Title: Earth Observation and Deep Learning in Support of the Sustainable Development Goals
Speaker: Dr. Claudio Persello
Faculty of Geo-Information Science and Earth Observation,
University of Twente, The Netherlands
Date and time: December 8, 2021, 11:30-12:30
***This is an online event. To obtain Zoom link and password, please contact to the department.
The continuous developments in Earth observation technologies and the increasing availability of voluminous geospatial data go hand-in-hand with the demand for accurate and scalable information extraction methods. This demand is motivated by many applications and the growing awareness of the necessity to monitor the Earth’s system for the multiple threats to our natural environment, climate, and the sustainable development of human societies. Deep learning has revolutionized the way we analyze, fuse, and extract information from data. It allows us to streamline the processing workflow and generate actionable information in an efficient and reproducible manner. Moreover, departing from universities and research laboratories, the combination of Earth observation and deep learning has the opportunity to contribute to some of the most pressing global societal challenges, such as those identified by the United Nations in the 2030 agenda for sustainable development. This talk will present some research activities showing where Earth observation and deep learning can contribute to monitoring and achieving the Sustainable Development Goals (SDGs).
Dr. Claudio Persello received the Laurea (BSc) and Laurea Specialistica (MSc) degrees in telecommunications engineering and the PhD degree in communication and information technologies from the University of Trento, Trento, Italy, in 2003, 2005, and 2010, respectively. He is currently an Associate Professor at the Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, The Netherlands. Before joining ITC in 2014, he was a Marie Curie research fellow, conducting research activity at the Max Planck Institute for Intelligent Systems and the Remote Sensing Laboratory of the University of Trento. His main research interests are in the context of machine learning and deep learning for information extraction from remotely sensed images and geospatial data. The activity includes the investigation and development of dedicated deep learning techniques for various remote sensing sensor data and multiple applications, focusing on societal challenges in the Global South. He is particularly interested in combining deep learning and Earth observation to address and monitor the progress towards the sustainable development goals. Dr Persello is a referee for multiple journals in the field of remote sensing and image analysis, including IEEE Transactions on Geoscience and Remote Sensing, IEEE Geoscience and Remote Sensing Letters, IEEE Transactions Image Processing, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Remote Sensing and Pattern Recognition Letters. He is a member of the Remote Sensing editorial board and Associate Editor of the IEEE Geoscience and Remote Sensing Letters. He served/s on the Scientific Committee of MultiTemp 2011, 3D GeoInfo (since 2018), UAV-g 2019. He served as publication co-chair for IGARSS 2021. He is co-chair of the Image Analysis and Data Fusion (IADF) GRSS technical committee. His PhD thesis was awarded the prize for the best PhD thesis on Pattern Recognition published between 2010 and 2012 by the GIRPR, i.e., the Italian branch of the International Association for Pattern Recognition (IAPR). He is a Senior Member of the IEEE.