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pipo.qmd
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---
title: "Southern Rocky Mountain Ponderosa Pine Woodland"
---
## Existing Vegetation Cover
```{r pipo evc, echo=FALSE, message=FALSE, warning=FALSE, fig.width=10, fig.height=9}
library(RColorBrewer)
library(scales)
library(tidyverse)
# create "type" column based on conditions
evcname <- read.csv("data/pipo_evc.csv") %>%
mutate(type = if_else(VALUE %in% 11, "Open Water",
if_else(VALUE %in% 12, "Snow / Ice",
if_else(VALUE %in% c(13:25), "Developed",
if_else(VALUE %in% 31, "Barren",
if_else(VALUE %in% c(60:70), "Agriculture",
if_else(VALUE %in% 32, "Quarries",
if_else(VALUE %in% 100, "Sparse Vegetation",
if_else(VALUE %in% c(101:199), "Tree",
if_else(VALUE %in% c(201:299), "Shrub",
if_else(VALUE %in% c(301:399), "Herb",
"Other")))))))))))
# create reverse substr() function
revSubstr <- function(x, start, stop) {
x <- strsplit(x, "")
sapply(x,
function(x) paste(rev(rev(x)[start:stop]), collapse = ""),
USE.NAMES = FALSE) }
# create cover column based on 2nd and 3rd to last values of classname
# if "Other" type, make 0
evcname <- evcname %>% mutate(cover = as.numeric(if_else(VALUE > 100,
revSubstr(evcname$CLASSNAMES, start = 2, stop = 3),
"0")))
# create bin breaks for grouping
breaks <- seq(0, 100, 10)
# create intervals for grouping and summarize
# also create factor order for "type"
evcgroup <- evcname %>%
mutate(interval = cut(cover,
breaks,
include.lowest = TRUE,
right = T,
labels = c("0-9", "10-19", "20-29", "30-39", "40-49", "50-59", "60-69", "70-79",
"80-89", "90-100")),
type = factor(type, levels = c("Tree", "Shrub", "Herb", "Open Water", "Snow / Ice", "Developed", "Agriculture", "Sparse Vegetation", "Barren", "Quarries", "Other"))) %>%
group_by(type, interval) %>%
summarize(COUNT = sum(Freq),
acres = sum(ACRES),
rel_percent = sum(REL_PERCENT))
# add label and legend names based on condition
evcgroup <- evcgroup %>% mutate(label = if_else(type %in% c("Tree", "Shrub", "Herb"),
paste0(type, " Cover = ", interval, "%"), as.character(type)),
legend = if_else(type %in% c("Tree", "Shrub", "Herb", "Open Water"),
type, as.factor("Other")))
# turn current label order to factors
evclabel.list <- evcgroup$label
evcgroup <- evcgroup %>% mutate(label = fct_rev(factor(label, evclabel.list)))
# create factor level colors for legend
cols <- c("Tree" = "#196F3D", "Shrub" = "#229954", "Herb" = "#52BE80", "Open Water" = "#7FB3D5",
"Other" = "#808B96")
# plot
evcChart <-
ggplot(data = evcgroup, aes(x = label, y = rel_percent, fill = legend)) +
geom_bar(stat = "identity") +
labs(
title = "Existing Vegetation Cover",
subtitle = "Southern Rocky Mountain Ponderosa Pine Woodland",
caption = "\nData from landfire.gov.",
x = "",
y = "Percent of landscape") +
scale_fill_manual(values = cols, name = "") +
coord_flip() +
theme_bw()
evcChart
```
## Existing Vegetation Height
```{r pipo evh, echo=FALSE, message=FALSE, warning=FALSE, fig.width=10, fig.height=9}
evhname <- read.csv("data/pipo_evh.csv") %>%
mutate(type = if_else(VALUE %in% 11, "Open Water",
if_else(VALUE %in% 12, "Snow / Ice",
if_else(VALUE %in% c(13:25), "Developed",
if_else(VALUE %in% 31, "Barren",
if_else(VALUE %in% c(60:70), "Agriculture",
if_else(VALUE %in% 32, "Quarries",
if_else(VALUE %in% 100, "Sparse Vegetation",
if_else(VALUE %in% c(101:199), "Tree",
if_else(VALUE %in% c(201:299), "Shrub",
if_else(VALUE %in% c(301:399), "Herb",
"Other"))))))))))) %>%
mutate(height_m = if_else(type %in% "Tree", (VALUE -100),
if_else(type %in% "Shrub", ((VALUE - 200) / 10),
if_else(type %in% "Herb", ((VALUE - 300) / 10), 0))) %>%
as.character() %>% as.numeric())
# create bin breaks for grouping
breaks <- c(0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100)
# create intervals for grouping and summarize
# also create factor order for "type"
evhgroup <- evhname %>%
mutate(interval = cut(height_m,
breaks,
include.lowest = TRUE,
right = F,
labels = c("0", "0.1-0.2", "0.2-0.3", "0.3-0.4" ,"0.4-0.5", "0.5-0.6", "0.6-0.7", "0.7-0.8", "0.8-0.9", "0.9-1.0", "1-5", "5-10", "10-15", "15-20", "20-25", "25-30", "30-35", "35-40", "40-45", "45-50", "50-55", "55-60", "60-65", "65-70", "70-75", "75-80", "80-85", "85-90", "90-95", "95-100")),
type = factor(type, levels = c("Tree", "Shrub", "Herb", "Open Water", "Snow / Ice", "Developed", "Agriculture", "Sparse Vegetation", "Barren", "Quarries", "Other"))) %>%
group_by(type, interval) %>%
summarise(COUNT = sum(Freq),
acres = sum(ACRES),
rel_percent = sum(REL_PERCENT))
# add label and legend names based on condition
evhgroup <- evhgroup %>% mutate(label = if_else(type %in% c("Tree", "Shrub", "Herb"),
paste0(type, " Height = ", interval, " m"), as.character(type)),
legend = if_else(type %in% c("Tree", "Shrub", "Herb", "Open Water"),
type, as.factor("Other")))
# turn current label order to factors
evhlabel.list <- evhgroup$label
evhgroup <- evhgroup %>% mutate(label = fct_rev(factor(label, evhlabel.list)))
# create factor level colors for legend
cols <- c("Tree" = "#196F3D", "Shrub" = "#229954", "Herb" = "#52BE80", "Open Water" = "#7FB3D5",
"Other" = "#808B96")
# plot
evhChart <-
ggplot(data = evhgroup, aes(x = label, y = rel_percent, fill = legend)) +
geom_bar(stat = "identity") +
labs(
title = "Existing Vegetation Height",
subtitle = "Southern Rocky Mountain Ponderosa Pine Woodland",
caption = "\nData from landfire.gov.",
x = "",
y = "Percent of landscape") +
scale_fill_manual(values = cols, name = "") +
coord_flip() +
theme_bw()
evhChart
```
## EVC and EVH together
```{r pipo heatmap, echo=FALSE, message=FALSE, warning=FALSE, fig.width=10, fig.height=9}
# cove forest data from Upper Cheat watershed in WV
pipoHeat <- read_csv("data/pipo_heatmap.csv")
pipoHeatMap <- ggplot(pipoHeat,aes(x=evc, y=evh, fill = percent)) +
geom_tile(colour="white",size=0.2) +
guides(fill=guide_legend(title="Max percent \nper particular \ncombination")) +
scale_x_discrete(labels = function(x) paste0(x, "%")) +
coord_cartesian(ylim=c(0, 30)) +
labs(x="Canopy Cover",
y="Canopy Height (meters)",
title="Canopy cover and height combinations",
subtitle = "Southern Rocky Mountain Ponderosa Pine Woodland",
caption = "\nData from landfire.gov") +
scale_fill_distiller(palette = "Greens", trans = "reverse") +
theme_bw(base_size=14)
pipoHeatMap
```
## PIPO Map
<br>
{width=100%}