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Copy path09_pci_haralick_stats_1st.R
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09_pci_haralick_stats_1st.R
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library(hsdar)
library(foreach)
library(doParallel)
setwd("/media/sd19006/data/users/iotte/R-Server/hyperspectral/clean/1st_sd_hara/pci_sd_16/")
filepath_raster <- "/media/sd19006/data/users/iotte/R-Server/hyperspectral/clean/1st_sd_hara/pci_sd_16/"
# one plot aim: all plots
cl <- makeCluster(12)
registerDoParallel(cl)
# vegIndices raster files
fls_hps <- list.files(paste0(filepath_raster), full.names = FALSE,
recursive = FALSE, pattern = "*.tif")
fls_hps_stck <- foreach(i = seq(fls_hps), .packages = "raster") %dopar% {
stack(fls_hps[[i]])
}
#vegindex_names <- vegindex()
#veg <- rep(vegindex_names[c(4,68,87,89)], each = 29)
haralick <- c("smpl_energy", "smpl_entropy", "smpl_correlation", "smpl_inverse_difference_moment",
"smpl_inertia", "smpl_cluster_shade", "smpl_cluster_prominence", "smpl_haralick_correlation",
"adv_mean", "adv_variance", "adv_dissimilarity", "adv_sum_average", "adv_sum_variance",
"adv_sum_entropy", "adv_diff_entropies", "adv_diff_variances", "adv_IC1", "adv_IC2",
"hgr_short_run_emphasis", "hgr_long_run_emphasis", "hgr_grey_level_nonuniformity",
"hgr_run_length_nonuniformity", "hgr_run_percentage", "hgr_low_grey_level_run_emphasis",
"hgr_high_grey_level_run_emphasis", "hgr_short_run_low_grey_level_emphasis",
"hgr_short_run_high_grey_level_emphasis", "hgr_long_run_low_grey_level_emphasis",
"hgr_long_run_high_grey_level_emphasis")
### create colnames
# haralick 10
veg_hara_10_mean <- paste("16", haralick, 10, "mean", sep = "_") #veg
veg_hara_10_sd <- paste("16", haralick, 10, "sd", sep = "_") #veg
veg_hara_10 <- sort(c(veg_hara_10_mean, veg_hara_10_sd))
# haralick 02
veg_hara_02_mean <- paste("16", haralick, 02, "mean", sep = "_")
veg_hara_02_sd <- paste("16", haralick, 02, "sd", sep = "_")
veg_hara_02 <- sort(c(veg_hara_02_mean, veg_hara_02_sd))
# haralick 10
veg_hara_05_mean <- paste("16", haralick, 05, "mean", sep = "_")
veg_hara_05_sd <- paste("16", haralick, 05, "sd", sep = "_")
veg_hara_05 <- sort(c(veg_hara_05_mean, veg_hara_05_sd))
# haralick 30
veg_hara_30_mean <- paste("16", haralick, 30, "mean", sep = "_")
veg_hara_30_sd <- paste("16", haralick, 30, "sd", sep = "_")
veg_hara_30 <- sort(c(veg_hara_30_mean, veg_hara_30_sd))
####
####
# cof1 - 02
fls_hps_1.1 <- fls_hps_stck[[1]]
vegIndex.Vars.cof1 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.1[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.1[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.cof1) <- veg_hara_02
vegIndex.Vars.cof1$plotID <- "cof1"
vegIndex.Vars.cof1 <- vegIndex.Vars.cof1[,c(59,1:58)]
# cof1 - 05
fls_hps_1.2 <- fls_hps_stck[[2]]
vegIndex.Vars.cof1.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.2[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.2[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.cof1.2) <- veg_hara_05
vegIndex.Vars.all <- cbind(vegIndex.Vars.cof1, vegIndex.Vars.cof1.2)
# cof1 - 10
fls_hps_1.3 <- fls_hps_stck[[3]]
vegIndex.Vars.cof1.3 <- foreach(i = 1:nlayers(fls_hps_1.3), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.3[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.3[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.cof1.3) <- veg_hara_10
vegIndex.Vars.all <- cbind(vegIndex.Vars.all, vegIndex.Vars.cof1.3)
# cof1 - 30
fls_hps_1.5 <- fls_hps_stck[[4]]
vegIndex.Vars.cof1.5 <- foreach(i = 1:nlayers(fls_hps_1.5), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.5[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.5[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.cof1.5) <- veg_hara_30
vegIndex.Vars.cof1 <- cbind(vegIndex.Vars.all, vegIndex.Vars.cof1.5)
##
# cof2 - 02
fls_hps_1.1 <- fls_hps_stck[[5]]
vegIndex.Vars.cof2 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.1[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.1[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.cof2) <- veg_hara_02
vegIndex.Vars.cof2$plotID <- "cof2"
vegIndex.Vars.cof2 <- vegIndex.Vars.cof2[,c(59,1:58)]
# cof2 - 05
fls_hps_1.2 <- fls_hps_stck[[6]]
vegIndex.Vars.cof2.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.2[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.2[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.cof2.2) <- veg_hara_05
vegIndex.Vars.all <- cbind(vegIndex.Vars.cof2, vegIndex.Vars.cof2.2)
# cof2 - 10
fls_hps_1.3 <- fls_hps_stck[[7]]
vegIndex.Vars.cof2.3 <- foreach(i = 1:nlayers(fls_hps_1.3), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.3[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.3[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.cof2.3) <- veg_hara_10
vegIndex.Vars.all <- cbind(vegIndex.Vars.all, vegIndex.Vars.cof2.3)
# cof2 - 30
fls_hps_1.5 <- fls_hps_stck[[8]]
vegIndex.Vars.cof2.5 <- foreach(i = 1:nlayers(fls_hps_1.5), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.5[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.5[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.cof2.5) <- veg_hara_30
vegIndex.Vars.cof2 <- cbind(vegIndex.Vars.all, vegIndex.Vars.cof2.5)
vegIndex.Vars <- rbind(vegIndex.Vars.cof1, vegIndex.Vars.cof2)
##
# cof3 - 02
fls_hps_1.1 <- fls_hps_stck[[9]]
vegIndex.Vars.cof3 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.1[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.1[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.cof3) <- veg_hara_02
vegIndex.Vars.cof3$plotID <- "cof3"
vegIndex.Vars.cof3 <- vegIndex.Vars.cof3[,c(59,1:58)]
# cof3 - 05
fls_hps_1.2 <- fls_hps_stck[[10]]
vegIndex.Vars.cof3.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.2[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.2[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.cof3.2) <- veg_hara_05
vegIndex.Vars.all <- cbind(vegIndex.Vars.cof3, vegIndex.Vars.cof3.2)
# cof3 - 10
fls_hps_1.3 <- fls_hps_stck[[11]]
vegIndex.Vars.cof3.3 <- foreach(i = 1:nlayers(fls_hps_1.3), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.3[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.3[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.cof3.3) <- veg_hara_10
vegIndex.Vars.all <- cbind(vegIndex.Vars.all, vegIndex.Vars.cof3.3)
# cof3 - 30
fls_hps_1.5 <- fls_hps_stck[[12]]
vegIndex.Vars.cof3.5 <- foreach(i = 1:nlayers(fls_hps_1.5), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.5[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.5[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.cof3.5) <- veg_hara_30
vegIndex.Vars.cof3 <- cbind(vegIndex.Vars.all, vegIndex.Vars.cof3.5)
vegIndex.Vars <- rbind(vegIndex.Vars, vegIndex.Vars.cof3)
##
# cof4 - 02
fls_hps_1.1 <- fls_hps_stck[[13]]
vegIndex.Vars.cof4 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.1[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.1[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.cof4) <- veg_hara_02
vegIndex.Vars.cof4$plotID <- "cof4"
vegIndex.Vars.cof4 <- vegIndex.Vars.cof4[,c(59, 1:58)]
# cof4 - 05
fls_hps_1.2 <- fls_hps_stck[[14]]
vegIndex.Vars.cof4.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.2[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.2[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.cof4.2) <- veg_hara_05
vegIndex.Vars.all <- cbind(vegIndex.Vars.cof4, vegIndex.Vars.cof4.2)
# cof4 - 10
fls_hps_1.3 <- fls_hps_stck[[15]]
vegIndex.Vars.cof4.3 <- foreach(i = 1:nlayers(fls_hps_1.3), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.3[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.3[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.cof4.3) <- veg_hara_10
vegIndex.Vars.all <- cbind(vegIndex.Vars.all, vegIndex.Vars.cof4.3)
# cof4 - 30
fls_hps_1.5 <- fls_hps_stck[[16]]
vegIndex.Vars.cof4.5 <- foreach(i = 1:nlayers(fls_hps_1.5), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.5[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.5[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.cof4.5) <- veg_hara_30
vegIndex.Vars.cof4 <- cbind(vegIndex.Vars.all, vegIndex.Vars.cof4.5)
vegIndex.Vars <- rbind(vegIndex.Vars, vegIndex.Vars.cof4)
##
# cof5 - 02
fls_hps_1.1 <- fls_hps_stck[[17]]
vegIndex.Vars.cof5 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.1[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.1[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.cof5) <- veg_hara_02
vegIndex.Vars.cof5$plotID <- "cof5"
vegIndex.Vars.cof5 <- vegIndex.Vars.cof5[,c(59,1:58)]
# cof5 - 05
fls_hps_1.2 <- fls_hps_stck[[18]]
vegIndex.Vars.cof5.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.2[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.2[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.cof5.2) <- veg_hara_05
vegIndex.Vars.all <- cbind(vegIndex.Vars.cof5, vegIndex.Vars.cof5.2)
# cof5 - 10
fls_hps_1.3 <- fls_hps_stck[[19]]
vegIndex.Vars.cof5.3 <- foreach(i = 1:nlayers(fls_hps_1.3), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.3[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.3[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.cof5.3) <- veg_hara_10
vegIndex.Vars.all <- cbind(vegIndex.Vars.all, vegIndex.Vars.cof5.3)
# cof5 - 30
fls_hps_1.5 <- fls_hps_stck[[20]]
vegIndex.Vars.cof5.5 <- foreach(i = 1:nlayers(fls_hps_1.5), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.5[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.5[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.cof5.5) <- veg_hara_30
vegIndex.Vars.cof5 <- cbind(vegIndex.Vars.all, vegIndex.Vars.cof5.5)
vegIndex.Vars <- rbind(vegIndex.Vars, vegIndex.Vars.cof5)
##
# flm1 - 02
fls_hps_1.1 <- fls_hps_stck[[21]]
vegIndex.Vars.flm1 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.1[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.1[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.flm1) <- veg_hara_02
vegIndex.Vars.flm1$plotID <- "flm1"
vegIndex.Vars.flm1 <- vegIndex.Vars.flm1[,c(59,1:58)]
# flm1 - 05
fls_hps_1.2 <- fls_hps_stck[[22]]
vegIndex.Vars.flm1.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.2[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.2[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.flm1.2) <- veg_hara_05
vegIndex.Vars.all <- cbind(vegIndex.Vars.flm1, vegIndex.Vars.flm1.2)
# flm1 - 10
fls_hps_1.3 <- fls_hps_stck[[23]]
vegIndex.Vars.flm1.3 <- foreach(i = 1:nlayers(fls_hps_1.3), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.3[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.3[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.flm1.3) <- veg_hara_10
vegIndex.Vars.all <- cbind(vegIndex.Vars.all, vegIndex.Vars.flm1.3)
# flm1 - 30
fls_hps_1.5 <- fls_hps_stck[[24]]
vegIndex.Vars.flm1.5 <- foreach(i = 1:nlayers(fls_hps_1.5), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.5[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.5[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.flm1.5) <- veg_hara_30
vegIndex.Vars.flm1 <- cbind(vegIndex.Vars.all, vegIndex.Vars.flm1.5)
vegIndex.Vars <- rbind(vegIndex.Vars, vegIndex.Vars.flm1)
##
# flm2 - 02
fls_hps_1.1 <- fls_hps_stck[[25]]
vegIndex.Vars.flm2 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.1[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.1[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.flm2) <- veg_hara_02
vegIndex.Vars.flm2$plotID <- "flm2"
vegIndex.Vars.flm2 <- vegIndex.Vars.flm2[,c(59,1:58)]
# flm2 - 05
fls_hps_1.2 <- fls_hps_stck[[26]]
vegIndex.Vars.flm2.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.2[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.2[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.flm2.2) <- veg_hara_05
vegIndex.Vars.all <- cbind(vegIndex.Vars.flm2, vegIndex.Vars.flm2.2)
# flm2 - 10
fls_hps_1.3 <- fls_hps_stck[[27]]
vegIndex.Vars.flm2.3 <- foreach(i = 1:nlayers(fls_hps_1.3), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.3[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.3[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.flm2.3) <- veg_hara_10
vegIndex.Vars.all <- cbind(vegIndex.Vars.all, vegIndex.Vars.flm2.3)
# flm2 - 30
fls_hps_1.5 <- fls_hps_stck[[28]]
vegIndex.Vars.flm2.5 <- foreach(i = 1:nlayers(fls_hps_1.5), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.5[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.5[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.flm2.5) <- veg_hara_30
vegIndex.Vars.flm2 <- cbind(vegIndex.Vars.all, vegIndex.Vars.flm2.5)
vegIndex.Vars <- rbind(vegIndex.Vars, vegIndex.Vars.flm2)
##
# flm3 - 02
fls_hps_1.1 <- fls_hps_stck[[29]]
vegIndex.Vars.flm3 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.1[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.1[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.flm3) <- veg_hara_02
vegIndex.Vars.flm3$plotID <- "flm3"
vegIndex.Vars.flm3 <- vegIndex.Vars.flm3[,c(59,1:58)]
# flm3 - 05
fls_hps_1.2 <- fls_hps_stck[[30]]
vegIndex.Vars.flm3.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.2[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.2[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.flm3.2) <- veg_hara_05
vegIndex.Vars.all <- cbind(vegIndex.Vars.flm3, vegIndex.Vars.flm3.2)
# flm3 - 10
fls_hps_1.3 <- fls_hps_stck[[31]]
vegIndex.Vars.flm3.3 <- foreach(i = 1:nlayers(fls_hps_1.3), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.3[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.3[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.flm3.3) <- veg_hara_10
vegIndex.Vars.all <- cbind(vegIndex.Vars.all, vegIndex.Vars.flm3.3)
# flm3 - 30
fls_hps_1.5 <- fls_hps_stck[[32]]
vegIndex.Vars.flm3.5 <- foreach(i = 1:nlayers(fls_hps_1.5), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.5[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.5[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.flm3.5) <- veg_hara_30
vegIndex.Vars.flm3 <- cbind(vegIndex.Vars.all, vegIndex.Vars.flm3.5)
vegIndex.Vars <- rbind(vegIndex.Vars, vegIndex.Vars.flm3)
##
# flm4 - 02
fls_hps_1.1 <- fls_hps_stck[[33]]
vegIndex.Vars.flm4 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.1[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.1[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.flm4) <- veg_hara_02
vegIndex.Vars.flm4$plotID <- "flm4"
vegIndex.Vars.flm4 <- vegIndex.Vars.flm4[,c(59,1:58)]
# flm4 - 05
fls_hps_1.2 <- fls_hps_stck[[34]]
vegIndex.Vars.flm4.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.2[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.2[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.flm4.2) <- veg_hara_05
vegIndex.Vars.all <- cbind(vegIndex.Vars.flm4, vegIndex.Vars.flm4.2)
# flm4 - 10
fls_hps_1.3 <- fls_hps_stck[[35]]
vegIndex.Vars.flm4.3 <- foreach(i = 1:nlayers(fls_hps_1.3), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.3[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.3[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.flm4.3) <- veg_hara_10
vegIndex.Vars.all <- cbind(vegIndex.Vars.all, vegIndex.Vars.flm4.3)
# flm4 - 30
fls_hps_1.5 <- fls_hps_stck[[36]]
vegIndex.Vars.flm4.5 <- foreach(i = 1:nlayers(fls_hps_1.5), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.5[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.5[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.flm4.5) <- veg_hara_30
vegIndex.Vars.flm4 <- cbind(vegIndex.Vars.all, vegIndex.Vars.flm4.5)
vegIndex.Vars <- rbind(vegIndex.Vars, vegIndex.Vars.flm4)
##
# flm6 - 02
fls_hps_1.1 <- fls_hps_stck[[37]]
vegIndex.Vars.flm6 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.1[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.1[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.flm6) <- veg_hara_02
vegIndex.Vars.flm6$plotID <- "flm6"
vegIndex.Vars.flm6 <- vegIndex.Vars.flm6[,c(59,1:58)]
# flm6 - 05
fls_hps_1.2 <- fls_hps_stck[[38]]
vegIndex.Vars.flm6.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.2[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.2[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.flm6.2) <- veg_hara_05
vegIndex.Vars.all <- cbind(vegIndex.Vars.flm6, vegIndex.Vars.flm6.2)
# flm6 - 10
fls_hps_1.3 <- fls_hps_stck[[39]]
vegIndex.Vars.flm6.3 <- foreach(i = 1:nlayers(fls_hps_1.3), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.3[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.3[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.flm6.3) <- veg_hara_10
vegIndex.Vars.all <- cbind(vegIndex.Vars.all, vegIndex.Vars.flm6.3)
# flm6 - 30
fls_hps_1.5 <- fls_hps_stck[[40]]
vegIndex.Vars.flm6.5 <- foreach(i = 1:nlayers(fls_hps_1.5), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.5[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.5[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.flm6.5) <- veg_hara_30
vegIndex.Vars.flm6 <- cbind(vegIndex.Vars.all, vegIndex.Vars.flm6.5)
vegIndex.Vars <- rbind(vegIndex.Vars, vegIndex.Vars.flm6)
##
# foc1 - 02
fls_hps_1.1 <- fls_hps_stck[[41]]
vegIndex.Vars.foc1 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.1[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.1[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.foc1) <- veg_hara_02
vegIndex.Vars.foc1$plotID <- "foc1"
vegIndex.Vars.foc1 <- vegIndex.Vars.foc1[,c(59,1:58)]
# foc1 - 05
fls_hps_1.2 <- fls_hps_stck[[42]]
vegIndex.Vars.foc1.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.2[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.2[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.foc1.2) <- veg_hara_05
vegIndex.Vars.all <- cbind(vegIndex.Vars.foc1, vegIndex.Vars.foc1.2)
# foc1 - 10
fls_hps_1.3 <- fls_hps_stck[[43]]
vegIndex.Vars.foc1.3 <- foreach(i = 1:nlayers(fls_hps_1.3), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.3[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.3[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.foc1.3) <- veg_hara_10
vegIndex.Vars.all <- cbind(vegIndex.Vars.all, vegIndex.Vars.foc1.3)
# foc1 - 30
fls_hps_1.5 <- fls_hps_stck[[44]]
vegIndex.Vars.foc1.5 <- foreach(i = 1:nlayers(fls_hps_1.5), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.5[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.5[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.foc1.5) <- veg_hara_30
vegIndex.Vars.foc1 <- cbind(vegIndex.Vars.all, vegIndex.Vars.foc1.5)
vegIndex.Vars <- rbind(vegIndex.Vars, vegIndex.Vars.foc1)
##
# foc6 - 02
fls_hps_1.1 <- fls_hps_stck[[45]]
vegIndex.Vars.foc6 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.1[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.1[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.foc6) <- veg_hara_02
vegIndex.Vars.foc6$plotID <- "foc6"
vegIndex.Vars.foc6 <- vegIndex.Vars.foc6[,c(59,1:58)]
# foc6 - 05
fls_hps_1.2 <- fls_hps_stck[[46]]
vegIndex.Vars.foc6.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.2[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.2[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.foc6.2) <- veg_hara_05
vegIndex.Vars.all <- cbind(vegIndex.Vars.foc6, vegIndex.Vars.foc6.2)
# foc6 - 10
fls_hps_1.3 <- fls_hps_stck[[47]]
vegIndex.Vars.foc6.3 <- foreach(i = 1:nlayers(fls_hps_1.3), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.3[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.3[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.foc6.3) <- veg_hara_10
vegIndex.Vars.all <- cbind(vegIndex.Vars.all, vegIndex.Vars.foc6.3)
# foc6 - 30
fls_hps_1.5 <- fls_hps_stck[[48]]
vegIndex.Vars.foc6.5 <- foreach(i = 1:nlayers(fls_hps_1.5), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.5[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.5[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get neames of vegIndices
colnames(vegIndex.Vars.foc6.5) <- veg_hara_30
vegIndex.Vars.foc6 <- cbind(vegIndex.Vars.all, vegIndex.Vars.foc6.5)
vegIndex.Vars <- rbind(vegIndex.Vars, vegIndex.Vars.foc6)
##
# fod5 - 02
fls_hps_1.1 <- fls_hps_stck[[49]]
vegIndex.Vars.fod5 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.1[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.1[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.fod5) <- veg_hara_02
vegIndex.Vars.fod5$plotID <- "fod5"
vegIndex.Vars.fod5 <- vegIndex.Vars.fod5[,c(59,1:58)]
# fod5 - 05
fls_hps_1.2 <- fls_hps_stck[[50]]
vegIndex.Vars.fod5.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.2[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.2[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.fod5.2) <- veg_hara_05
vegIndex.Vars.all <- cbind(vegIndex.Vars.fod5, vegIndex.Vars.fod5.2)
# fod5 - 10
fls_hps_1.3 <- fls_hps_stck[[51]]
vegIndex.Vars.fod5.3 <- foreach(i = 1:nlayers(fls_hps_1.3), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.3[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.3[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.fod5.3) <- veg_hara_10
vegIndex.Vars.all <- cbind(vegIndex.Vars.all, vegIndex.Vars.fod5.3)
# fod5 - 30
fls_hps_1.5 <- fls_hps_stck[[52]]
vegIndex.Vars.fod5.5 <- foreach(i = 1:nlayers(fls_hps_1.5), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.5[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.5[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.fod5.5) <- veg_hara_30
vegIndex.Vars.fod5 <- cbind(vegIndex.Vars.all, vegIndex.Vars.fod5.5)
vegIndex.Vars <- rbind(vegIndex.Vars, vegIndex.Vars.fod5)
##
# gra1 - 02
fls_hps_1.1 <- fls_hps_stck[[53]]
vegIndex.Vars.gra1 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.1[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.1[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.gra1) <- veg_hara_02
vegIndex.Vars.gra1$plotID <- "gra1"
vegIndex.Vars.gra1 <- vegIndex.Vars.gra1[,c(59,1:58)]
# gra1 - 05
fls_hps_1.2 <- fls_hps_stck[[54]]
vegIndex.Vars.gra1.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.2[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.2[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.gra1.2) <- veg_hara_05
vegIndex.Vars.all <- cbind(vegIndex.Vars.gra1, vegIndex.Vars.gra1.2)
# gra1 - 10
fls_hps_1.3 <- fls_hps_stck[[55]]
vegIndex.Vars.gra1.3 <- foreach(i = 1:nlayers(fls_hps_1.3), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.3[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.3[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.gra1.3) <- veg_hara_10
vegIndex.Vars.all <- cbind(vegIndex.Vars.all, vegIndex.Vars.gra1.3)
# gra1 - 30
fls_hps_1.5 <- fls_hps_stck[[56]]
vegIndex.Vars.gra1.5 <- foreach(i = 1:nlayers(fls_hps_1.5), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.5[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.5[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.gra1.5) <- veg_hara_30
vegIndex.Vars.gra1 <- cbind(vegIndex.Vars.all, vegIndex.Vars.gra1.5)
vegIndex.Vars <- rbind(vegIndex.Vars, vegIndex.Vars.gra1)
##
# gra2 - 02
fls_hps_1.1 <- fls_hps_stck[[57]]
vegIndex.Vars.gra2 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.1[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.1[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.gra2) <- veg_hara_02
vegIndex.Vars.gra2$plotID <- "gra2"
vegIndex.Vars.gra2 <- vegIndex.Vars.gra2[,c(59,1:58)]
# gra2 - 05
fls_hps_1.2 <- fls_hps_stck[[58]]
vegIndex.Vars.gra2.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.2[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.2[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.gra2.2) <- veg_hara_05
vegIndex.Vars.all <- cbind(vegIndex.Vars.gra2, vegIndex.Vars.gra2.2)
# gra2 - 10
fls_hps_1.3 <- fls_hps_stck[[59]]
vegIndex.Vars.gra2.3 <- foreach(i = 1:nlayers(fls_hps_1.3), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.3[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.3[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.gra2.3) <- veg_hara_10
vegIndex.Vars.all <- cbind(vegIndex.Vars.all, vegIndex.Vars.gra2.3)
# gra2 - 30
fls_hps_1.5 <- fls_hps_stck[[60]]
vegIndex.Vars.gra2.5 <- foreach(i = 1:nlayers(fls_hps_1.5), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.5[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.5[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.gra2.5) <- veg_hara_30
vegIndex.Vars.gra2 <- cbind(vegIndex.Vars.all, vegIndex.Vars.gra2.5)
vegIndex.Vars <- rbind(vegIndex.Vars, vegIndex.Vars.gra2)
##
# gra3 - 02
fls_hps_1.1 <- fls_hps_stck[[61]]
vegIndex.Vars.gra3 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.1[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.1[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.gra3) <- veg_hara_02
vegIndex.Vars.gra3$plotID <- "gra3"
vegIndex.Vars.gra3 <- vegIndex.Vars.gra3[,c(59,1:58)]
# gra3 - 05
fls_hps_1.2 <- fls_hps_stck[[62]]
vegIndex.Vars.gra3.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.2[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.2[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.gra3.2) <- veg_hara_05
vegIndex.Vars.all <- cbind(vegIndex.Vars.gra3, vegIndex.Vars.gra3.2)
# gra3 - 10
fls_hps_1.3 <- fls_hps_stck[[63]]
vegIndex.Vars.gra3.3 <- foreach(i = 1:nlayers(fls_hps_1.3), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.3[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.3[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.gra3.3) <- veg_hara_10
vegIndex.Vars.all <- cbind(vegIndex.Vars.all, vegIndex.Vars.gra3.3)
# gra3 - 30
fls_hps_1.5 <- fls_hps_stck[[64]]
vegIndex.Vars.gra3.5 <- foreach(i = 1:nlayers(fls_hps_1.5), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.5[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.5[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.gra3.5) <- veg_hara_30
vegIndex.Vars.gra3 <- cbind(vegIndex.Vars.all, vegIndex.Vars.gra3.5)
vegIndex.Vars <- rbind(vegIndex.Vars, vegIndex.Vars.gra3)
##
# gra4 - 02
fls_hps_1.1 <- fls_hps_stck[[65]]
vegIndex.Vars.gra4 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.1[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.1[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.gra4) <- veg_hara_02
vegIndex.Vars.gra4$plotID <- "gra4"
vegIndex.Vars.gra4 <- vegIndex.Vars.gra4[,c(59,1:58)]
# gra4 - 05
fls_hps_1.2 <- fls_hps_stck[[66]]
vegIndex.Vars.gra4.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.2[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.2[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.gra4.2) <- veg_hara_05
vegIndex.Vars.all <- cbind(vegIndex.Vars.gra4, vegIndex.Vars.gra4.2)
# gra4 - 10
fls_hps_1.3 <- fls_hps_stck[[67]]
vegIndex.Vars.gra4.3 <- foreach(i = 1:nlayers(fls_hps_1.3), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.3[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.3[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.gra4.3) <- veg_hara_10
vegIndex.Vars.all <- cbind(vegIndex.Vars.all, vegIndex.Vars.gra4.3)
# gra4 - 30
fls_hps_1.5 <- fls_hps_stck[[68]]
vegIndex.Vars.gra4.5 <- foreach(i = 1:nlayers(fls_hps_1.5), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.5[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.5[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.gra4.5) <- veg_hara_30
vegIndex.Vars.gra4 <- cbind(vegIndex.Vars.all, vegIndex.Vars.gra4.5)
vegIndex.Vars <- rbind(vegIndex.Vars, vegIndex.Vars.gra4)
##
# gra5 - 02
fls_hps_1.1 <- fls_hps_stck[[69]]
vegIndex.Vars.gra5 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.1[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.1[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.gra5) <- veg_hara_02
vegIndex.Vars.gra5$plotID <- "gra5"
vegIndex.Vars.gra5 <- vegIndex.Vars.gra5[,c(59,1:58)]
# gra5 - 05
fls_hps_1.2 <- fls_hps_stck[[70]]
vegIndex.Vars.gra5.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.2[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.2[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.gra5.2) <- veg_hara_05
vegIndex.Vars.all <- cbind(vegIndex.Vars.gra5, vegIndex.Vars.gra5.2)
# gra5 - 10
fls_hps_1.3 <- fls_hps_stck[[71]]
vegIndex.Vars.gra5.3 <- foreach(i = 1:nlayers(fls_hps_1.3), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.3[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.3[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.gra5.3) <- veg_hara_10
vegIndex.Vars.all <- cbind(vegIndex.Vars.all, vegIndex.Vars.gra5.3)
# gra5 - 30
fls_hps_1.5 <- fls_hps_stck[[72]]
vegIndex.Vars.gra5.5 <- foreach(i = 1:nlayers(fls_hps_1.5), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.5[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.5[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.gra5.5) <- veg_hara_30
vegIndex.Vars.gra5 <- cbind(vegIndex.Vars.all, vegIndex.Vars.gra5.5)
vegIndex.Vars <- rbind(vegIndex.Vars,vegIndex.Vars.gra5)
##
# gra6 - 02
fls_hps_1.1 <- fls_hps_stck[[73]]
vegIndex.Vars.gra6 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.1[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.1[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}
# get names of vegIndices
colnames(vegIndex.Vars.gra6) <- veg_hara_02
vegIndex.Vars.gra6$plotID <- "gra6"
vegIndex.Vars.gra6 <- vegIndex.Vars.gra6[,c(59,1:58)]
# gra6 - 05
fls_hps_1.2 <- fls_hps_stck[[74]]
vegIndex.Vars.gra6.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "cbind") %dopar% {
mean <- mean(fls_hps_1.2[[i]][], na.rm = TRUE)
sd <- sd(fls_hps_1.2[[i]][], na.rm = TRUE)
data.frame(mean, sd)
}