Description Usage Arguments Details Value See Also Examples
Tool to support the selection of an adequate satellite temporal resolution. It evaluates how the change in temporal resolution changes the amount of samples and sample regions based on a set of coordinate pairs and their observation dates.
1 | tMoveRes(xy, obs.date, time.res, pixel.res)
|
xy |
Object of class SpatialPoints or SpatialPointsDataFrame. |
obs.date |
Object of class Date with xy observation dates. |
time.res |
Vector of temporal resolutions (expressed in days). |
pixel.res |
Spatial resolution (unit depends on spatial projection). |
Given a base spatial resolution (pixel.res and a vector of temporal resolutions (time.res), the function determines the number of unique pixels and unique pixel regions after their temporal aggregation. For each temporal resolution, the function starts by converting xy to unique pixel coordinates and labels them based on their spatial aggregation. Then, the function counts the number of samples and sample regions. The output of the function consists of:
stats - Summary statistics reporting on the number of temporal widows, unique samples and unique sample regions per temporal resolution.
plot - Plot representing the change in number of samples and sample regions per temporal resolution.
A list object reporting on the amount and distribution of unique pixels and connected pixel regions per temporal resolution.
1 2 3 4 5 6 7 8 9 10 11 12 | {
require(raster)
data(longMove) # access reference data
longMove <- longMove[c(1:50, 2000:2050,3000:3050),] # subset for testing
# test function for intervals of 1, 8 and 16 days (e.g. of MODIS data)
obs.date <- as.Date(longMove@data$timestamp)
a.res <- tMoveRes(longMove, obs.date, c(1,8,16), 0.1)
}
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