Stockholm University 2021
Geocomputation and Machine Learning for environmental applications
06 April - 03 June 2021, 2.00 PM - 4.30 PM
Organizer by Spatial Ecology and the Bolin Center from Climate Research University - Stockholm University
In this course, students will be introduced to an array of powerful open-source geocomputation tools and machine learning methodologies under Linux environment. Students who have never been exposed to programming under linux are expected to reach the stage where they feel confident in using very advanced open source data processing routines. Students with a precedent programming background will find the course beneficial in enhancing their programming skills for better modelling and coding proficiency. Our dual teaching aim is to equip attendees with powerful tools as well as rendering their abilities of continuing independent development afterwards. The acquired skills will be beneficial, not only for GIS related application, but also for general data processing and applied statistical computing in a number of fields. These essentially lay the foundation for career development as a data scientist in the geographic domain.
Lectures
06 April 2021 - Course introduction and objectives
08 April 2021 - OSGeoLive installation, git, and bash introduction
13 April 2021 - Bash and AWK for file manipulation.
15 April 2021 - GDAL\OGR and Data Type.
20 April 2021 - GDAL\OGR and Data Type.
22 April 2021 - PKTOOLS.
27 April 2021 - PKTOOLS for temporal analysis.
29 April 2021 - PKTOOLS for temporal analysis.
04 May 2021 - Student presentation and Machine Learning introduction.
Students: Presenting objectives for the final project
06 May 2021 - Student presentation and Machine Learning.
Students: Presenting objectives for the final project
11 May 2021 - Machine learning.
18 May 2021 - GRASS and Machine learning.
20 May 2021 - Artificial Neural Networks 1.
25 May 2021 - Artificial Neural Networks 2.
27 May 2021 - Artificial Neural Networks 3.
03 June 2021 - Student Presentations.