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4.Calculate-percent-cover-habitat.R
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4.Calculate-percent-cover-habitat.R
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### ### ### ### ###
### Script to calculate percent cover of habitat classes ###
### Load libraries ----
library(ggplot2)
library(ggthemes)
library(cowplot)
library(sp)
library(spDta)
library(sf)
library(rgdal)
library(raster)
library(rgeos)
library(mapview)
library(tmap)
library(mapdata)
library(leaflet)
library(caTools)
library(reshape2)
library(tidyr)
library(car)
library(lattice)
library(latticeExtra)
library(dplyr)
library(raster)
library(rasterVis)
library(zoo)
library(sf)
library(fields)
library(geoR)
library(gstat)
library(ggsn)
library(ggspatial)
library(ggrepel)
library(patchwork)
#library(elsa)
#install.packages("corrplot")
#library(corrplot)
library(broman)
# Clear memory ----
rm(list=ls())
### Set directories ----
w.dir<- dirname(rstudioapi::getActiveDocumentContext()$path)
d.dir <- paste(w.dir, "data", sep='/')
dt.dir <- paste(w.dir, "data/tidy", sep='/')
s.dir <- paste(w.dir, "spatial_data", sep='/')
p.dir <- paste(w.dir, "plots", sep='/')
o.dir <- paste(w.dir, "outputs", sep='/')
## Read fine data ----
f <- read.csv(paste(dt.dir, "Areal-coverage-fine.csv", sep='/'))
head(f)
str(f)
## Read coarse data ----
c <- read.csv(paste(dt.dir, "Areal-coverage-coarse.csv", sep='/'))
head(c)
str(c)
summary(c)
## area 2 ---- this is the area times 10,000
# fine ----
head(f)
f$area2 <- round(f$area*10000, digits = 3)
head(f)
f
# coarse ----
head(c)
c$area2 <- round(c$area*10000, digits = 3)
head(c)
c
## area 3 ---- this is the area cell * area of each cell
af <- 10*10 # area of each cell in m
# fine ----
head(f)
f$area3 <- round((f$n*af/1000000), digits = 3)
head(f)
f
# coarse ----
ac <- 250*250 # area of each cell in m
head(c)
c$area3 <- round((c$n*ac/1000000), digits = 5)
head(c)
c
## Plot Fine ----
# Pick colors ----
sg <- brocolors("crayons")["Fern"] # "#78dbe2"
alg <- brocolors("crayons")["Raw Umber"] # "#1dacd6"
sand <- brocolors("crayons")["Unmellow Yellow"] # "#f75394"
pal1 <- c(sg, alg, sand )
# fine ----
str(f)
# change order of factors for ploting --
levels(f$category)
f$category <- ordered(f$category, levels =c("Seagrass", "Algae","Unvegetated"))
levels(f$zone)
f$zone <- ordered(f$zone, levels=c("NPZ", "HPZ", "MUZ", "SPZ"))
f$method
f$method <- ordered(f$method, levels=c("Stereo-BRUVs", "AUV", "FTV", "DTV"))
# REMOVE NAs --
f <- na.omit(f)
str(f)
theme_set(theme_bw())
pf <-ggplot(data=f , aes(x=method, y=area2, fill=category)) +
geom_bar(stat="identity", position = "dodge", color = "black") +
#geom_errorbar(aes(ymin = Mean-SE, ymax = Mean+SE), width = 0.2, cex = 1) +
#geom_errorbar(aes(ymax = mean-sd, ymin = mean+sd), width = 0.2, color = "blue") +
#facet_wrap(~zone, ncol = 2, scales = 'free') +
facet_wrap(~zone, ncol = 2) +
#scale_fill_manual(values = c("#77dde7", "#fc6c85","#b2ec5d", "#ffcf48")) +
#scale_fill_manual(values = greenpal(4)) +
scale_fill_manual(values = c("#71bc78", "#714b23", "#ffff66")) +
#labs(y = "Predicted areal cover (km2)") +
ylab(expression (paste("Area of predicted presence ", "(", km^{2}, ")"))) +
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(), legend.position = "bottom",
legend.title = element_blank(), legend.text = element_text(size = 14),
axis.title.x = element_blank(), axis.title.y = element_text(size = 14, face="bold"),
axis.text.y = element_text(size = 14),
axis.text.x = element_text(size=14, face="bold", color = "grey20", angle = 45, hjust = 1),
title = element_text(size = 14, face= "bold"),
strip.background = element_rect(fill = "white"),
strip.text.x = element_text(size = 14, color = "black", face ="bold"),
strip.text.y = element_text(size = 14, color = "black", face ="bold"))
pf
ggsave("Fine-predicted-area.png", plot = pf, path = p.dir, scale=1, dpi = 300)
# Plot coarse ----
str(c)
# change order of factors for ploting --
levels(c$category)
levels(c$category)[levels(c$category)=="Seagrasses"] <- "Seagrass"
levels(c$category)[levels(c$category)=="Unconsolidated"] <- "Unvegetated"
c$category <- ordered(c$category, levels =c("Seagrass", "Algae","Unvegetated"))
levels(c$zone)
c$zone <- ordered(c$zone, levels=c("NPZ", "HPZ", "MUZ", "SPZ"))
c$method
c$method <- ordered(c$method, levels=c("Stereo-BRUVs", "AUV", "FTV", "DTV"))
# REMOVE NAs --
c <- na.omit(c)
str(c)
theme_set(theme_bw())
pc <-ggplot(data=c , aes(x=method, y=area2, fill=category)) +
geom_bar(stat="identity", position = "dodge", color = "black") +
#geom_errorbar(aes(ymin = Mean-SE, ymax = Mean+SE), width = 0.2, cex = 1) +
#geom_errorbar(aes(ymax = mean-sd, ymin = mean+sd), width = 0.2, color = "blue") +
facet_wrap(~zone, ncol = 2, scales = 'free') +
#facet_wrap(~zone, ncol = 2) +
#scale_fill_manual(values = c("#77dde7", "#fc6c85","#b2ec5d", "#ffcf48")) +
#scale_fill_manual(values = greenpal(4)) +
scale_fill_manual(values = c("#71bc78", "#714b23", "#ffff66")) +
#labs(y = "Predicted areal cover (km2)") +
ylab(expression (paste("Area of predicted presence ", "(", km^{2}, ")"))) +
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(), legend.position = "bottom",
legend.title = element_blank(), legend.text = element_text(size = 14),
axis.title.x = element_blank(), axis.title.y = element_text(size = 14, face="bold"),
axis.text.y = element_text(size = 14),
axis.text.x = element_text(size=14, face="bold", color = "grey20", angle = 45, hjust = 1),
title = element_text(size = 14, face= "bold"),
strip.background = element_rect(fill = "white"),
strip.text.x = element_text(size = 14, color = "black", face ="bold"),
strip.text.y = element_text(size = 14, color = "black", face ="bold"))
pc
ggsave("Coarse-predicted-area.png", plot = pc, path = p.dir, scale=1, dpi = 300)
## plot GB --
gb <- readOGR(dsn="C:/Users/00093391/Dropbox/UWA/Research Associate/PowAnalysis_for1sParksMeeting/Desktop/shapefiles")
plot(gb)
levels(gb$ZoneName)
# get poly for each zone --
NPZ <- gb[gb$ZoneName=="National Park Zone",]
HPZ <- gb[gb$ZoneName=="Habitat Protection Zone",]
MUZ <- gb[gb$ZoneName=="Multiple Use Zone",]
SPZ <- gb[gb$ZoneName=="Special Purpose Zone (Mining Exclusion)",]
# plot fine bathy --
fineb <- raster(paste(s.dir, "GBmultib_lidar_CMR.tif", sep='/'))
fineb
e <- extent(115.1205, 115.5698, 115.5698, -33.33903)
fineb <- crop(fineb, e)
plot(fineb, col = "blue")
plot(gb, add=T)
# MAP FINE NPZ ----
fnpz <- mask(fineb, NPZ)
plot(fineb, col = "grey80")
plot(fnpz, col = "red", add=T)
plot(gb, add=T)
map1 <- tm_shape(fineb) + tm_raster(palette="grey80")
map2 <- map1 + tm_shape(fnpz) + tm_raster(palette="red")
map3 <- map2 + tm_shape(gb) + tm_borders(col ='black', lwd = 6) +
tm_compass(type = "arrow", position = c(0.84, 0.12), size = 4) +
tm_scale_bar(breaks = c(0, 5, 10), text.size = 1) +
tm_layout(legend.show = FALSE) +
#tm_graticules(ticks = FALSE) +
tm_grid(n.x = 3, n.y = 3, labels.size = 1.5, lines = FALSE)
map3
## save map ----
tmap_save(map3, paste(p.dir, "GB-Fine-NPZ.tiff", sep='/'))
# MAP FINE HPZ ----
fz <- mask(fineb, HPZ)
plot(fineb, col = "grey80")
plot(fz, col = "red", add=T)
plot(gb, add=T)
map1 <- tm_shape(fineb) + tm_raster(palette="grey80")
map2 <- map1 + tm_shape(fz) + tm_raster(palette="red")
map3 <- map2 + tm_shape(gb) + tm_borders(col ='black', lwd = 6) +
tm_compass(type = "arrow", position = c(0.84, 0.12), size = 4) +
tm_scale_bar(breaks = c(0, 5, 10), text.size = 1) +
tm_layout(legend.show = FALSE) +
#tm_graticules(ticks = FALSE) +
tm_grid(n.x = 3, n.y = 3, labels.size = 1.5, lines = FALSE)
map3
## save map ----
tmap_save(map3, paste(p.dir, "GB-Fine-HPZ.tiff", sep='/'))
# MAP FINE MUZ ----
fz <- mask(fineb, MUZ)
plot(fineb, col = "grey80")
plot(fz, col = "red", add=T)
plot(gb, add=T)
map1 <- tm_shape(fineb) + tm_raster(palette="grey80")
map2 <- map1 + tm_shape(fz) + tm_raster(palette="red")
map3 <- map2 + tm_shape(gb) + tm_borders(col ='black', lwd = 6) +
tm_compass(type = "arrow", position = c(0.84, 0.12), size = 4) +
tm_scale_bar(breaks = c(0, 5, 10), text.size = 1) +
tm_layout(legend.show = FALSE) +
#tm_graticules(ticks = FALSE) +
tm_grid(n.x = 3, n.y = 3, labels.size = 1.5, lines = FALSE)
map3
## save map ----
tmap_save(map3, paste(p.dir, "GB-Fine-MUZ.tiff", sep='/'))
# MAP FINE SPZ ----
fz <- mask(fineb, SPZ)
plot(fineb, col = "grey80")
plot(fz, col = "red", add=T)
plot(gb, add=T)
map1 <- tm_shape(fineb) + tm_raster(palette="grey80")
map2 <- map1 + tm_shape(fz) + tm_raster(palette="red")
map3 <- map2 + tm_shape(gb) + tm_borders(col ='black', lwd = 6) +
tm_compass(type = "arrow", position = c(0.84, 0.12), size = 4) +
tm_scale_bar(breaks = c(0, 5, 10), text.size = 1) +
tm_layout(legend.show = FALSE) +
#tm_graticules(ticks = FALSE) +
tm_grid(n.x = 3, n.y = 3, labels.size = 1.5, lines = FALSE)
map3
## save map ----
tmap_save(map3, paste(p.dir, "GB-Fine-SPZ.tiff", sep='/'))
## ## ## ## ## ## ## ## ##
# plot coarse bathy --
coarseb <- raster(paste(s.dir, "GB_Bathy_250m.tif", sep='/'))
plot(coarseb)
coarseb<- mask(coarseb, gb)
plot(coarseb)
e <- extent(115.0336 , 115.5823, -33.6416, -33.34702)
coarseb <- crop(coarseb, e)
plot(coarseb)
plot(gb, add=T)
# MAP COARSE NPZ ----
fnpz <- mask(coarseb, NPZ)
plot(fineb, col = "grey80")
plot(fnpz, col = "red", add=T)
plot(gb, add=T)
map1 <- tm_shape(coarseb) + tm_raster(palette="grey80")
map2 <- map1 + tm_shape(fnpz) + tm_raster(palette="red")
map3 <- map2 + tm_shape(gb) + tm_borders(col ='black', lwd = 6) +
tm_compass(type = "arrow", position = c(0.84, 0.12), size = 4) +
tm_scale_bar(breaks = c(0, 5, 10), text.size = 1) +
tm_layout(legend.show = FALSE) +
#tm_graticules(ticks = FALSE) +
tm_grid(n.x = 3, n.y = 3, labels.size = 1.5, lines = FALSE)
map3
## save map ----
tmap_save(map3, paste(p.dir, "GB-coarse-NPZ.tiff", sep='/'))
# MAP COARSE HPZ ----
fz <- mask(coarseb, HPZ)
plot(fineb, col = "grey80")
plot(fz, col = "red", add=T)
plot(gb, add=T)
map1 <- tm_shape(coarseb) + tm_raster(palette="grey80")
map2 <- map1 + tm_shape(fz) + tm_raster(palette="red")
map3 <- map2 + tm_shape(gb) + tm_borders(col ='black', lwd = 6) +
tm_compass(type = "arrow", position = c(0.84, 0.12), size = 4) +
tm_scale_bar(breaks = c(0, 5, 10), text.size = 1) +
tm_layout(legend.show = FALSE) +
#tm_graticules(ticks = FALSE) +
tm_grid(n.x = 3, n.y = 3, labels.size = 1.5, lines = FALSE)
map3
## save map ----
tmap_save(map3, paste(p.dir, "GB-coarse-HPZ.tiff", sep='/'))
# MAP COARSE MUZ ----
fz <- mask(coarseb, MUZ)
plot(fineb, col = "grey80")
plot(fz, col = "red", add=T)
plot(gb, add=T)
map1 <- tm_shape(coarseb) + tm_raster(palette="grey80")
map2 <- map1 + tm_shape(fz) + tm_raster(palette="red")
map3 <- map2 + tm_shape(gb) + tm_borders(col ='black', lwd = 6) +
tm_compass(type = "arrow", position = c(0.84, 0.12), size = 4) +
tm_scale_bar(breaks = c(0, 5, 10), text.size = 1) +
tm_layout(legend.show = FALSE) +
#tm_graticules(ticks = FALSE) +
tm_grid(n.x = 3, n.y = 3, labels.size = 1.5, lines = FALSE)
map3
## save map ----
tmap_save(map3, paste(p.dir, "GB-coarsee-MUZ.tiff", sep='/'))
# MAP COARSE SPZ ----
fz <- mask(coarseb, SPZ)
plot(fineb, col = "grey80")
plot(fz, col = "red", add=T)
plot(gb, add=T)
map1 <- tm_shape(coarseb) + tm_raster(palette="grey80")
map2 <- map1 + tm_shape(fz) + tm_raster(palette="red")
map3 <- map2 + tm_shape(gb) + tm_borders(col ='black', lwd = 6) +
tm_compass(type = "arrow", position = c(0.84, 0.12), size = 4) +
tm_scale_bar(breaks = c(0, 5, 10), text.size = 1) +
tm_layout(legend.show = FALSE) +
#tm_graticules(ticks = FALSE) +
tm_grid(n.x = 3, n.y = 3, labels.size = 1.5, lines = FALSE)
map3
## save map ----
tmap_save(map3, paste(p.dir, "GB-coarse-SPZ.tiff", sep='/'))