BEGIN seminar – Lorena Cristina Abad Crespo
Date: Tuesday 15th October 2024 – 14:00 (UTC+1) –
Time: Online
Slides
Exploring data cubes for vector geometries in R (loreabad6.github.io)
Exploring data cubes for vector geometries in R
Abstract:
Vector data cubes are multi-dimensional data structures. They are different from raster data cubes as instead of having a longitude/latitude or x/y dimensions, they support a geometry as a minimum spatial dimension. Typically, representing data in vector data cubes becomes useful when thematic variables are changing over time at the vector locations, i.e. for spatio-temporal data. For example, time series of temperature, precipitation, wind speed, etc. recorded by climate stations can be represented and analysed using vector data cubes. In R, these data structures are supported in the form of array objects by the {stars} package and as tabular objects with the {cubble} package. This talk will introduce the usage of both packages and will also give a sneak peek to a new package, {post}, which combines the advantages of {stars} and {cubble} to support vector data cubes for polygon geometry time series. Particularly, {post} was created to analyse the evolution of geomorphological features such as landslides, lava flows, and glaciers, which change their geometry over time. However, it can be used to analyse other types of moving and/or changing geometries, for example, urban sprawl.
Bio:
Lorena is a PhD researcher at the Department of Geoinformatics – Z_GIS at the University of Salzburg, Austria, where she is part of the Risk, Hazard & Climate and Earth Observation Analytics research groups. She focuses on the analysis of big Earth observation data to map and monitor landscape dynamics and researches the bridge between EO data cubes and temporal GIS for spatio-temporal analyses.
