.gitignore

@@ -4,5 +4,3 @@
 .Ruserdata
 
 data/*
-
-figures/*

01_download_data.R

@@ -30,6 +30,7 @@ extent <- list(longitude_max = max(extent$longitude),
                latitude_max = max(extent$latitude),
                latitude_min = min(extent$latitude))
 
+
 # get watershed areas
 extent_huc <- get_huc(AOI = extent_poly, buffer = 0, type = "huc04")
 

02_process_data.R

@@ -1,5 +1,4 @@
 # load libraries
-library(nhdplusTools)
 library(sf)
 
 # reload extent data so you don't need to run the download data script again
@@ -27,18 +26,13 @@ extent <- list(longitude_max = max(extent$longitude),
 # load and crop hydrologic data
 data <- list(NULL)
 sf_use_s2(FALSE)
-layers <- c("NHDArea",
-            "NHDFlowline",
-            "NHDWaterbody",
-            "NHDPlusLandSea")
 for (layer in layers){
   data[[layer]] <- st_crop(st_read(paste0(nhdplusTools_data_dir(),"/data.gpkg"), layer = layer), y = extent_bbox)
 }
 
 # load political boundaries
-political <- st_crop(
-      st_transform(
-        st_read(
-          paste0(data_dir, "/political_boundaries/bound_p/boundaries_p_2021_v3.shp")),
-        crs=crs),
-      y = extent_bbox)
+political <- list(NULL)
+political_boundaries <- list.files(path = paste0(data_dir, "/political_boundaries"))
+for (boundary in political_boundaries) {
+  political[[boundary]] <- st_read(paste0(data_dir, "/political_boundaries/", boundary))
+}

03_make_figures.R

@@ -7,32 +7,21 @@ ifelse(!dir.exists(file.path(getwd(), figure_dir)), dir.create(file.path(getwd()
 
 # set colors
 colors <- list(darkblue = "#062e57",
-               lightblue = "#b1dcf3",
-               lightgrey = "#6D6D6D")
+         lightblue = "#b1dcf3")
 
 # set dimensions of figures
-width <- 8
-height <- 10
+width <- 8.5
+height <- 11
 units <- "in"
 res <- 600
 margin <- 0
 
-# set state to highlight
-state <- c("Wisconsin")
 
 # plot map
 plot_map <- function () {
 plot(sf::st_geometry(extent_poly), 
-       col = colors$lightblue,
-       border = NA)
-  plot(sf::st_geometry(political$geometry), 
-       col = colors$lightgrey,
-       border = NA,
-       add = TRUE)
-  plot(sf::st_geometry(political[political$NAME_En %in% state, ]), 
  col = colors$darkblue,
-       border = NA,
-       add = TRUE)
+ border = "black")
 plot(sf::st_geometry(data$NHDWaterbody), 
  col = colors$lightblue, 
  border = NA,
@@ -46,35 +35,19 @@ plot_map <- function () {
  lwd = data$NHDFlowline$TotDASqKM^0.3204*0.0446,
  border = NA,
  add = TRUE)
-  plot(sf::st_geometry(extent_poly), 
-       col = NA,
-       border = "black",
-       lwd = 1,
-       add = TRUE)
 }
 
 # save figure
-# tiff(filename = paste0(figure_dir,"/map.tiff"),
-#    width = width,
-#    height = height,
-#    units = units,
-#    res = res,
-#    compression = "lzw")
-# par(mai=c(margin, margin, margin, margin))
-# par(mar=c(1,1,1,1))
-# plot_map()
-# dev.off()
-# 
-# jpeg(filename = paste0(figure_dir,"/map.jpg"),
-#    width = width,
-#    height = height,
-#    units = units,
-#    res = res,
-#    quality = 93)
-# par(mai=c(margin, margin, margin, margin))
-# par(mar=c(1,1,1,1))
-# plot_map()
-# dev.off()
+tiff(filename = paste0(figure_dir,"/map.tiff"),
+     width = width,
+     height = height,
+     units = units,
+     res = res,
+     compression = "lzw")
+par(mai=c(margin, margin, margin, margin))
+par(mar=c(1,1,1,1))
+plot_map()
+dev.off()
 
 png(filename = paste0(figure_dir, "/map.png"),
     width = width,

README.md

@@ -6,10 +6,10 @@ Downloads USGS data for a given location and makes a pretty map of the rivers. T
 1. Clone the repository
 2. Edit the extent of the map you want to produce in `extent.csv`. Include lat/long coordinates of two opposite corners (i.e. top-left and bottom-right).
 3. Run the scripts:
-- `01_download_data.R` - This will take the longest. The whole of Wisconsin downloads ~12GB of data. It downloads the data to a `data` directory in the repo
-- `02_process_data.R` - This loads and processes the data. After the initial run downloading the data for a given extent, you can start with this script.
-- `03_make_figures.R` - This generates figures in a `figures` directory in the repo.
+- `01_download_data.R` - This will take the longest. The whole of Wisconsin downloads ~12GB of data
+- `02_process_data.R`
+- `03_make_figures.R`
 
 
 ## Example figure
-![example figure](example.png)
+![example figure](figures/map.png)

extent.csv

@@ -1,3 +1,3 @@
 latitude,longitude
-47.73208,-93.55154
-41.49273,-86.64896
+47.33402,-93.10419
+42.43754,-86.832

extent_olympic.csv

@@ -1,3 +0,0 @@
-latitude,longitude
-48.50775,-124.91972
-46.88398,-122.07015

extent_wa.csv

@@ -1,3 +0,0 @@
-latitude,longitude
-49.17657,-125.43151
-45.23644,-115.81455

extent_wi.csv

@@ -1,3 +0,0 @@
-latitude,longitude
-47.73208,-93.55154
-41.49273,-86.64896