References

Solid Earth

1869-9529

Copernicus Publications

Göttingen, Germany

10.5194/se-5-741-2014

Plate tectonic raster reconstruction in GPlates

Cannon

https://orcid.org/0000-0003-4749-5605

¹ Lau

¹ ² Müller

R. D.

https://orcid.org/0000-0002-3334-5764

EarthByte Group, School of Geosciences, University of Sydney, Australia

now at: Google, Sydney, Australia

01 08 2014

5 2 741 755

2014

This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/3.0/

This article is available from https://se.copernicus.org/articles/5/741/2014/se-5-741-2014.html

The full text article is available as a PDF file from https://se.copernicus.org/articles/5/741/2014/se-5-741-2014.pdf

We describe a novel method implemented in the GPlates plate tectonic reconstruction software to interactively reconstruct arbitrarily high-resolution raster data to past geological times using a rotation model. The approach is based on the projection of geo-referenced raster data into a cube map followed by a reverse projection onto rotated tectonic plates on the surface of the globe. This decouples the rendering of a geo-referenced raster from its reconstruction, providing a number of benefits including a simple implementation and the ability to combine rasters with different geo-referencing or inbuilt raster projections. The cube map projection is accelerated by graphics hardware in a wide variety of computer systems manufactured over the last decade. Furthermore, by integrating a multi-resolution tile partitioning into the cube map we can provide on-demand tile streaming, level-of-detail rendering and hierarchical visibility culling, enabling researchers to visually explore essentially unlimited resolution geophysical raster data attached to tectonic plates and reconstructed through geological time. This capability forms the basis for interactively building and improving plate reconstructions in an iterative fashion, particularly for tectonically complex regions.

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