QGIS is one of the most used desktop software for geospatial data management, analysis and visualisation. This entity provides the basics for using QGIS for the first time, or refreshing memory of the software interface and functionalities.
DIDAIhub: Getting started with QGIS Read More »
This mini-MOOC provides an overview of different phases of the data analysis pipeline using Python and its data analysis ecosystem with GDAL.
DIDAIhub: Processing large raster images in GDAL Read More »
This mini-MOOC focuses on competencies in adding, organizing, querying, retrieving, and combining data, and assessing data consistency with the help of the SQL tools in the DBMS and in QGIS.
DIDAIhub: Geospatial data management in postgres/postgis databases Read More »
Learn to define the concept of open data, and how to discover and use it as a research resource. Learn about about terms and conditions of accessing and using open data,as well as practical measures which help to decide whether to share data openly or not, and what part of it could be shared openly.
DIDAIhub: Principles of Open Data Read More »
Understand the basics of geometric and statistical properties and nature of geospatial data. Learn the skills to operate common analysis of geometric properties and basic statistics in QGIS. Gain deeper understanding on the nature and possibilities & limitation of geospatial data.
DIDAIhub: Geometries of geospatial data and basic statistics Read More »
Learn principles of Spatial Data Infrastructures (SDIs) and practical skills in using SDIs and sharing your own data via Climate Risk Database.
Resilience Academy: Data sharing in Climate Risk Database Read More »
Learn principles and practical skills to use metadata standards for good quality geospatial data management. After completing the module, you are able to use metadata standards based on ISO19115 and recommendations of the OSGEO, and you are skilled in creating and evaluating the data quality based on metadata, as well as creating metadata of your
Resilience Academy: Metadata Read More »
Learn the principles, hands-on skills and good practices of assessing geospatial data quality, using geospatial data of different origin and characteristics. Practicals utilise datasets from Climate Risk Database.
Resilience Academy: Geospatial data quality Read More »