tectonicr (version 0.4.8)

stress2grid: Spatial Interpolation of SHmax

Description

Stress field interpolation and wavelength analysis using a kernel (weighted) mean/median and standard deviation/IQR of stress data. Parameters can be adjusted to have inverse-distance-weighting (IDW) or nearest-neighbor interpolations (NN).

Usage

stress2grid(
  x,
  stat = c("mean", "median", "tensor"),
  grid = NULL,
  lon_range = NULL,
  lat_range = NULL,
  gridsize = 2,
  min_data = 3L,
  max_data = Inf,
  max_sd = Inf,
  threshold = deprecated(),
  min_dist_threshold = 200,
  arte_thres = deprecated(),
  method_weighting = FALSE,
  quality_weighting = TRUE,
  dist_weighting = c("inverse", "linear", "none"),
  idp = 1,
  qp = 1,
  mp = 1,
  dist_threshold = 0.1,
  R_range = seq(50, 1000, 50),
  ...
)
stress2grid_stats(
  x,
  grid = NULL,
  lon_range = NULL,
  lat_range = NULL,
  gridsize = 2,
  min_data = 4L,
  max_data = Inf,
  threshold = deprecated(),
  min_dist_threshold = 200,
  arte_thres = deprecated(),
  method_weighting = FALSE,
  quality_weighting = TRUE,
  dist_weighting = c("inverse", "linear", "none"),
  idp = 1,
  qp = 1,
  mp = 1,
  dist_threshold = 0.1,
  R_range = seq(50, 1000, 50),
  mode = FALSE,
  kappa = 10,
  ...
)

Value

sf object containing

lon,lat

longitude and latitude in degrees

azi

Circular mean od median SHmax in degree

sd

Circular standard deviation or Quasi-IQR on the Circle of SHmax in degrees

R

Search radius in km

mdr

Mean distance between grid point and datapoints per search radius

N

Number of data points in search radius

When stress2grid_stats(), azi and sd are replaced by the output of circular_summary().

Arguments

x

sf object containing

azi

SHmax in degree

unc

(optional) Uncertainties of SHmax in degree

type

(optional) Methods used for the determination of the direction of SHmax

stat

whether the direction of interpolated SHmax is based on the circular mean and standard deviation ("mean", the default), the quasi-circular median and quasi-interquartile range ("median"), or the orientation tensor based principal direction and dispersion ("tensor").

grid

(optional) Point object of class sf.

lon_range, lat_range

(optional) numeric vector specifying the minimum and maximum longitudes and latitudes (ignored if grid is specified).

gridsize

numeric. Target spacing of the regular grid in decimal degree. Default is 2.5. (is ignored if grid is specified)

min_data

integer. If the number of observations within distance R_range is less than min_data, a missing value NA will be generated. Default is 3 for stress2grid() and 4 for stress2grid_stats().

max_data

integer. The number of nearest observations that should be used for prediction, where "nearest" is defined in terms of the space of the spatial locations. Default is Inf.

max_sd

numeric. Threshold for deviation of direction in degrees; if exceeds, missing values will be generated.

threshold

is no longer supported; use max_sd instead.

min_dist_threshold

numeric. Distance threshold for smallest distance of the prediction location to the next observation location. Default is 200 km.

arte_thres

is no longer supported; use min_dist_threshold instead.

method_weighting

logical. If a method weighting should be applied: Default is FALSE. If FALSE, overwrites mp.

quality_weighting

logical. If a quality weighting should be applied: Default is TRUE. If FALSE, overwrites qp.

dist_weighting

Distance weighting method which should be used. One of "none", "linear", or "inverse" (the default).

idp, qp, mp

numeric. The weighting power of inverse distance, quality and method (the higher the value, the more weight). Default is 1. When set to 0, no weighting is applied. Only effective when dist_weighting=="inverse".

dist_threshold

numeric. Distance weight to prevent overweight of data nearby (0 to 1). Default is 0.1

R_range

numeric value or vector specifying the kernel half-width(s) search radii, i.e. the maximum distance from the prediction location to be used for prediction (in km). Default is seq(50, 1000, 50). If combined with max_data, both criteria apply.

...

(optional) arguments to dist_greatcircle()

mode

logical. Should the circular mode be included in the statistical summary (slow)?

kappa

numeric. von Mises distribution concentration parameter used for the circular mode. Will be estimated using est.kappa() if not provided.

Details

stress2grid() is originally based on the MATLAB script "stress2grid" by Ziegler and Heidbach (2019): https://github.com/MorZieg/Stress2Grid. The tectonicr version has been significantly modified to provide better performance and more flexibility.

stress2grid_stats() is based on stress2grid() but calculates circular summary statistics (see circular_summary()).

References

Ziegler, M. and Heidbach, O. (2019). Matlab Script Stress2Grid v1.1. GFZ Data Services. tools:::Rd_expr_doi("10.5880/wsm.2019.002")

See Also

dist_greatcircle(), PoR_stress2grid(), compact_grid(), circular_mean(), circular_median(), circular_sd(), circular_summary()

Examples

data("san_andreas")

# Inverse Distance Weighting interpolation:
stress2grid(san_andreas, stat = "median") |> head()

stress2grid(san_andreas, stat = "tensor") |> head()

# Nearest Neighbor interpolation:
stress2grid(san_andreas, stat = "median", max_data = 5) |> head()

if (FALSE) {
stress2grid_stats(san_andreas) |> head()
}