xdem.coreg.BlockwiseCoreg

xdem.coreg.BlockwiseCoreg#

class xdem.coreg.BlockwiseCoreg(step, mp_config=None, block_size_fit=500, block_size_apply=500, parent_path=None)[source]#

A processing class of choice is run on a subdivision of the raster. When later applying the step the optimal warping is interpolated based on X/Y/Z shifts from the coreg algorithm at the grid points.

__init__(step, mp_config=None, block_size_fit=500, block_size_apply=500, parent_path=None)[source]#

Instantiate a blockwise processing object for performing coregistration on subdivided DEM tiles.

Parameters:

  • step (Coreg | CoregPipeline) – An instantiated coregistration method or pipeline to apply on each tile.

  • mp_config (MultiprocConfig | None) – Configuration object for multiprocessing

  • block_size_fit (int) – Size of tiles to process per coregistration step in fit step.

  • block_size_apply (int) – Size of tiles to process per coregistration step in apply step.

  • parent_path (str) – Parent path for output files.

Methods

__init__(step[, mp_config, block_size_fit, ...])

Instantiate a blockwise processing object for performing coregistration on subdivided DEM tiles.

apply(to_be_aligned_elev[, ...])

Apply the coregistration transformation to an elevation array using a ransac filter.

fit(reference_elev, to_be_aligned_elev[, ...])

Fit the coregistration model by estimating transformation parameters between the reference and target elevation data.