Mapping urban deprivation and socio-economic inequalities using earth observation and deep learning скачать в хорошем качестве

Mapping urban deprivation and socio-economic inequalities using earth observation and deep learning

Mapping urban deprivation and socio-economic inequalities using earth observation and deep learning Tuesday, December 8, 2020 4 PM Central European Time 10 AM US Eastern Time Speaker: Prof. Claudio Persello, University of Twente, Netherlands According to UN-Habitat, approximately 1 billion people worldwide reside in informal settlements, commonly called slums, living in deprived conditions lacking access to essential services such as safe water, acceptable sanitation, and durable housing. This talk will present recent research activities aimed at using Earth observation and deep learning for mapping informal settlements, investigating their temporal evolution and the associated socio-economic conditions. SPEAKER’S BIO: Prof. Claudio Persello is an Associate Professor at the University of Twente, faculty of Geo-Information Science and Earth Observation (ITC), department of Earth Observation Science (EOS), Enschede, The Netherlands. From 2011 to 2013 he was a Marie Curie research fellow with the project “MaleRS – Machine learning techniques for the analysis and classification of the last generation of remote sensing data”, supported by the European Commission and the Province of Trento. During the first two years of this project, he conducted his research activity at the Department of Empirical Inference, Max Planck Institute for Intelligent Systems, Tubingen, Germany. From June 2013 to August 2014, he was with the Remote Sensing Laboratory, Department of Information Engineering and Computer Science, University of Trento. His main research interests are on the analysis of remote sensing data, machine learning, image classification, and pattern recognition. He is currently working on the analysis of images acquired by Unmanned Airborne Vehicles (UAVs) for monitoring urban areas.