tMoveRes: tMoveRes

In RRemelgado/rsMove: Guidelines for the use of Remote Sensing in Movement Ecology

tMoveRes

Description

Analysis of GPS data losses with the choice temporal resolutions.

Usage

tMoveRes(x, y, time.res, pixel.res)

Arguments

x	spatVector.
y	Date vector with observation dates or each entry in x.
time.res	Vector of temporal resolutions (expressed in days).
pixel.res	Spatial resolution (unit depends on spatial projection).

Details

For each spatial resolution given by pixel.res, and for each temporal resolutions given by time.res, the function simulates the number of unique pixels and pixel regions preserved after accounting for pseudo-replication at each hypothetical time step, assuming that the GPS data until the next date with available environmental data is aggregated into unique pixels. Finally, For each temporal aggregation window, the function reports the 'pixel ratio' and the 'region ratio', i.e., the number of pixels and regions divided by the number of GPS records.

Value

A list containing:

• stats - Summary statistics reporting on the number of temporal widows, unique samples and unique sample regions per temporal resolution.

• summary.plot - Plot representing the change in number of unique pixels and pixel regions per temporal resolution.

• temporal.plot - Plot representing the change in number of unique pixels and pixel regions per temporal resolution and time step.

See Also

sMoveRes

Examples

{

 require(terra)

 #'  # read movement data
 longMove = read.csv(system.file('extdata',
 'longMove.csv', package="rsMove"))

 # convert observations to vector
 longMove = vect(longMove, geom=c("long","lat"), crs="EPSG:4326")

 # test function for intervals of 1, 8 and 16 days (e.g. of MODIS data)
 obs.date = as.Date(longMove$timestamp)
 a.res = tMoveRes(longMove, obs.date, c(1,8,16), 0.1)

}

RRemelgado/rsMove documentation built on June 3, 2024, 10:07 p.m.