Terrain Ruggedness Index

Source: R/tri.R

Implementation of the Riley et al (1999) Terrain Ruggedness Index

The algebraic approximation is considerably faster. However, because inclusion of the center cell, the larger the scale the larger the divergence of the minimum value.

Recommended ranges for classifying Topographic Ruggedness Index:

  • 0-80 - level terrain surface.

  • 81-116 - nearly level surface.

  • 117-161 - slightly rugged surface.

  • 162-239 - intermediately rugged surface.

  • 240-497 - moderately rugged surface.

  • 498-958 - highly rugged surface.

  • gt 959 - extremely rugged surface.

tri(r, s = 3, exact = TRUE, file.name = NULL, ...)

Arguments

r

RasterLayer class object
s

Scale of window. Must be odd number, can represent 2 dimensions (eg., s=c(3,5) would represent a 3 x 5 window)
exact

Calculate (TRUE/FALSE) the exact TRI or an algebraic approximation.
file.name

Name of output raster (optional)
...

Additional arguments passed to writeRaster

Value

raster class object or raster written to disk

References

Riley, S.J., S.D. DeGloria and R. Elliot (1999) A terrain ruggedness index that quantifies topographic heterogeneity, Intermountain Journal of Sciences 5(1-4):23-27.

Author

Jeffrey S. Evans jeffrey_evans@tnc.org

Examples

# \donttest{
 library(raster)
 data(elev)
  ( tri.ext <- tri(elev) )

#> class      : RasterLayer 
#> dimensions : 6, 6, 36  (nrow, ncol, ncell)
#> resolution : 0.5, 0.5  (x, y)
#> extent     : -1.5, 1.5, -1.5, 1.5  (xmin, xmax, ymin, ymax)
#> crs        : +proj=longlat +datum=WGS84 +ellps=WGS84 +towgs84=0,0,0 
#> source     : memory
#> names      : layer 
#> values     : 14.89966, 14.89966  (min, max)
#> 
  ( tri.app <- tri(elev, exact = FALSE) )

#> class      : RasterLayer 
#> dimensions : 6, 6, 36  (nrow, ncol, ncell)
#> resolution : 0.5, 0.5  (x, y)
#> extent     : -1.5, 1.5, -1.5, 1.5  (xmin, xmax, ymin, ymax)
#> crs        : +proj=longlat +datum=WGS84 +ellps=WGS84 +towgs84=0,0,0 
#> source     : memory
#> names      : layer 
#> values     : 14.89966, 14.89966  (min, max)
#> 
  plot(stack(tri.ext, tri.app))

# }