SC6.10 | Exploring satellite imagery with the Copernicus Browser and the Copernicus Data Space Ecosystem QGIS Plugin
Exploring satellite imagery with the Copernicus Browser and the Copernicus Data Space Ecosystem QGIS Plugin
Co-organized by ESSI6/GM13
Convener: András Zlinszky | Co-convener: Megha Devaraju
Thu, 18 Apr, 08:30–10:15 (CEST)
 
Room -2.85/86
Thu, 08:30
Satellite imagery acquired by the Sentinel satellites can now be openly accessed via a new interface that was launched for easy searching, navigating, visualizing and download of these datasets. The Copernicus Browser provides the tools to quickly visualise satellite imagery, whether individual acquisitions, comparing different dates or even generating timelapses. This course will explain the basics of satellite Earth Observation, introduce the sensors and satellites available and their various applications. In addition to the default visualization options, custom scripts will be introduced for calculating spectral indices and derived products. Advanced image effects and tools and download options will be shown, together with tools for sharing imagery online without downloading. The Copernicus Browser interface for downloading individual images will also be demonstrated, with powerful search and filtering options for finding images of interest.
Additionally, much of the functionality of the Copernicus Browser is also available in a QGIS plugin. In addition to accessing the imagery from the ecosystem, users can also create custom configurations and layers. This plugin will also be demonstrated with practical case studies.
This short course will introduce the functionality of the Copernicus Browser and the Copernicus Data Space Ecosystem QGIS plugin, starting from beginner level and progressing towards the more advanced tools. Participants can follow on their own computers, but the course will be designed also for those without on-site computer access. After the course, participants will be able to search and discover satellite imagery of sites and events of interest, identify algorithms for studying various properties of the imagery, visualize the results, and download or share the resulting products. No prior knowledge of remote sensing or image processing is required.