurrent hyperspectral research are based on airborne/simulated data. This talk will briefly recap development in future Hyperspectral EO missions and some of the research directions: data acquisition, spatial and spectral enhancement, classification, applications, etc

 

 

 

特邀讲者:Jonathan Cheung-Wai Chan

Department of Electronics and InformaticsVrije Universiteit BrusselBelgium

简介:Jonathan Cheung-Wai Chan received the Ph.D. Degree from the University of Hong Kong in 1999. After that, he was a research scientist with the Department of Geography, University of Maryland, at College Park, Maryland USA. From 2001 to 2005, he was with the Interuniversity Micro-Electronics Centre (IMEC), Leuven, Belgium. From 2005 to 2011, he was with the Department of Geography at Vrije Universiteit Brussel (VUB), Brussels, Belgium. From 2013 to 2014, he was a Marie Curie fellow at Fondazione Edmund Mach (FEM), Italy. He is currently a Guest Professor at the Department of Electronics and Informatics (ETRO), VUB. His research interests include land cover classification, machine learning algorithms, spectral and spatial enhancement for hyperspectral satellite images.

He serves as a regular Technical Committee member for IEEE International Geoscience and Remote Sensing Symposium. He is the Guest Editor of Remote Sensing, for the Special Issues: Spatial Enhancement of Hyperspectral Data and Applications. Deep Learning and Data Mining for Hyperspectral Imagery.

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