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09_haralick_stats_mod_2nd.R
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09_haralick_stats_mod_2nd.R
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library(hsdar)
library(foreach)
library(doParallel)
setwd("/media/sd19006/data/users/iotte/R-Server/hyperspectral/clean/2nd/norm_441/re_norm/pca/pca_inverse/pci_vegIndex/pci_vegIndex_hara/pci_vegIndex_hara_dia_50m/")
filepath_raster <- "/media/sd19006/data/users/iotte/R-Server/hyperspectral/clean/2nd/norm_441/re_norm/pca/pca_inverse/pci_vegIndex/pci_vegIndex_hara/pci_vegIndex_hara_dia_50m/"
# vegIndices raster files
fls_hps <- list.files(paste0(filepath_raster), full.names = FALSE,
recursive = FALSE, pattern = "*dia_50m.tif")
fls_hps_stck <- lapply(seq(fls_hps), function(i){
stack(fls_hps[[i]])
})
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")
# one plot aim: all plots
cl <- makeCluster(detectCores() - 10)
registerDoParallel(cl)
# fed1 - 10
fls_hps_1.1 <- fls_hps_stck[[1]]
vegIndex.Vars.fed1 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "rbind") %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
vegindex_names <- vegindex()
vegIndex.Vars.fed1$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fed1$haralick <- haralick
vegIndex.Vars.fed1$xyrad <- "10"
vegIndex.Vars.fed1$plotID <- "fed1"
# fed1 - 2
fls_hps_1.2 <- fls_hps_stck[[2]]
vegIndex.Vars.fed1.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.fed1.2$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fed1.2$haralick <- haralick
vegIndex.Vars.fed1.2$xyrad <- "02"
vegIndex.Vars.fed1.2$plotID <- "fed1"
vegIndex.Vars.all <- rbind(vegIndex.Vars.fed1, vegIndex.Vars.fed1.2)
# fed1 - 30
fls_hps_1.3 <- fls_hps_stck[[3]]
vegIndex.Vars.fed1.3 <- foreach(i = 1:nlayers(fls_hps_1.3), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.fed1.3$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fed1.3$haralick <- haralick
vegIndex.Vars.fed1.3$xyrad <- "30"
vegIndex.Vars.fed1.3$plotID <- "fed1"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fed1.3)
# fed1 - 5
fls_hps_1.5 <- fls_hps_stck[[4]]
vegIndex.Vars.fed1.5 <- foreach(i = 1:nlayers(fls_hps_1.5), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.fed1.5$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fed1.5$haralick <- haralick
vegIndex.Vars.fed1.5$xyrad <- "05"
vegIndex.Vars.fed1.5$plotID <- "fed1"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fed1.5)
##
# fed2 - 10
fls_hps_1.1 <- fls_hps_stck[[5]]
vegIndex.Vars.fed2 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "rbind") %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
vegindex_names <- vegindex()
vegIndex.Vars.fed2$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fed2$haralick <- haralick
vegIndex.Vars.fed2$xyrad <- "10"
vegIndex.Vars.fed2$plotID <- "fed2"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fed2)
# fed2 - 2
fls_hps_1.2 <- fls_hps_stck[[6]]
vegIndex.Vars.fed2.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.fed2.2$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fed2.2$haralick <- haralick
vegIndex.Vars.fed2.2$xyrad <- "02"
vegIndex.Vars.fed2.2$plotID <- "fed2"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fed2.2)
# fed2 - 30
fls_hps_1.3 <- fls_hps_stck[[7]]
vegIndex.Vars.fed2.3 <- foreach(i = 1:nlayers(fls_hps_1.3), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.fed2.3$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fed2.3$haralick <- haralick
vegIndex.Vars.fed2.3$xyrad <- "30"
vegIndex.Vars.fed2.3$plotID <- "fed2"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fed2.3)
# fed2 - 5
fls_hps_1.5 <- fls_hps_stck[[8]]
vegIndex.Vars.fed2.5 <- foreach(i = 1:nlayers(fls_hps_1.5), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.fed2.5$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fed2.5$haralick <- haralick
vegIndex.Vars.fed2.5$xyrad <- "05"
vegIndex.Vars.fed2.5$plotID <- "fed2"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fed2.5)
##
# fed3 - 10
fls_hps_1.1 <- fls_hps_stck[[9]]
vegIndex.Vars.fed3 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "rbind") %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
vegindex_names <- vegindex()
vegIndex.Vars.fed3$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fed3$haralick <- haralick
vegIndex.Vars.fed3$xyrad <- "10"
vegIndex.Vars.fed3$plotID <- "fed3"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fed3)
# fed3 - 2
fls_hps_1.2 <- fls_hps_stck[[10]]
vegIndex.Vars.fed3.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.fed3.2$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fed3.2$haralick <- haralick
vegIndex.Vars.fed3.2$xyrad <- "02"
vegIndex.Vars.fed3.2$plotID <- "fed3"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fed3.2)
# fed3 - 30
fls_hps_1.3 <- fls_hps_stck[[11]]
vegIndex.Vars.fed3.3 <- foreach(i = 1:nlayers(fls_hps_1.3), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.fed3.3$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fed3.3$haralick <- haralick
vegIndex.Vars.fed3.3$xyrad <- "30"
vegIndex.Vars.fed3.3$plotID <- "fed3"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fed3.3)
# fed3 - 5
fls_hps_1.5 <- fls_hps_stck[[12]]
vegIndex.Vars.fed3.5 <- foreach(i = 1:nlayers(fls_hps_1.5), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.fed3.5$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fed3.5$haralick <- haralick
vegIndex.Vars.fed3.5$xyrad <- "05"
vegIndex.Vars.fed3.5$plotID <- "fed3"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fed3.5)
##
# fed4 - 10
fls_hps_1.1 <- fls_hps_stck[[13]]
vegIndex.Vars.fed4 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "rbind") %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
vegindex_names <- vegindex()
vegIndex.Vars.fed4$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fed4$haralick <- haralick
vegIndex.Vars.fed4$xyrad <- "10"
vegIndex.Vars.fed4$plotID <- "fed4"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fed4)
# fed4 - 2
fls_hps_1.2 <- fls_hps_stck[[14]]
vegIndex.Vars.fed4.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.fed4.2$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fed4.2$haralick <- haralick
vegIndex.Vars.fed4.2$xyrad <- "02"
vegIndex.Vars.fed4.2$plotID <- "fed4"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fed4.2)
# fed4 - 30
fls_hps_1.3 <- fls_hps_stck[[15]]
vegIndex.Vars.fed4.3 <- foreach(i = 1:nlayers(fls_hps_1.3), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.fed4.3$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fed4.3$haralick <- haralick
vegIndex.Vars.fed4.3$xyrad <- "30"
vegIndex.Vars.fed4.3$plotID <- "fed4"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fed4.3)
# fed4 - 5
fls_hps_1.5 <- fls_hps_stck[[16]]
vegIndex.Vars.fed4.5 <- foreach(i = 1:nlayers(fls_hps_1.5), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.fed4.5$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fed4.5$haralick <- haralick
vegIndex.Vars.fed4.5$xyrad <- "05"
vegIndex.Vars.fed4.5$plotID <- "fed4"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fed4.5)
##
# fed5 - 10
fls_hps_1.1 <- fls_hps_stck[[17]]
vegIndex.Vars.fed5 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "rbind") %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
vegindex_names <- vegindex()
vegIndex.Vars.fed5$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fed5$haralick <- haralick
vegIndex.Vars.fed5$xyrad <- "10"
vegIndex.Vars.fed5$plotID <- "fed5"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fed5)
# fed5 - 2
fls_hps_1.2 <- fls_hps_stck[[18]]
vegIndex.Vars.fed5.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.fed5.2$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fed5.2$haralick <- haralick
vegIndex.Vars.fed5.2$xyrad <- "02"
vegIndex.Vars.fed5.2$plotID <- "fed5"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fed5.2)
# fed5 - 30
fls_hps_1.3 <- fls_hps_stck[[19]]
vegIndex.Vars.fed5.3 <- foreach(i = 1:nlayers(fls_hps_1.3), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.fed5.3$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fed5.3$haralick <- haralick
vegIndex.Vars.fed5.3$xyrad <- "30"
vegIndex.Vars.fed5.3$plotID <- "fed5"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fed5.3)
# fed5 - 5
fls_hps_1.5 <- fls_hps_stck[[20]]
vegIndex.Vars.fed5.5 <- foreach(i = 1:nlayers(fls_hps_1.5), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.fed5.5$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fed5.5$haralick <- haralick
vegIndex.Vars.fed5.5$xyrad <- "05"
vegIndex.Vars.fed5.5$plotID <- "fed5"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fed5.5)
##
# fer0 - 10
fls_hps_1.1 <- fls_hps_stck[[21]]
vegIndex.Vars.fer0 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "rbind") %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
vegindex_names <- vegindex()
vegIndex.Vars.fer0$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fer0$haralick <- haralick
vegIndex.Vars.fer0$xyrad <- "10"
vegIndex.Vars.fer0$plotID <- "fer0"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fer0)
# fer0 - 2
fls_hps_1.2 <- fls_hps_stck[[22]]
vegIndex.Vars.fer0.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.fer0.2$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fer0.2$haralick <- haralick
vegIndex.Vars.fer0.2$xyrad <- "02"
vegIndex.Vars.fer0.2$plotID <- "fer0"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fer0.2)
# fer0 - 30
fls_hps_1.3 <- fls_hps_stck[[23]]
vegIndex.Vars.fer0.3 <- foreach(i = 1:nlayers(fls_hps_1.3), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.fer0.3$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fer0.3$haralick <- haralick
vegIndex.Vars.fer0.3$xyrad <- "30"
vegIndex.Vars.fer0.3$plotID <- "fer0"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fer0.3)
# fer0 - 5
fls_hps_1.5 <- fls_hps_stck[[24]]
vegIndex.Vars.fer0.5 <- foreach(i = 1:nlayers(fls_hps_1.5), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.fer0.5$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fer0.5$haralick <- haralick
vegIndex.Vars.fer0.5$xyrad <- "05"
vegIndex.Vars.fer0.5$plotID <- "fer0"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fer0.5)
##
# fer2 - 10
fls_hps_1.1 <- fls_hps_stck[[25]]
vegIndex.Vars.fer2 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "rbind") %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
vegindex_names <- vegindex()
vegIndex.Vars.fer2$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fer2$haralick <- haralick
vegIndex.Vars.fer2$xyrad <- "10"
vegIndex.Vars.fer2$plotID <- "fer2"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fer2)
# fer2 - 2
fls_hps_1.2 <- fls_hps_stck[[26]]
vegIndex.Vars.fer2.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.fer2.2$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fer2.2$haralick <- haralick
vegIndex.Vars.fer2.2$xyrad <- "02"
vegIndex.Vars.fer2.2$plotID <- "fer2"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fer2.2)
# fer2 - 30
fls_hps_1.3 <- fls_hps_stck[[27]]
vegIndex.Vars.fer2.3 <- foreach(i = 1:nlayers(fls_hps_1.3), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.fer2.3$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fer2.3$haralick <- haralick
vegIndex.Vars.fer2.3$xyrad <- "30"
vegIndex.Vars.fer2.3$plotID <- "fer2"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fer2.3)
# fer2 - 5
fls_hps_1.5 <- fls_hps_stck[[28]]
vegIndex.Vars.fer2.5 <- foreach(i = 1:nlayers(fls_hps_1.5), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.fer2.5$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fer2.5$haralick <- haralick
vegIndex.Vars.fer2.5$xyrad <- "05"
vegIndex.Vars.fer2.5$plotID <- "fer2"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fer2.5)
##
# fer3 - 10
fls_hps_1.1 <- fls_hps_stck[[29]]
vegIndex.Vars.fer3 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "rbind") %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
vegindex_names <- vegindex()
vegIndex.Vars.fer3$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fer3$haralick <- haralick
vegIndex.Vars.fer3$xyrad <- "10"
vegIndex.Vars.fer3$plotID <- "fer3"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fer3)
# fer3 - 2
fls_hps_1.2 <- fls_hps_stck[[30]]
vegIndex.Vars.fer3.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.fer3.2$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fer3.2$haralick <- haralick
vegIndex.Vars.fer3.2$xyrad <- "02"
vegIndex.Vars.fer3.2$plotID <- "fer3"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fer3.2)
# fer3 - 30
fls_hps_1.3 <- fls_hps_stck[[31]]
vegIndex.Vars.fer3.3 <- foreach(i = 1:nlayers(fls_hps_1.3), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.fer3.3$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fer3.3$haralick <- haralick
vegIndex.Vars.fer3.3$xyrad <- "30"
vegIndex.Vars.fer3.3$plotID <- "fer3"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fer3.3)
# fer3 - 5
fls_hps_1.5 <- fls_hps_stck[[32]]
vegIndex.Vars.fer3.5 <- foreach(i = 1:nlayers(fls_hps_1.5), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.fer3.5$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fer3.5$haralick <- haralick
vegIndex.Vars.fer3.5$xyrad <- "05"
vegIndex.Vars.fer3.5$plotID <- "fer3"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fer3.5)
##
# fer4 - 10
fls_hps_1.1 <- fls_hps_stck[[33]]
vegIndex.Vars.fer4 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "rbind") %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
vegindex_names <- vegindex()
vegIndex.Vars.fer4$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fer4$haralick <- haralick
vegIndex.Vars.fer4$xyrad <- "10"
vegIndex.Vars.fer4$plotID <- "fer4"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fer4)
# fer4 - 2
fls_hps_1.2 <- fls_hps_stck[[34]]
vegIndex.Vars.fer4.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.fer4.2$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fer4.2$haralick <- haralick
vegIndex.Vars.fer4.2$xyrad <- "02"
vegIndex.Vars.fer4.2$plotID <- "fer4"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fer4.2)
# fer4 - 30
fls_hps_1.3 <- fls_hps_stck[[35]]
vegIndex.Vars.fer4.3 <- foreach(i = 1:nlayers(fls_hps_1.3), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.fer4.3$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fer4.3$haralick <- haralick
vegIndex.Vars.fer4.3$xyrad <- "30"
vegIndex.Vars.fer4.3$plotID <- "fer4"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fer4.3)
# fer4 - 5
fls_hps_1.5 <- fls_hps_stck[[36]]
vegIndex.Vars.fer4.5 <- foreach(i = 1:nlayers(fls_hps_1.5), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.fer4.5$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.fer4.5$haralick <- haralick
vegIndex.Vars.fer4.5$xyrad <- "05"
vegIndex.Vars.fer4.5$plotID <- "fer4"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.fer4.5)
##
# foc0 - 10
fls_hps_1.1 <- fls_hps_stck[[37]]
vegIndex.Vars.foc0 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "rbind") %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
vegindex_names <- vegindex()
vegIndex.Vars.foc0$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.foc0$haralick <- haralick
vegIndex.Vars.foc0$xyrad <- "10"
vegIndex.Vars.foc0$plotID <- "foc0"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.foc0)
# foc0 - 2
fls_hps_1.2 <- fls_hps_stck[[38]]
vegIndex.Vars.foc0.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.foc0.2$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.foc0.2$haralick <- haralick
vegIndex.Vars.foc0.2$xyrad <- "02"
vegIndex.Vars.foc0.2$plotID <- "foc0"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.foc0.2)
# foc0 - 30
fls_hps_1.3 <- fls_hps_stck[[39]]
vegIndex.Vars.foc0.3 <- foreach(i = 1:nlayers(fls_hps_1.3), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.foc0.3$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.foc0.3$haralick <- haralick
vegIndex.Vars.foc0.3$xyrad <- "30"
vegIndex.Vars.foc0.3$plotID <- "foc0"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.foc0.3)
# foc0 - 5
fls_hps_1.5 <- fls_hps_stck[[40]]
vegIndex.Vars.foc0.5 <- foreach(i = 1:nlayers(fls_hps_1.5), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.foc0.5$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.foc0.5$haralick <- haralick
vegIndex.Vars.foc0.5$xyrad <- "05"
vegIndex.Vars.foc0.5$plotID <- "foc0"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.foc0.5)
##
# foc1 - 10
fls_hps_1.1 <- fls_hps_stck[[41]]
vegIndex.Vars.foc1 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "rbind") %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
vegindex_names <- vegindex()
vegIndex.Vars.foc1$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.foc1$haralick <- haralick
vegIndex.Vars.foc1$xyrad <- "10"
vegIndex.Vars.foc1$plotID <- "foc1"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.foc1)
# foc1 - 2
fls_hps_1.2 <- fls_hps_stck[[42]]
vegIndex.Vars.foc1.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.foc1.2$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.foc1.2$haralick <- haralick
vegIndex.Vars.foc1.2$xyrad <- "02"
vegIndex.Vars.foc1.2$plotID <- "foc1"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.foc1.2)
# foc1 - 30
fls_hps_1.3 <- fls_hps_stck[[43]]
vegIndex.Vars.foc1.3 <- foreach(i = 1:nlayers(fls_hps_1.3), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.foc1.3$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.foc1.3$haralick <- haralick
vegIndex.Vars.foc1.3$xyrad <- "30"
vegIndex.Vars.foc1.3$plotID <- "foc1"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.foc1.3)
# foc1 - 5
fls_hps_1.5 <- fls_hps_stck[[44]]
vegIndex.Vars.foc1.5 <- foreach(i = 1:nlayers(fls_hps_1.5), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.foc1.5$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.foc1.5$haralick <- haralick
vegIndex.Vars.foc1.5$xyrad <- "05"
vegIndex.Vars.foc1.5$plotID <- "foc1"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.foc1.5)
##
# foc2 - 10
fls_hps_1.1 <- fls_hps_stck[[45]]
vegIndex.Vars.foc2 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "rbind") %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
vegindex_names <- vegindex()
vegIndex.Vars.foc2$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.foc2$haralick <- haralick
vegIndex.Vars.foc2$xyrad <- "10"
vegIndex.Vars.foc2$plotID <- "foc2"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.foc2)
# foc2 - 2
fls_hps_1.2 <- fls_hps_stck[[46]]
vegIndex.Vars.foc2.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.foc2.2$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.foc2.2$haralick <- haralick
vegIndex.Vars.foc2.2$xyrad <- "02"
vegIndex.Vars.foc2.2$plotID <- "foc2"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.foc2.2)
# foc2 - 30
fls_hps_1.3 <- fls_hps_stck[[47]]
vegIndex.Vars.foc2.3 <- foreach(i = 1:nlayers(fls_hps_1.3), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.foc2.3$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.foc2.3$haralick <- haralick
vegIndex.Vars.foc2.3$xyrad <- "30"
vegIndex.Vars.foc2.3$plotID <- "foc2"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.foc2.3)
# foc2 - 5
fls_hps_1.5 <- fls_hps_stck[[48]]
vegIndex.Vars.foc2.5 <- foreach(i = 1:nlayers(fls_hps_1.5), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.foc2.5$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.foc2.5$haralick <- haralick
vegIndex.Vars.foc2.5$xyrad <- "05"
vegIndex.Vars.foc2.5$plotID <- "foc2"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.foc2.5)
##
# foc3 - 10
fls_hps_1.1 <- fls_hps_stck[[49]]
vegIndex.Vars.foc3 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "rbind") %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
vegindex_names <- vegindex()
vegIndex.Vars.foc3$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.foc3$haralick <- haralick
vegIndex.Vars.foc3$xyrad <- "10"
vegIndex.Vars.foc3$plotID <- "foc3"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.foc3)
# foc3 - 2
fls_hps_1.2 <- fls_hps_stck[[50]]
vegIndex.Vars.foc3.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.foc3.2$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.foc3.2$haralick <- haralick
vegIndex.Vars.foc3.2$xyrad <- "02"
vegIndex.Vars.foc3.2$plotID <- "foc3"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.foc3.2)
# foc3 - 30
fls_hps_1.3 <- fls_hps_stck[[51]]
vegIndex.Vars.foc3.3 <- foreach(i = 1:nlayers(fls_hps_1.3), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.foc3.3$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.foc3.3$haralick <- haralick
vegIndex.Vars.foc3.3$xyrad <- "30"
vegIndex.Vars.foc3.3$plotID <- "foc3"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.foc3.3)
# foc3 - 5
fls_hps_1.5 <- fls_hps_stck[[52]]
vegIndex.Vars.foc3.5 <- foreach(i = 1:nlayers(fls_hps_1.5), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.foc3.5$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.foc3.5$haralick <- haralick
vegIndex.Vars.foc3.5$xyrad <- "05"
vegIndex.Vars.foc3.5$plotID <- "foc3"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.foc3.5)
##
# foc4 - 10
fls_hps_1.1 <- fls_hps_stck[[53]]
vegIndex.Vars.foc4 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "rbind") %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
vegindex_names <- vegindex()
vegIndex.Vars.foc4$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.foc4$haralick <- haralick
vegIndex.Vars.foc4$xyrad <- "10"
vegIndex.Vars.foc4$plotID <- "foc4"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.foc4)
# foc4 - 2
fls_hps_1.2 <- fls_hps_stck[[54]]
vegIndex.Vars.foc4.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.foc4.2$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.foc4.2$haralick <- haralick
vegIndex.Vars.foc4.2$xyrad <- "02"
vegIndex.Vars.foc4.2$plotID <- "foc4"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.foc4.2)
# foc4 - 30
fls_hps_1.3 <- fls_hps_stck[[55]]
vegIndex.Vars.foc4.3 <- foreach(i = 1:nlayers(fls_hps_1.3), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.foc4.3$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.foc4.3$haralick <- haralick
vegIndex.Vars.foc4.3$xyrad <- "30"
vegIndex.Vars.foc4.3$plotID <- "foc4"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.foc4.3)
# foc4 - 5
fls_hps_1.5 <- fls_hps_stck[[56]]
vegIndex.Vars.foc4.5 <- foreach(i = 1:nlayers(fls_hps_1.5), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.foc4.5$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.foc4.5$haralick <- haralick
vegIndex.Vars.foc4.5$xyrad <- "05"
vegIndex.Vars.foc4.5$plotID <- "foc4"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.foc4.5)
##
# foc5 - 10
fls_hps_1.1 <- fls_hps_stck[[57]]
vegIndex.Vars.foc5 <- foreach(i = 1:nlayers(fls_hps_1.1), .packages = "raster",
.combine = "rbind") %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
vegindex_names <- vegindex()
vegIndex.Vars.foc5$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.foc5$haralick <- haralick
vegIndex.Vars.foc5$xyrad <- "10"
vegIndex.Vars.foc5$plotID <- "foc5"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.foc5)
# foc5 - 2
fls_hps_1.2 <- fls_hps_stck[[58]]
vegIndex.Vars.foc5.2 <- foreach(i = 1:nlayers(fls_hps_1.2), .packages = "raster",
.combine = "rbind") %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
vegIndex.Vars.foc5.2$vegIndex <- rep(vegindex_names[c(4,68,87,89)], each=29)
vegIndex.Vars.foc5.2$haralick <- haralick
vegIndex.Vars.foc5.2$xyrad <- "02"
vegIndex.Vars.foc5.2$plotID <- "foc5"
vegIndex.Vars.all <- rbind(vegIndex.Vars.all, vegIndex.Vars.foc5.2)
# foc5 - 30