Novel Topics in Geoinformatics: Drones, EO, Space-Time, Deep Learning

How drones relate to satellites in data collection and mapping? What space-time interactions have to say for understanding our environment?

May 23, 2022, 11:00am Eastern Time – June 3, 2022, 10:30am Eastern Time

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Instructors and teaching assistant

Photo of Panagiotis PartsinevelosPanagiotis Partsinevelos, Technical University of Crete

Dr. Panagiotis Partsinevelosis an Associate Professor in the area of Space Informatics including Uncrewed Aerial Systems, GIS, Remote Sensing, GNSS from their computer science perspective. He received his PhD in Spatial Information Science & Engineering from the University of Maine, part of the National Center for Geographic Information and Analysis (NCGIA) in USA and NASA Center of Excellence in Remote Sensing Applications. Prof. Partsinevelos directs Senselab Research group, a leading interdisciplinary research entity developing novel solutions for 3-dimensional processing, tangible GIS, gestural interfaces, visualization platforms, location-based services, ML algorithms, smart cities, etc. SenseLab has been recognized by a series of prestigious international awards and distinctions including: 2019 Airbus Global Earth Observation challenge, 1st globally, 2018 RMIT drones for refugees, Amman, 2017 Space Oscars, Tallinn, 1st globally, 2016 European GNSS Service (GSA), 1st place globally, 2016 ESNC Satellite masters, 2nd overall winners, (400 teams), Madrid, 2016 UAE Drones for Good (1st in EU and 3rd internationally between 1017 teams from 165 countries), Dubai, 2016 DJI drones Developer Challenge (short-listed), USA, 2015 Copernicus Masters NCMA, 1st winner in Remote Sensing visualization, Berlin.After many years of teaching in many versatile and demanding environments, countries, continents, cultures and levels, Dr. Partsinevelos is privileged with long term collaborations and through a genuine inclination towards philosophy, humanities, and cognition, he is always there to creatively share an provoke classroom experiences.

Emmanouil VarouchakisEmmanouil Varouchakis, Technical University of Crete

Dr. Emmanouil Varouchakisis is an Assistant Professor at the School of Mineral Resources Engineering, Technical University of Crete-Greece, with expertise in spatiotemporal geostatistical analysis of earth science data. Dr. Varouchakis has significant teaching experience in the area of space-time geostatistics having taught advanced geostatistics courses in IHE Delft and Technical University of Crete, and in invited seminars of European Geosciences Union. His Research experience include more than 40 journal publications in the area of geostatistics employed in earth science and satellite data. Dr. Varouchakis will be responsible for the geostatistics session and the relative assignment and project preparation providing his unique expertise in space-time geostatistical data analysis.

Photo of Georgios PetrakisGeorge Petrakis, Technical University of Crete

George Petrakis is a Phd candidate in GeoInformatics engineering. He completed his under-graduate studies in Rural, Surveying and GeoInformatics Engineering school of Technical University of Athens and his post-graduate studies in Mineral Resources Engineering school of the Technical University of Crete. He has participated in many research projects, while he has an active role in several publications and conferences. His main research interests include topics from geospatial web development, computer vision / photogrammetry and machine / deep learning.


Eligibility and capacity

We will select up to 20 graduate students to participate in this workshop. Selection will be based on your AAG membership status, your research needs, and time of registration. If you are selected, we will notify you ahead of the workshop and provide you all the workshop details and session links. If you are selected, the expectation is that you will participate in all sessions of the workshop.


Audience

This workshop is for any student across the whole geography spectrum. The selected participants should be eager to learn combinational current methodologies for data collection, data integration/fusion and data analysis. Students are not required to be familiar with any particular software and they can be in any stage of their research, since the topics covered may inspire new graduate students and also aid students in their data collection or defense stage to propagate their research agenda. Students should be familiar with introductory undergraduate algebra and use of any common software (programming is not required). The assignments will be based mainly on open (Python, R, QGIS, etc.) or in-house/free to use implemented tools and software.


Detailed schedule

This workshop will meet at the following times (Eastern Time):

  • Session 1: AAG Welcome Session, 11:00 am – 12:30 pm, Monday, May 23
  • Session 2: 9:00 – 10:30 am, Tuesday, May 31
  • Session 3: 9:00 – 11:00 am, Wednesday, June 1
  • Session 4: Optional Office Hours and Lab Hour, 11:00 am – 1:00 pm, Wednesday, June 1
  • Session 5: 9:00 – 11:00 am, Thursday, June 2
  • Session 6: Optional Office Hours and Lab Hour, 11:00 am – 1:00 pm, Thursday, June 2
  • Session 7: 9:00 – 10:30 am, Friday, June 3

Throughout the week, expect to also spend a few hours working independently on readings or short assignments for the workshop.