ndvi_to_sem — ndvi_to_sem • greenSD

Convert ndvi raster data into semantic vegetation areas

Usage

ndvi_to_sem(r = NULL, threshold = c(0.2, 0.5), quiet = FALSE)

Arguments

r: A SpatRaster with single greenspace layer, typically the output from get_esa_wc(), or get_s2a_ndvi().
threshold: numeric vector of two. Thresholds, defaulting to c(0.2, 0.5), for classify two types of vegetation areas according to Hashim et al. (2019): (1) Non-vegetation (Development and bare land): NDVI values generally below 0.2. (2) Low vegetation (Shrub and grassland): NDVI values generally between 0.2 and 0.5. (2) High vegetation (Temperate and Tropical urban forest ): NDVI values generally between 0.5 and 1.0.
quiet: logical. Whether show progress bars for some process.

Value

SpatRaster. A raster, where 0 represents non-green area, 1 represents shrub and grassland, and 2 represents trees.

References

Hashim, H., Abd Latif, Z., & Adnan, N. A. (2019). Urban vegetation classification with NDVI threshold value method with very high resolution (VHR) Pleiades imagery. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 42, 237-240.

Examples

sample_data <- terra::rast(system.file("extdata", "detroit_gs.tif", package = "greenSD"))
seg <- ndvi_to_sem(sample_data$`25_NDVI`, threshold = c(0.2, 0.6))