The advent of cloud computing has revolutionised the capabilities of researchers and professionals globally, helping them to access and analyse Earth observation (EO) data more easily than ever. Despite the well-understood tools and technologies, such as cloud-optimised GeoTIFFs (COG) and the Spatio-Temporal Asset Catalog (STAC) and STAC API specifications, many EO professionals have not yet had the opportunity to practically apply these innovations. This workshop aims to bridge that gap by showcasing how cloud-native geospatial technologies simplify the process of working with EO data, using Python as the primary programming language.

In part one of the workshop, we’ll talk about Al Gore’s vision for a digital Earth, and how we’re on the path to realising that vision, before we get hands-on coding a Earth observation data science notebook from scratch, loading and visualising Landsat data.

In part two, we’ll talk about Cloud Native Geospatial and what it means for data access and then we’ll shift over to another example of a long time series of sea-surface temperature data, accessed from Source Coop, before concluding with a discussion session.

Throughout the workshop, participants will gain hands-on experience and insights into how cloud-native geospatial technologies have significantly enhanced the ability to access and analyze large volumes of EO data. By the end of the session, attendees will have acquired practical examples and knowledge to further develop their skills in this innovative field.