sits (version 1.1.0)

sits_geo_dist: Compute the minimum distances among samples and prediction points.

Description

Compute the minimum distances among samples and samples to prediction points, following the approach proposed by Meyer and Pebesma(2022).

Usage

sits_geo_dist(samples, roi = NULL, n = 1000)

Value

A tibble with sample-to-sample and sample-to-prediction distances.

Arguments

samples

A `sits` tibble with time series samples.

roi

A `sf` object (polygon) with a region of interest for prediction.

n

Maximum number of samples to consider.

Author

Alber Sanchez,

Rolf Simoes,

Felipe Carvalho,

Gilberto Camara,

References

Meyer, H., Pebesma, E. "Machine learning-based global maps of ecological variables and the challenge of assessing them", Nature Communications 13, 2208 (2022). https://doi.org/10.1038/s41467-022-29838-9

Examples

if (sits_run_examples()) {
    # read a shapefile for the state of Mato Grosso, Brazil
    mt_shp <- system.file("extdata/shapefiles/mato_grosso/mt.shp",
        package = "sits"
    )
    # convert to an sf object
    mt_sf <- sf::read_sf(mt_shp)
    # calculate sample-to-sample and sample-to-prediction distances
    distances <- sits_geo_dist(samples_modis_4bands, mt_sf)
    # plot sample-to-sample and sample-to-prediction distances
    plot(distances)
}