pvts_mosaicfreecloud: Get the best Available Pixel on an Image Collection

In pvts-approach/PVts: photosynthetic vegetation time series manipulation in R.

Description

A three-step algorithm for creating a mosaic from satellite imagery (see notes).

Usage

pvts_mosaicfreecloud(x, time, CLUSTER = NULL, fit_negative = TRUE,
  RasterLayer = TRUE)

Arguments

x	filename(character), Raster* or star object (see read_stars).
time	Date or character vector with the dates of the files.
CLUSTER	cluster to use for parallel apply; see makeCluster.
fit_negative	logical; if TRUE, negative values are replace by NA.
RasterLayer	logical; if TRUE, return a RasterLayer object.

Note

The three steps are:

• Chooses the image less affected by atmospheric noise.

• Calculate the time gap between the image selected in step one to the remaining images.

• Take the clean pixels considering the shortest time gap and ending with the image most temporally distant.

Please see Tarazona et al. (2018) for more details.

Examples

library(PVts)
library(raster)
data(pvts_datasets)

x <- pvts_datasets$mosaic[,1:100,1:100]
time <- as.Date(c("2016-07-30","2016-08-15","2016-09-16"))
simple_mean <- x %>%
 st_apply(1:2,mean) %>%
 as('Raster')
 f1 <- pvts_mosaicfreecloud(x,time)
group_img <- stack(simple_mean,f1)
names(group_img) <- c('Simple mean','MosaicFreeCloud')
plot(group_img)

pvts-approach/PVts documentation built on July 1, 2019, 4:59 p.m.