mapme.biodiversity (version 0.9.3)

tri: Calculate Terrain Ruggedness Index (TRI) statistics

Description

Terrain Ruggedness Index is a measurement developed by Riley, et al. (1999). The elevation difference between the centre pixel and its eight immediate pixels are squared and then averaged and its square root is taken to get the TRI value. This function allows to calculate terrain ruggedness index (tri) statistics for polygons. For each polygon, the desired statistic(s) are returned.

Usage

calc_tri(engine = "extract", stats = "mean")

Value

A function that returns an indicator tibble with tri as variable and the respective statistic as value.

Arguments

engine

The preferred processing functions from either one of "zonal", "extract" or "exactextract" as character.

stats

Function to be applied to compute statistics for polygons either single or multiple inputs as character. Supported statistics are: "mean", "median", "sd", "min", "max", "sum" "var".

Details

The range of index values and corresponding meaning:

• 0-80 m - level surface

• 81-116 m - nearly level surface

• 117-161 m - slightly rugged surface

• 162-239 m - intermediately rugged surface

• 240-497 m - moderately rugged surface

• 498-958 m - highly rugged surface

• 959-4367 m extremely rugged surface

The required resources for this indicator are:

• nasa_srtm

References

Riley, S. J., DeGloria, S. D., & Elliot, R. (1999). Index that quantifies topographic heterogeneity. Intermountain Journal of Sciences, 5(1-4), 23-27.

Examples

# \dontshow{
mapme.biodiversity:::.copy_resource_dir(file.path(tempdir(), "mapme-data"))
# }
if (FALSE) {
library(sf)
library(mapme.biodiversity)

outdir <- file.path(tempdir(), "mapme-data")
dir.create(outdir, showWarnings = FALSE)

mapme_options(
  outdir = outdir,
  verbose = FALSE
)

aoi <- system.file("extdata", "sierra_de_neiba_478140_2.gpkg",
  package = "mapme.biodiversity"
) %>%
  read_sf() %>%
  get_resources(get_nasa_srtm()) %>%
  calc_indicators(
    calc_tri(stats = c("mean", "median", "sd", "var"), engine = "extract")
  ) %>%
  portfolio_long()

aoi
}