Craig F. Barrett
April 07, 2021
Department of Biology
West Virginia University
Morgantown, WV USA 26506
cfb0001@mail.wvu.edu
# install packages if needed
# install.packages(c("rgbif", "ggplot2", "tidyverse", "gganimate", "ggthemes", "sf", "tools", "maps", "rnaturalearth", "rnaturalearthdata"))
# load libraries
library(shiny)
library(ggplot2)
library(tidyverse)
library(gganimate)
library(ggthemes)
library(sf)
library("tools")
library(maps)
library("rnaturalearth")
library("rnaturalearthdata")
#read in data, convert to data.frame, set "awn" as a factor
setwd(choose.dir())
awn <- read.csv("awndatanew.csv")
awn <- data.frame(awn)# remove duplicate records based on latitude
awn <- awn %>% distinct(decimalLatitude, .keep_all = TRUE)
awns <- as.factor(awn$awn)
awn <- data.frame(awn)
world <- ne_countries(scale = "medium", returnclass = "sf")
## class(world)
states <- st_as_sf(map("state", plot = FALSE, fill = TRUE))
## head(states)
states <- cbind(states, st_coordinates(st_centroid(states)))st_centroid assumes attributes are constant over geometries of xst_centroid does not give correct centroids for longitude/latitude data#Generate the map and coordinate boundaries
usa <- ggplot(data = world) +
#mutate(year = as.numeric(awn$year)) +
geom_sf(data = states, fill = NA) +
coord_sf(xlim = c(-96, -70), ylim = c(28, 45), expand = FALSE)
# map the occurrence data
JSmap <- usa +
geom_point(data = awn, shape = 21, colour="black", aes(x=decimalLongitude, y=decimalLatitude, fill=awns), size=6, stroke=1) +
#transition_states(year, transition_length = 1, state_length = 1) +
scale_fill_manual(values=c("red", "blue")) +
transition_time(year) +
labs(title = 'Digitized herbarium records of Microstegium vimineum', subtitle = 'Year: {round(frame_time,0)}') +
shadow_mark()
#animate!
JSmap
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Finalizing encoding... done!#save animation as a .gif
anim_save("Js_awn_map_red_blue.gif", JSmap)
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Finalizing encoding... done!#################################
### Interactive leaflet map #####
#################################
library(leaflet)
library(dplyr)
# read in data
awn<-read.csv("awndatanew.csv")
# add interactive popup information from data file
awn<-awn%>%mutate(popup_info=paste(Collection,"<br/>",year,"<br/>","Awn?",awn,"<br/>","Elevation",elev,"<br/>",County))
# map the points based on lat/lon
leaflet()%>%addTiles()%>%addCircleMarkers(data=awn, lat=~decimalLatitude,lng=~decimalLongitude,radius=4,color= ~awn,popup = ~popup_info)Data contains 1 rows with either missing or invalid lat/lon values and will be ignored
#create color pallete for awned/awnless records
colors<-c("red","blue")
pal<-colorFactor(colors, awn$awn)
# Now, map with colors indicating awned/awnless
leaflet()%>%addTiles()%>%addCircleMarkers(data=awn, lat=~decimalLatitude,lng=~decimalLongitude,radius=4,popup = ~popup_info,color=~pal(awn))Data contains 1 rows with either missing or invalid lat/lon values and will be ignored