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Workshops & Sessions

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New course

10 - 12 June 2024

DSI-NRF CIMERA and the Helmholtz Institute Freiberg for Resource Technology will present a short course in person at the University of the Witwatersrand, Johannesburg, South Africa. This short course forms part of the Expl4Pred collaborative programme.  

   

The short course contains:

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EGU: Conference Session
15 - 19 April 2024

DSI-NRF CIMERA and the Helmholtz Institute Freiberg for Resource Technology will present a short course in person at the University of the Witwatersrand, Johannesburg, South Africa. This short course forms part of the Expl4Pred collaborative programme.  

   

The short course contains:

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The Importance of remote sensing in exploration: Earth Observation tools
30 Jan - 1 Feb 2023

DSI-NRF CIMERA and the Helmholtz Institute Freiberg for Resource Technology presented this short course in person at the University of the Witwatersrand, Johannesburg, South Africa. 

   

The course covered the following topics:

  • Intro to Earth Observation (EO)

  • Intro to SAR and Multispectral data

  • GNSS, LIDAR, photogrammetry and DEMs

  • Intro to hyperspectral data

  • Image processing and spectroscopy

  • Intro to machine learning   

  • Tutorials on: QGIS, data processing, mineral mapping, 

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Earth Observation in the raw material sector
8 - 9 June 2021

EIT RawMaterials, HIF@HZDR, INFACT and TheiaX offered a two-week digital event dedicated to the use of Earth Observation data for the raw material sector. 

   

The Earth Observation in the Raw Materials Sector was a 2-weeks event consisting of 2 short courses running in parallel and culminating with a user forum. The first course, organised by EIT RawMaterials, introduces Earth Observation data processing for beginners. The second series of events is organised by the Helmholtz-Institute Freiberg for Resource Technology (part of Helmholtz-Zentrum Dresden Rossendorf (HZDR)), a start-up, TheiaX, and the H2020 project INFACT. It gave the attendees the opportunity to learn about sustainable exploration, drill-core scanning as well as machine learning methods for Earth Observation. 

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