Vector data cubes for features evolving in space and time

AGILE 2024 - Glasgow, UK - 05.06.2024

Lorena Abad

University of Salzburg

Martin Sudmanns

University of Salzburg

Daniel Hölbling

University of Salzburg

From EO…

to feature outlines

Raster data cubes

Vector data cubes

Vector data cubes

Let’s take a step back…


Vector data cubes are nothing new

Raster data cube

Vector data cube



Vector data cubes in array format

  • Avoids duplicates and excessive columns

  • Allows indexing and lookup

  • Supports data cube operations (filtering, reducing, etc.)

Vector data cubes in tabular format

  • Interlinked space time

  • Nested structure

  • Avoids duplicates

  • Efficient storage

And now, back where we left off…









What can I do with this?

What can I do with this?

  • Structure and analyse spatial features that evolve over time

  • Quantify and visualise changes over time

  • Compute statistics and analyse time series at the object level instead of pixel level

What can I do with this?


  • Experiment with novel visualisations (e.g. glyph plots)

What can I do with this?


  • Integrate and interact with raster data cubes

  • Spatio-temporal cropping and zonal statistic computations using time matching

What is next?

  • Test for multiple geomorphological features

  • Upscaling and performance checks

  • Creating software to work with vector data cube structures for changing geometries

Thank you for your attention!

Questions?

References

Hölbling, Daniel, Lorena Abad, Zahra Dabiri, Prasicek, and Anne-Laure Argentin. 2024. “Butangbunasi Landslide and Landslide-Dammed Lake Outlines Based on Landsat Time Series with Respect to Typhoons.” Zenodo. https://doi.org/10.5281/zenodo.10635102.
Pebesma, Edzer, and Roger Bivand. 2023. Spatial Data Science with Applications in R. Geographical Analysis. 1st ed. Chapman & Hall. https://r-spatial.org/book/.
Pedersen, Gro B. M., Joaquin M. C. Belart, Birgir Vilhelm Óskarsson, Magnús Tumi Gudmundsson, Nils Gies, Thórdís Högnadóttir, Ásta Rut Hjartardóttir, et al. 2023. “Digital Elevation Models, Orthoimages and Lava Outlines of the 2021 Fagradalsfjall Eruption: Results from Near Real-Time Photogrammetric Monitoring.” Zenodo. https://doi.org/10.5281/zenodo.7866738 .
Zhang, H. Sherry, Dianne Cook, Ursula Laa, Nicolas Langrené, and Patricia Menéndez. 2022. “Cubble: An R Package for Organizing and Wrangling Multivariate Spatio-Temporal Data.” http://arxiv.org/pdf/2205.00259.pdf.