timeDir: timeDir

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

timeDir

Description

Analysis of environmental change in time for a set of coordinate pairs.

Usage

timeDir(x, x.dates, y, y.dates, temporal.buffer, fun = NULL, min.count = 2)

Arguments

x	Object of class SpatRaster.
x.dates	Object of class Date with observation dates of y.
y	Object of class SpatVector.
y.dates	Object of class Date with observation dates of y.
temporal.buffer	two element vector with temporal window size (expressed in days).
fun	List of statistical function to apply to the data.
min.count	Minimum number of samples required by stat.fun. Default is 2.

Details

This function quantifies environmental changes in time for each GPS entry along a movement track. First, for each point in y, the function compares its observation date (y.dates) against the dates with environmental data (x.dates), and preserves those entries in x that fall within the temporal.buffer. The user can adjust this window to determine which images are the most important. For example, if one wishes to know how the landscape evolved up to the observation date of the target sample, temporal.buffer can be define as, e.g., c(30,0) forcing the function to only consider pixels recorded within the previous 30 days. After selecting adequate temporal information for each data point, a list of user-defined statistical metrics are calculated (i.e., fun).

Value

A data.frame with statistics at each GPS observation. In addition the user defined statistics, the table will contain several entries describing the data used to calculate those statistics:

• distance_traveled - Total distance traveled between all observations

• elapsed_time - Time between the first and last observation

• nr_observations - nr_observations

• pixel_value - Pixel value at the main observation

See Also

spaceDir

Examples

{

 require(terra)

 # read raster data
 file <- list.files(system.file('extdata', '', package="rsMove"), 'ndvi.tif', full.names=TRUE)
 r.stk <- rast(file)
 r.stk <- c(r.stk, r.stk, r.stk) # dummy files for the example

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

 # convert observations to vector
 shortMove = vect(shortMove, geom=c("x","y"), crs="EPSG:32632")

 # raster dates
 r.dates <- seq.Date(as.Date("2013-08-01"), as.Date("2013-08-09"), 1)

 # sample dates
 obs.dates <- as.Date(shortMove$date)

 # perform directional sampling
 functions <- list(
    slope=function(x,y) lm(y~x)$coefficients[2][[1]],
    mean=function(x,y) mean(y, na.rm=T),
    sd=function(x,y) sd(y, na.rm=T)
 )
 time.env <- timeDir(r.stk, r.dates, shortMove, obs.dates, 3, fun=functions)

}

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