xdem.spatialstats.spatial_error_propagation

xdem.spatialstats.spatial_error_propagation#

xdem.spatialstats.spatial_error_propagation(areas, errors, params_variogram_model, **kwargs)[source]#

Spatial propagation of elevation errors to an area using the estimated heteroscedasticity and spatial correlations.

This function is based on the number_effective_samples function to estimate uncorrelated samples. If given a vector area, it uses Equation 18 of Hugonnet et al. (2022), https://doi.org/10.1109/jstars.2022.3188922. If given a numeric area, it uses a generalization of Rolstad et al. (2009), http://dx.doi.org/10.3189/002214309789470950.

The standard error SE (1-sigma) is then computed as SE = mean(SD) / Neff, where mean(SD) is the mean of errors in the area of interest which accounts for heteroscedasticity, and Neff is the number of effective samples.

Parameters:
  • areas – Area of interest either as a numeric value of surface in the same unit as the variogram ranges (will assume a circular shape), or as a vector (shapefile) of the area.

  • errors – Errors from heteroscedasticity estimation and modelling, as an array or Raster.

  • params_variogram_model – Dataframe of variogram models to sum with three to four columns, “model” for the model types (e.g., [“spherical”, “matern”]), “range” for the correlation ranges (e.g., [2, 100]), “psill” for the partial sills (e.g., [0.8, 0.2]) and “smooth” for the smoothness parameter if it exists for this model (e.g., [None, 0.2]).

  • kwargs – Keyword argument to pass to the neff_hugonnet_approx function.

Returns:

List of standard errors (1-sigma) for the input areas