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EuroSDR Educational Service (EduServ) annually offers four two-week e-learning courses in the field of GeoInformation (GI). It is designed for knowledge transfer from the research to the production domain. Thus, it is mainly focused on participants from NMCAs and industry but also PhD students and researches find the courses interesting as they always reflect latest developments in GI.
The 17th series of e-learning courses from EuroSDR will begin with a pre-course seminar, hosted by Dr. Julià Talaya at the Cartographic and Geologic Institute of Catalunya, Barcelona, Spain, from 4th to 5th March 2019. During the seminar, background material of four e-learning courses will be presented by the tutors, participants will meet the tutors and fellow participants, and the learning platform – Moodle, will be demonstrated.
The four e-learning courses are scheduled from March till June 2019. They can be followed over the Internet from any location, thereby allowing participants to update their knowledge with minimum disruption. Courses require about thirty hours of online study.
The flyer can be downloaded here.
Automatic Topographic Mapping through Description and Classification of Remotely Sensed Imagery and Cartographic Enhancement (pdf)
Tutors: Joachim Höhlea, Sébastien Lefèvreb, and Bharath Bhushan Damodaranb
aAalborg University, bIRISA/Université Bretagne Sud
The course introduces advanced classification schemes with the goal to produce and update 2D topographic databases. The inclusion of the spatial descriptors such as geometry and shape are important to characterize the topographic objects in the orthoimages. This course will present some of the challenges in mapping from high resolution orthoimages. The solution to these challenges will be provided by the efficient and effective tool called as morphological attribute profiles. They are multi-scale attributes and are constructed by hierarchical representation of the images, thus enabling object-based image analysis. These characterizations are classified using well-established machine learning methods and different data sources (either raw or derived features). Different approaches to assess the thematic and geometric accuracy of maps will be discussed, and lastly the cartographic enhancement of the classification maps at different levels of quality will be presented. Solutions to the tasks are given by means of detailed course material including open source programs.
Dates: 11 - 22 March 2019
3D Sensing, Scene Reconstruction and Semantic Interpretation (pdf)
Tutors: Martin Weinmanna, Michael Weinmannb, Franz Rottensteinerc, Boris Jutzia
aKarlsruhe Institute of Technology, bUniversity of Bonn, cLeibniz Universität Hannover
The adequate acquisition and analysis of a scene are of great interest for photogrammetry, remote sensing, computer vision and robotics. In the scope of this course, we will address four major issues in this regard. The first part will give a general introduction on geometry acquisition via (passive and active) optical 3D sensing techniques. The second part will focus on active optical 3D sensing as commonly used for the acquisition of large geospatial data and provide a survey on the extraction of descriptive features from such data. The third part will focus on a semantic interpretation of point cloud data and thereby address all components of a typical processing workflow from given point cloud data to a semantic labeling with respect to user-defined classes. The fourth part is dedicated to deep learning techniques for the semantic labeling of point clouds as well as to the context-based classification of these data using graphical models such as Conditional Random Fields (CRFs).
Dates: 1 - 12 April 2019
Open Spatial Data Infrastructures (pdf)
Tutors: Bastiaan van Loenena, Joep Crompvoetsb
aTU Delft, bKU Leuven
This is an introductory course to Open Spatial Data Infrastructures (Open SDI). SDIs facilitate more and more the accessibility to open (spatial) data and provision of open services. Open SDI refers to standards, technologies, policies, and institutions necessary for opening the open data and services. This course gives a comprehensive overview on the state-of-the art in Open SDI and its key components, introduces the participants to the underlying principles of Open SDI and lets them experience hands-on what it means to establish and maintain an Open SDI. A number of topics will be discussed: key standards, architectures, (network) services, relevant EU-regulations and policies, governance strategies, and key institutions. At the end of the course, participants are: informed about Open SDI strategies around the world, aware of the main strengths, weaknesses, opportunities and threats of Open SDI, familiar with the latest technological developments, capable to facilitate the opening of open data using latest developed tools, and able to evaluate Open SDIs.
Dates: 6 - 17 May 2019
Deep Learning for Remote Sensing (pdf)
Tutors: Loic Landrieua, Sébastien Lefevreb, Bertrand Le Sauxc)
aIGN France, bIRISA/Université Bretagne Sud, cONERA
Deep Learning has led to significant breakthroughs in various fields including computer vision. Remote sensing also benefits from such methodological advances and deep networks currently achieve state-of-the-art results in many automatic tasks, such as object detection, semantic segmentation (e.g. for land cover mapping), change detection, etc. The goal of this course is to introduce deep learning, review the main architectures relevant for cartography, photogrammetry and other EuroSDR-related fields, as well as to train the participants with available software and codes.
It is complementary to the course "Topographic Maps through Description and Classification of Remotely Sensed Imagery and Cartographic Enhancement" that focuses on the traditional approach to automated classification (i.e. feature extraction and supervised classification) while deep learning brings a paradigm change by learning both the features and the classifier, at the possible cost of higher labelled datasets and higher computational resources. The audience will be welcome to come with their own data to discuss the lecturers about the relevance of deep learning solutions in their context.
Dates: 3 - 14 June 2019
You can register here for the e-learning courses until 22nd February 2019. You will receive a confirmation email within 7 days.
€600 for pre-course seminar + 1 or 2 courses
€700 for pre-course seminar + 3 or 4 courses
€100 for pre-course seminar only
The fee for attending the pre-course seminar is €100. This fee will be deducted from the course fee in case of later subscription to the e-learning courses.
A limited number of scholarships will be available to fully cover the course fee and to partially support the travel costs to the pre-course seminar (up to € 500). The scholarships are intended to Ph.D./Master students and other applicants with no or very limited financial support from their university or public institution. Successful completion of at least two courses is required from applicants in order to reimburse their travel costs.
In order to proceed with the application:
- Register to EduServ.
- Fill in the application form that includes a motivation letter, information about professional experience and calculation of travel costs. It is recommended to support the application with a reference letter. Both documents shall be submitted to firstname.lastname@example.org not later than 1st February 2019.
Applicants will be informed about the acceptance/rejection of their application latest on 18th January 2019. The approved travel costs will not be refunded before successful completing of at least two e-Learning courses the applicant registered for! Successful applicants from previous years will be automatically excluded from the evaluation.
Date: 4th - 5th March 2019
Transportation and hotels: More information on how to reach ICGC, transportation and nearby hotels can be found here.
Programme of the seminar (pdf)
4th March 2019
8:30 – 9:00
9:00 - 9:30
09:30 - 12:30*
Introduction to the course “Automatic Topographic Mapping through Description and Classification of Remotely Sensed Imagery and Cartographic Enhancement” (Joachim Höhle, Aalborg University, Denmark & Sébastien Lefèvre, IRISA / Université Bretagne Sud, France)
12:30 - 13:30
13:30 - 16:30*
Introduction to the course “3D Sensing, Scene Reconstruction and Semantic Interpretation” (Martin Weinmann & Boris Jutzi, Karlsruhe Institute of Technology, Germany, Michael Weinmann, University of Bonn, Germany)
16:30 - 17:00
Presentation of the Moodle Learning Management System (Markéta Potůčková, Charles University, Czechia)
Dinner at the Mussol Arenas restaurant
5th March 2019
09:00 - 12:00*
Introduction to the course “Deep Learning for Remote Sensing” (Loic Landrieu, MATIS/IGN, France & Sébastien Lefèvre, IRISA / Université Bretagne Sud, France)
12:00 - 13:00
13:00 - 16:00*
Introduction to the course “Open Spatial Data Infrastructures” (Joep Crompvoets, KU Leuven, Belgium)
16:00 - 16:10
Closing the seminar
* Each session includes a coffee break (approx. 10:30 and 15:00)
“The whole course was really well done in both terms of form and content. Everything was thought through, communication was top notch. I believe I gained valuable knowledge in most of the topics. I can highly recommend this course to anyone who is interested in spatial research.” (Jan Dolezal, Charles University)
“Both [courses] were very enlightening and supported me during several steps of my PhD research.” (Marco Palma, Università Politecnica delle Marche)
- I haven't received a confirmation email yet. Did something go wrong?
No. An official confirmation email will be sent to you within 7 days. If you haven't received an email, please contact the secretariat (email@example.com).
- I would like to enroll to the e-learning course(s), but I am not able to attend the pre-course seminar. Is that a problem?
No. It is not obligatory to attend the pre-course seminar. Please note that the fee for attending the pre-course seminar is always included in the total price.
- Is it possible to register for the seminar only?
Yes. The fee for attending the pre-course seminar only is €100. This fee will be deducted from the course fee in case of later subscription to the e-learning courses.
- What does the course fee include?
The course fee includes all course materials, two-weeks of e-learning, participation at a two-day seminar, lunch on both days and a joint dinner on Monday evening. Please note that the course fee does not include accommodation and travel costs.
- Can I pay by credit card?
Unfortunately we are unable to accept payment by credit card. However, payments can be made by bank transfer or by invoice.
- Is it possible to request an invoice?
Yes. If you would like to receive an invoice, please contact the secretariat as soon as possible at firstname.lastname@example.org. Please note that EuroSDR does not have a VAT number.
- Who can apply for a scholarship?
The scholarships are intended to Ph.D./Master students and other applicants with no or very limited financial support from their university or public institution. You can only apply for a scholarship if you take active part in all 4 EduServ courses (but we accept if at least two of them are successfully completed). Please note that successful applicants from previous years will be automatically excluded from the evaluation.
- When will I receive the login details of Moodle?
You will receive an email with the login details about a week prior to the start of the e-learning course you registered for.
- Will I receive a certificate?
Yes, you will receive a certificate of completion after successfully completing the e-learning course(s). This certificate will be sent to you by email or to the address you provided on the registration form latest at the beginning of July. If you haven't received your certificate by then, please contact the secretariat (email@example.com).
In case you did not pass the course(s), it is possible to obtain a certificate of attendance. You can request this certificate by sending an email to firstname.lastname@example.org.
For more information, contact Ms. Tatjana Van Huyck - email@example.com