Space Data Analysis Course

The course objectives are to make the students familiar with the basics of accessing and processing data from space missions. The course familizes students with selected missions and access to their data.  These are selected to represent a variety of data produced by scientific and applicational space missions. The students will gain practical experience with data management, visualization, and processing. The topics covered in the course should prepare students for further work in ESA projects, for instance as a trainee in the Young Graduate Trainee programme.

Lectures are focused on presentation of various space missions and approaches for the data analysis. Labs are focused on practically applying the topics discussed in the lectures. One of the important tasks realized by students within the course is work on a semester project assigned individually to each student or to a group of students. The projects are focused on expanding the topics examined in the lectures and exercises. 

Syllabus

Lecture topics are selected to cover a variety of mission types explored by ESA. Explored fields focus on astronomy,  geophysics, remote sensing, planetary science. The labs follow lecture topics with practical examples of data analysis.

The lecture plan includes few lectures dedicated to give an opportunity to finish lessons and discussions started during the previous weeks, to discuss semester projects, and if necessary, topics that students find challenging.

Lectures

  1. Introduction (Slides), AMON (Slides)
  2. Basic data science packages (Slides, Recording)
  3. Copernicus programme I. (Slides 1, Recording)
  4. Copernicus programme II. (Slides 2)
  5. Copernicus programme III. (Slides 3)
  6. Copernicus programme – time allocated for catching-up in case of missed or problematic topics
  7. Astrometry – Gaia (Slides)
  8. Astronomy – Herschel, Hubble space telescope, TESS
  9. Astrometry/Astronomy/Exoplanets – time allocated for catching-up in case of missed or problematic topics, discussion about semester projects
  10. Magnetosphere field – Swarm, magnetosphere models
  11. Heliophysics – Parker Solar Probe
  12. Cosmic ray physics – PAMELA, AMS, EUSO (cosmic ray oriented measurements)
  13. Presentation of student projects and time allocated for catching-up in case of missed or problematic topics

Labs

  1. Introduction, AMON 
  2. Basic data science packages (Slides, Recording)
  3. Copernicus programme I. (Recording)
  4. Copernicus programme II.
  5. Copernicus programme III.
  6. Consultations related to semester projects, time allocated for catching-up in case of missed or problematic topics.
  7. Astrometry – Gaia
  8. Astronomy – Herschel, Hubble space telescope, TESS
  9. Consultations related to semester projects, time allocated for catching-up in case of missed or problematic topics.
  10. Magnetosphere field – Swarm, magnetosphere models
  11. Heliophysics – Parker Solar Probe
  12. Cosmic ray physics – PAMELA, AMS (cosmic ray oriented measurements)
  13. Consultations related to semester projects, time allocated for catching-up in case of missed or problematic topics.

Course schedule

  • One 2-hour lesson and one 2-hour lab per week.
  • Students can also receive individual consultations after agreement with an instructor.
  • Time of the lectures and seminars will be dictated by the schedule given by the DCI.

Links

Course completion requirements

Overall assessment consists of “Continuous assessment” (40%) and “Final assessment” (60%).

  • “Continuous assessment” is based on student activity during the labs (20%) and the semester project (20%).
    • Weekly submissions (push) of lab work to the faculty’s Git repository. Completed lab work will be graded by points (20 divided by number of labs with prepared activity). 
    • Semester project will be graded based on weekly activity and on the final result of the project. Students have 10 weeks to finish their projects, 1 point is given for each weekly report about the work and remaining 10 points grade the final result.
  • “Final assessment” consists of an exam in which students will be required to practically process a dataset, which is similar activity as done during the labs. The assessment will also include oral examination of a student about topics covered in the course.

Semester project topics

The selection of semester topics is on Friday at 17:00 CET. For more information, please follow the news on Mattermost.
Výber semestrálnych tém je v piatok o 17:00 SEČ. Ak chcete získať viac informácií, sledujte novinky na Mattermost.

During the semester, besides the lab activities, students work on their projects. Each project is assigned to a pair of students, except when a student continues with the project in the following two semesters as his diploma thesis topic. 

The topics of projects selected for the summer semester 2020/2021 are the following:

Besides these topics, four students working on a diploma thesis related to the analysis of space data:

  • Mapping of cloud and meteorological measurements into observations of Mini-EUSO detector
  • Development of autonomous operation of a full-sky airglow camera
  • Detection of meteors in measurements of Mini-EUSO experiment using machine learning methods
  • Processing of data from EUSO experiments using neural networks

Each semester topic has associated a webpage, which provides additional information, and it will be updated during the semester as students raise questions or some other issues arise. 

Each project is assigned a Mattermost “channel,” which will serve as a forum for discussions and consultations regarding the semester project.

Topics covered in the course

AMON-net

AMON-net is a network of AMON detectors, which are one pixel detectors of the UV background of the atmosphere. The project is managed and developed by the Institute of Experimental Physics of Slovak Academy of Sciences. The project is also supported by two ESA PECS projects. The aim of the lesson and seminar is to familiarize students with popular libraries for data analysis.  The aim is to discuss topics related to data filtration, joining of datasets, visualization, and machine learning (prediction of background variation based on observed data).  The AMON-related topics will also be covered in semester projects.

Astrometry – Gaia

The Gaia is one of the ESA’s large projects, therefore it was considered  as imperative to cover this topic within this course.

The aim of the topic is to familiarize students with Gaia mission, astronomical terms, work with astronomical catalogues, and usage of such data. The attention will be given to usage of the Gaia archive – topics will include TAP, ADQL, Datalink, HEALPix, discussion of the Gaia data model, and visualization of the data. The students will familiarize themselves with astropy, matplotlib, numpy, healpy and other python. Activities will also include work with web-based Gaia Archive, and TOPCAT application. 

Astronomy – Herschel, Hubble Space Telescope

The topic of astronomy is closely related to astrometry, and it is covered as a continuation of the topics examined within the Gaia-related lecture and seminar. Herschel and Hubble Space telescopes will be used to demonstrate concepts related to processing of the astronomical data.

The covered topics include archives of the space telescope data, working with FITS files, HiPS and MOC formats.The students will work with ESASky and Aladin applications.

Students will continue working with the Astropy library. Activities will also include work with the HIPE (Herschel Interactive Processing Environment) application.

Copernicus programme

The Copernicus is the European Union’s flagship Earth Observation and Monitoring programme, in which the ESA is one of the key stakeholders.  

The aim of this topic in the course is to introduce students into the area of Earth monitoring. 

Data access is demonstrated for satellite data and for copernicus services through GUIs and through API. Students should gain experience with handling typical data formats such as NetCDF and GRIB. The activities include programming with popular python libraries such as rasterio, geopandas, cartopy, and also applications in ESA’s SNAP package (Sentinel application platform). The tasks include visualization, classification, and application of models.

Magnetosphere field

The SWARM mission collects data about the Earth’s magnetic field. The geomagnetosphere topic is also investigated by the Institute of Experimental Physics, which makes it more likely to be investigated within diploma students’ theses. The activities include usage of the geomagnetospheric models, downloading and visualization of the actual data, and comparison between models and reality.

Geophysics

The SWARM mission collects data about the Earth’s magnetic field. The geomagnetosphere topic is also investigated by the Institute of Experimental Physics, which makes it more likely to be investigated within diploma students’ theses. The activities include usage of the geomagnetospheric models, downloading and visualization of the actual data, and comparison between models and reality.