HRDS: A Python package for hierarchical raster datasets
Jon Hill · The Journal of Open Source Software · 2019
Multi-scale modelling of geophysical domains requires data, such as bathymetry or topography to set up the initial conditions.These data are typically in the form of GIS rasters and can be derived from a number of sources.A single data source is commonly used which has a fixed spatial resolution.However, in multiscale models, e.g.Martin-Short et al. (2015), the spatial scale of the model can vary by four or more orders of magnitude, e.g. from kilometre-to sub-metre-scale.In order to use the high resolution data set in the area of highest model resolution this limited-area highest resolution data must be blended with a wider area coarse resolution dataset.A choice therefore has to be made to either sacrifice some resolution or create a very large data file.For a wide region zooming into metre-scale processes this data file could be terabytes in size when re-sampled at the resolution of the highest resolution dataset.This problem is particularly acute when using GIS tools such as qmesh (A. Avdis, Candy, Hill, Kramer, & Piggott, 2018) to generate meshes from contours or other derivatives of the raster data.