This repository contains source shapefiles and visualization scripts for the Trend CT story: How the drought has spread in Connecticut .

What’s in this walkthrough:

Loading libraries

library(tidyr)
library(dplyr)
library(ggmap)
library(ggplot2)
library(rgdal)
library(sp)
library(maptools)
library(scales)
library(extrafont)
library(lubridate)
library(magick)

Prepping the shape files

# Bring in the base layer of US state borders
usmap <- readOGR(dsn="us_shape", layer="statesp010g")
## OGR data source with driver: ESRI Shapefile 
## Source: "us_shape", layer: "statesp010g"
## with 61 features
## It has 11 fields
# Convert the shapefile into a dataframe that we can work with
usfort <- fortify(usmap, region="STATE_ABBR")

# NOTE: YOU CAN CREATE STATE-SPECIFIC MAPS FOR YOUR STATE IF YOU SUB OUT "CT" 
# AND THEN CHANGE THE BOUNDING BOX LATITUDES AND LONGITUDES (XLIM AND YLIM IN COORD_MAP)
# IN THE CONNECTICUT CHUNK OF CODE BELOW

# Creating a shapefile specifically for Connecticut
ctfort <- filter(usfort, id=="CT")

# Creating a shapefile of all state shapes minus Connecticut
not_ct_fort <- filter(usfort, id!="CT")

# Compiling a list of the folders in the 'shapes' folder
shape_list <- list.files("shapes")

United States

for (i in 1:length(shape_list)) {
  
  # Loop through and gets the folder name
  file_name <- shape_list[i]
  
  # Figures out the exact folder location
  dsn_name <- paste0("shapes/", file_name)
  
  # The shapefile itself is the same as the directory minus "_M"
  layer_name <- gsub("_M", "", file_name)
  
  # The shapefiles/directories are labeled by date, so we want to extract that and turn it into a string (AP format)
  the_date <- gsub("USDM_", "", layer_name)
  the_date <- ymd(the_date)
  ap_date <- paste0(month(the_date, label=T, abbr=F), " ", day(the_date), ", ", year(the_date))
  
  # Now that we've got the name of the shapefile and the folder location, we can read in the data
  droughtmap <- readOGR(dsn=dsn_name, layer=layer_name)
  
  # Transform the shapefile into a dataframe so we can work with it in R
  droughtfort <- fortify(droughtmap, region="DM")
  
  gg <- ggplot() 
  
  # This line will bring in the drought shapefile
  gg <- gg +  geom_polygon(data = droughtfort, aes(x=long, y=lat, group=group, fill=id), color = "black", size=0) 
  
  # This line brings in the US borders as a layer
  gg <- gg +  geom_polygon(data = usfort, aes(x=long, y=lat, group=group, fill=total), color = "gray73", fill=NA, size=0.2) 
  
  # This sets the boundaries of the view so it excludes Alaska and Hawaii
  gg <- gg +  coord_map("polyconic", xlim=c(-125, -70), ylim=c(25.5, 48.5)) 
  
  # This line sets the colors and text for the legend items
  gg <- gg +  scale_fill_manual(name="", values = c("#FFFF00", "#FCD37F", "#FFAA00", "#E60000", "#730000"),
                                labels = c("Abnormal", "Moderate", "Severe", "Extreme", "Exceptional"))
  
  # The rest of the code in this chunk is for blurbs and style.
  gg <- gg + labs(x=NULL, y=NULL, 
                  title="Drought in the U.S.",
                  subtitle=ap_date,
                  caption="National Drought Mitigation Center (NDMC), \nthe U.S. Department of Agriculture (USDA), \n and the National Oceanic and Atmospheric Association (NOAA)")
  gg <- gg + theme(plot.title=element_text(face="bold", family="Lato Regular", size=13))
  gg <- gg + theme(plot.caption=element_text(face="bold", family="Lato Regular", size=7, color="gray", margin=margin(t=10, r=80)))
  gg <- gg + theme(legend.position="top")
  gg <- gg + theme(axis.line =  element_blank(),
                   axis.text =  element_blank(),
                   axis.ticks =  element_blank(),
                   panel.grid.major = element_blank(),
                   panel.grid.minor = element_blank(),
                   panel.border = element_blank(),
                   panel.background = element_blank()) 
print(gg)
}
## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160105_M", layer: "USDM_20160105"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160112_M", layer: "USDM_20160112"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160119_M", layer: "USDM_20160119"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160126_M", layer: "USDM_20160126"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160202_M", layer: "USDM_20160202"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160209_M", layer: "USDM_20160209"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160216_M", layer: "USDM_20160216"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160223_M", layer: "USDM_20160223"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160301_M", layer: "USDM_20160301"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160308_M", layer: "USDM_20160308"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160315_M", layer: "USDM_20160315"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160322_M", layer: "USDM_20160322"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160329_M", layer: "USDM_20160329"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160405_M", layer: "USDM_20160405"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160412_M", layer: "USDM_20160412"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160419_M", layer: "USDM_20160419"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160426_M", layer: "USDM_20160426"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160503_M", layer: "USDM_20160503"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160510_M", layer: "USDM_20160510"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160517_M", layer: "USDM_20160517"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160524_M", layer: "USDM_20160524"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160531_M", layer: "USDM_20160531"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160607_M", layer: "USDM_20160607"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160614_M", layer: "USDM_20160614"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160621_M", layer: "USDM_20160621"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160628_M", layer: "USDM_20160628"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160705_M", layer: "USDM_20160705"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160712_M", layer: "USDM_20160712"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160719_M", layer: "USDM_20160719"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160726_M", layer: "USDM_20160726"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160802_M", layer: "USDM_20160802"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160809_M", layer: "USDM_20160809"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160816_M", layer: "USDM_20160816"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160823_M", layer: "USDM_20160823"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160830_M", layer: "USDM_20160830"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160906_M", layer: "USDM_20160906"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160913_M", layer: "USDM_20160913"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160920_M", layer: "USDM_20160920"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160927_M", layer: "USDM_20160927"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20161004_M", layer: "USDM_20161004"
## with 5 features
## It has 4 fields

U.S. GIF

# Creates a list of the images in us_maps_gif
the_list <- paste0("us_maps_gif/", list.files("us_maps_gif/"))

# This function applies the function image_read to the files in the_list
frames <- lapply(the_list, image_read)

# This creates a gif of the frames
animation <- image_animate(image_join(frames), fps=4)

# Saves image
image_write(animation,"us_map.gif")
## [1] "us_map.gif"
# Loading image
US GIF

US GIF

Connecticut

for (i in 1:length(shape_list)) {
  
  # Loop through and gets the folder name
  file_name <- shape_list[i]
  
  # Figures out the exact folder location
  dsn_name <- paste0("shapes/", file_name)
  
  # The shapefile itself is the same as the directory minus "_M"
  layer_name <- gsub("_M", "", file_name)
  
  # The shapefiles/directories are labeled by date, so we want to extract that and turn it into a string (AP format)
  the_date <- gsub("USDM_", "", layer_name)
  the_date <- ymd(the_date)
  ap_date <- paste0(month(the_date, label=T, abbr=F), " ", day(the_date), ", ", year(the_date))
  
  # Now that we've got the name of the shapefile and the folder location, we can read in the data
  droughtmap <- readOGR(dsn=dsn_name, layer=layer_name)
  
  # Transform the shapefile into a dataframe so we can work with it in R
  droughtfort <- fortify(droughtmap, region="DM")
  
  # Same as annotations above except where noted
  gg <- ggplot() 
  gg <- gg +  geom_polygon(data = droughtfort, aes(x=long, y=lat, group=group, fill=id), color = NA, size=0.5) 
  
  # Adds a layer that whites out all states minus Connecticut so it covers the drought layer in all areas except Connecticut
  gg <- gg +  geom_polygon(data = not_ct_fort, aes(x=long, y=lat, group=group, fill=total), color = "white", fill="white", size=.5) 
  
  # Adds a layer for Connecticut so it adds a black border for clarity
  gg <- gg +  geom_polygon(data = ctfort, aes(x=long, y=lat, group=group, fill=total), color = "gray73", fill=NA, size=0.5) 
  
  # This is the bounding box so it sets the viewpoint to just Connecticut
  # Change this bounding box below if you want to set it anywhere else
  gg <- gg +  coord_map("polyconic", xlim=c(-73.8, -71.6), ylim=c(40.9, 42.2)) 
  gg <- gg +  scale_fill_manual(name="", values = c("#FFFF00", "#FCD37F", "#FFAA00", "#E60000", "#730000"),
                                labels = c("Abnormal", "Moderate", "Severe", "Extreme", "Exceptional"))
  gg <- gg + labs(x=NULL, y=NULL, 
                  title="Drought in Connecticut",
                  subtitle=ap_date,
                  caption="National Drought Mitigation Center (NDMC), \nthe U.S. Department of Agriculture (USDA), \n and the National Oceanic and Atmospheric Association (NOAA)")
  gg <- gg + theme(plot.title=element_text(face="bold", family="Lato Regular", size=13))
  gg <- gg + theme(plot.caption=element_text(face="bold", family="Lato Regular", size=7, color="gray", margin=margin(t=10, r=80)))
  gg <- gg + theme(legend.position="top")
  gg <- gg + theme(axis.line =  element_blank(),
                   axis.text =  element_blank(),
                   axis.ticks =  element_blank(),
                   panel.grid.major = element_blank(),
                   panel.grid.minor = element_blank(),
                   panel.border = element_blank(),
                   panel.background = element_blank()) 
print(gg)
}
## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160105_M", layer: "USDM_20160105"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160112_M", layer: "USDM_20160112"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160119_M", layer: "USDM_20160119"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160126_M", layer: "USDM_20160126"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160202_M", layer: "USDM_20160202"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160209_M", layer: "USDM_20160209"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160216_M", layer: "USDM_20160216"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160223_M", layer: "USDM_20160223"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160301_M", layer: "USDM_20160301"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160308_M", layer: "USDM_20160308"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160315_M", layer: "USDM_20160315"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160322_M", layer: "USDM_20160322"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160329_M", layer: "USDM_20160329"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160405_M", layer: "USDM_20160405"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160412_M", layer: "USDM_20160412"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160419_M", layer: "USDM_20160419"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160426_M", layer: "USDM_20160426"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160503_M", layer: "USDM_20160503"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160510_M", layer: "USDM_20160510"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160517_M", layer: "USDM_20160517"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160524_M", layer: "USDM_20160524"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160531_M", layer: "USDM_20160531"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160607_M", layer: "USDM_20160607"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160614_M", layer: "USDM_20160614"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160621_M", layer: "USDM_20160621"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160628_M", layer: "USDM_20160628"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160705_M", layer: "USDM_20160705"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160712_M", layer: "USDM_20160712"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160719_M", layer: "USDM_20160719"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160726_M", layer: "USDM_20160726"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160802_M", layer: "USDM_20160802"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160809_M", layer: "USDM_20160809"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160816_M", layer: "USDM_20160816"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160823_M", layer: "USDM_20160823"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160830_M", layer: "USDM_20160830"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160906_M", layer: "USDM_20160906"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160913_M", layer: "USDM_20160913"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160920_M", layer: "USDM_20160920"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20160927_M", layer: "USDM_20160927"
## with 5 features
## It has 4 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "shapes/USDM_20161004_M", layer: "USDM_20161004"
## with 5 features
## It has 4 fields

CT GIF

# Same code as above but just for a different folder this time
the_list <- paste0("ct_maps_gif/", list.files("ct_maps_gif/"))
frames <- lapply(the_list, image_read)
animation <- image_animate(image_join(frames), fps=4)
image_write(animation,"ct_map.gif")
## [1] "ct_map.gif"
CT GIF

CT GIF