GRSS Schools
PhD Spring School on “Advanced remote sensing techniques for risk management”
Goals and objectives The PhD school on “Advanced remote sensing techniques for risk management” aim at introducing the attendees to the development and implementation of new, innovative and advanced remote sensing techniques to improve capabilities in characterizing risk components such as hazard, vulnerability and exposure by means of hyperspectral image analysis, advanced SAR processing, machine learning and cloud computing for remote sensing, and geostationary satellites data processing. The PhD school will be supported by EU H2020 EOXPOSURE. It will consist of three days of theoretical and practices sessions focused on tools and application examples, and two days of EOEXPOSURE open workshop to present conferences and tutorials related to risk, vulnerability and exposure applications. To this aim, the school and the EOXPOSURE event will bring together leading researchers from academic institutions, data providers and industry end users.
Contact points:
- Jorge Marquez (Universidad Nacional de Mar del Plata, Buenos Aires, Argentina);
- Marcelo Scavuzzo, Anabella Ferral, Sofia Lanfri, Alba German (CONAE, Instituto Mario Gulich, Univ. Cordoba, Cordoba, Argentina).
Format: online
Tentative audience: 300
Tentative dates: end of September 2021 – week 38
IGARSS21 summer school on “Drone acquisition, processing and applications”
Goals and objectives The summer school aims to offer the students a thorough introduction to the use of drones for remote sensing, with a strong focus to operational use of these platforms for several applications. It includes diverse sessions:
- theory: platforms, sensors and imaging data, ground truth measurements;
- Hands-on sessions: data acquisition, data processing, validation of materials;
- Demos: drone& camera set-up; mission planning, calibration, quality control; ground truth;
Contact points:
- Michal Shimoni (RMA, Brussels, Belgium)
- Bart Deronde (VITO, Mol, Belgium)
Format: in person
Tentative audience: 20
Tentative dates: July 7-9, 2021
Fall School on “Advanced Techniques in Remote Sensing Data Processing and Analysis”
Goals and objectives The research and development community has been engaged in advancements in the processing and analyzing remotely sensed data in the last couple of decades. The school will introduce the students to numerous approaches/frameworks/schemes/algorithms to address information retrieval in remotely sensed satellite data acquisition, processing, and analysis. They include feature extraction (information retrieval), information analysis/characterization, information reasoning, spatio-temporal modeling, and visualization. With data availability across various spatial/spectral/temporal resolutions, besides information extraction, the school will focus on pattern retrieval, pattern analysis, spatial reasoning, simulation, and modeling of spatio-temporal behaviours of several terrestrial phenomena and processes as well.
Contact points:
- Avik Bhattacharya, Indian Institute of Technology Bombay
- S. Daya Sagar, Indian Statistical Institute-Bangalore Centre
- Rama Rao Nidamanuri, Indian Institute of Space Science and Technology
- Ashish Ghosh, Indian Statistical Institute, Kolkata
Format: Hybrid
Tentative audience: 300
Tentative dates: Nov. 25-27, 2021
Summer School on High-Performance and Disruptive Computing in Remote Sensing (HDCRS)
Goals and objectives The summer school organized by the High-Performance and Disruptive Computing in Remote Sensing (HDCRS) Working Group is part of the IEEE Geoscience and Remote Sensing Society (GRSS), in particular of the Earth Science Informatics (ESI) Technical Committee. This school is the perfect venue to network with students and young professionals, as well as senior researcher and professors who are world-renowned leaders in the field of remote sensing and work on interdisciplinary research with high-performance and distributed computing, disruptive computing and parallel programming models with specialized hardware. This year the programme includes:
- Topic 1: From HPC to Quantum paradigms in Earth Observation
- Topic 2: Programming GPUs and Accelerators with Directives
- Topic 3: Scaling Machine Learning for Remote Sensing using Cloud Computing
For more information, see indico-jsc.fz-juelich.de/event/174/overview
Contact points:
- Gabriele Cavallaro (Forschungszentrum Jülich)
- Dora Blanco Heras (University of Santiago de Compostela)
- Wu Zebin (Nanjing University of Science and Technology)
- Simulation and Data Lab Remote Sensing (University of Iceland)
- Center of Excellence “Research on AI- and Simulation-Based Engineering at Exascale” (CoE RAISE)
Format: online
Tentative audience: 300
Tentative dates: May 31 – June 3, 2021
Spectrum Management School for Remote Sensing Scientists and Engineers
Coming Soon
Summer school on Artificial Intelligence in Remote Sensing Applications
Coming Soon
