Module 3: Accessing and working with spatial evidence
Finding data, choosing tools, and getting ready to practise
Through Modules 1 and 2, we introduce spatial evidence for effective restoration decision-making, how it is generated and evaluated. In Module 3, we’ll explore how to find and access spatial data, the different tools that can be used, how to set up a robust workflow, and hands-on practice through notebooks.
Focusing on GGW-specific datasets (generated through the K4GGWA evidence pipeline we saw in 2.1) available through our open-data infrastructure, and R as the main tool, learners will gain practical experience in working with spatial evidence for restoration decision-making.
In this module
Explore the growing landscape of open spatial data, what a STAC is and how it works, and our STAC-based catalogue for easy discoverability and access to GGW datasets.
Compare the different tools available for working with spatial data and get set up with R and RStudio.
Build good habits for organising projects and files, follow a general workflow for approaching any spatial data task from framing the question through to data access, and generate evidence.
What you will learn
By the end of Module 3, you should be able to:
Describe the current landscape for accessing spatial data, including the shift toward open, cloud-based data and the role of STAC as a common discovery standard.
Explain what a STAC catalog is, and locate and browse the K4GGWA GGW collection.
Compare the main types of tools available for working with spatial data, and explain why this hub uses R.
Install and set up R and RStudio, ready to start working with data.
Apply good project and file organisation habits, and follow a general workflow for approaching a spatial data task.
Locate the practical notebooks in the tutorial gallery, and know how to get started with them.