plot.geo_distances: Make a kernel density plot of samples distances.

In e-sensing/sits: Satellite Image Time Series Analysis for Earth Observation Data Cubes

Make a kernel density plot of samples distances.

Description

Make a kernel density plot of samples distances.

Usage

## S3 method for class 'geo_distances'
plot(x, y, ...)

Arguments

x	Object of class "geo_distances".
y	Ignored.
...	Further specifications for plot.

Value

A plot showing the sample-to-sample distances and sample-to-prediction distances.

Note

Please refer to the sits documentation available in <https://e-sensing.github.io/sitsbook/> for detailed examples.

Author(s)

Felipe Souza, [e-mail]

Rolf Simoes, [e-mail]

Alber Sanchez, [e-mail]

References

Hanna Meyer and Edzer Pebesma, "Machine learning-based global maps of ecological variables and the challenge of assessing them" Nature Communications, 13,2022. DOI: 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_ndvi, mt_sf)
    # plot sample-to-sample and sample-to-prediction distances
    plot(distances)
}

e-sensing/sits documentation built on Jan. 28, 2024, 6:05 a.m.