Stress field and wavelength analysis using a kernel (weighted) mean/median and standard deviation/IQR of stress data
Usage
stress2grid(
x,
stat = c("mean", "median"),
grid = NULL,
lon_range = NULL,
lat_range = NULL,
gridsize = 2.5,
min_data = 3,
threshold = 25,
arte_thres = 200,
method_weighting = FALSE,
quality_weighting = TRUE,
dist_weight = c("inverse", "linear", "none"),
dist_threshold = 0.1,
R_range = seq(50, 1000, 50),
...
)
Arguments
- x
sf
object containing- azi
SHmax in degree
- unc
Uncertainties of SHmax in degree
- type
Methods used for the determination of the direction of SHmax
- stat
Should the direction of interpolated SHmax be based on the circular mean and standard deviation (
"mean"
, the default) or on the circular median and interquartile range ("median"
)?- grid
(optional) Point object of class
sf
.- lon_range, lat_range
(optional) numeric vector specifying the minimum and maximum longitudes and latitudes (are 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. Minimum number of data per bin. Default is 3
- threshold
Numeric. Threshold for deviation of direction. Default is 25
- arte_thres
Numeric. Maximum distance (in km) of the grid point to the nextdata point. Default is 200
- method_weighting
Logical. If a method weighting should be applied: Default is
FALSE
.- quality_weighting
Logical. If a quality weighting should be applied: Default is
TRUE
.- dist_weight
Distance weighting method which should be used. One of
"none"
,"linear"
, or"inverse"
(the default).- 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), i.e. the search radius (in km). Default is
seq(50, 1000, 50)
- ...
optional arguments to
dist_greatcircle()
Value
sf
object containing
- lon,lat
longitude and latitude in degrees
- azi
Mean SHmax in degree
- sd
Standard deviation of SHmax in degrees
- R
Search radius in km
- mdr
Mean distance of datapoints per search radius
- N
Number of data points in search radius
References
Ziegler, M. O. and Heidbach, O. (2019). Matlab Script Stress2Grid v1.1. GFZ Data Services. doi:10.5880/wsm.2019.002
Examples
data("san_andreas")
stress2grid(san_andreas)
#> Simple feature collection with 671 features and 7 fields
#> Geometry type: POINT
#> Dimension: XY
#> Bounding box: xmin: -124.57 ymin: 24.33 xmax: -107.07 ymax: 39.33
#> Geodetic CRS: WGS 84
#> # A tibble: 671 × 8
#> # Groups: R [20]
#> lon lat azi sd R mdr N geometry
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int> <POINT [°]>
#> 1 -115. 24.3 NA 0 50 NA 0 (-114.57 24.33)
#> 2 -115. 24.3 NA 0 100 NA 0 (-114.57 24.33)
#> 3 -115. 24.3 NA 0 150 NA 0 (-114.57 24.33)
#> 4 -115. 24.3 NA 0 200 NA 1 (-114.57 24.33)
#> 5 -115. 24.3 179. 5.32 250 0.820 3 (-114.57 24.33)
#> 6 -115. 24.3 170. 25.0 350 0.796 9 (-114.57 24.33)
#> 7 -115. 24.3 168. 19.3 400 0.816 18 (-114.57 24.33)
#> 8 -115. 24.3 171. 14.8 450 0.884 56 (-114.57 24.33)
#> 9 -115. 24.3 171. 16.3 500 0.876 107 (-114.57 24.33)
#> 10 -115. 24.3 171. 15.5 550 0.832 139 (-114.57 24.33)
#> # ℹ 661 more rows