Guest talk: Lingli Zhu "Deep Learning for Remote Sensing and Geographic Information Systems"

Dr. Lingli Zhu from Finnish Geospatial Research Institute will give a guest talk at the course CS-EJ3311 Deep Learning with Python.
Guest Talk tapahtumakuva

Deep Learning for Remote Sensing and Geographic Information Systems

Dr. Lingli Zhu
Finnish Geospatial Research Institute

Date: 15 November at 10:00-11:00


Although research on deep learning technology has been conducted with the cross- disciplinary in surveying and mapping, practical applications in such fields are fairly rare. Ministry of Finance in Finland funded the Advanced Technology for Topographic Map Updating (ATMU) project for the National Land Survey of Finland, aiming for exploring and utilizing deep learning technology for the topographic map updating. In the project, we investigated multiple deep learning technologies with the datasets of remote sensing and GIS, including different neural networks e.g. U-Net and PointNet, and different learning techniques: transfer learning and multitask learning, with different datasets: images (true orthophotos), vectors, Digital Surface Models (DSMs), and 3D Lidar point clouds. The lecture will focus on the use of deep learning technologies, as well as problems and challenges that we encountered in the ATMU project.


Dr. Lingli Zhu received her Doctoral Degree in the field of Remote Sensing (with a minor study in Information technology) at Aalto University in 2015. She achieved a Master Degree in Photogrammetry at Helsinki University of Technology (Current: Aalto university) in 2007, and a minor study in Geographic Information System (GIS). She works as a chief specialist in map production, and a research manager in Finnish Geospatial Research Institute, National Land Survey of Finland. Currently, she is leading the ATMU project that investigates the use of deep learning technology for topographic map updating. She is an expert in the fields of Laser scanning, Remote Sensing, Photogrammetry, GIS, Computer Vision, and Machine Learning. She has leaded a research group of 3D modelling and Virtual Reality since 2013, at Finnish Geospatial Research Institute(FGI), under the Centre of Excellence in Laser Scanning Research, granted by the Academy of Finland (2014-2019), the leading research projects equivalent to 2.5M€ during 2013-2019. In 2017, she was evaluated to meet the requirements of the Professor of Digital Photogrammetry (selected as top four candidates) in Aalto University. She has published 30+ SCI papers as the first author and three book chapters. One of the book chapters has reached a downloaded record of 2980. She was a member of Scientific committee of UPINLBS 2018 conference and also has been invited as a guest editor for special issues in several well known journals such as ISPRS International Journal of Geo- Information (IJGI) (2018, 2021), Remote Sensing (2019, 2020, 2021), and International Journal of Applied Earth Observation and Geoinformation (JAG) (2021). She has reviewed 40+ papers for Remote Sensing, Sensors, IJGI, JAG, and IEEE Transactions on Geoscience and Remote Sensing (TGRS), and so on.

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