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10 changed files with 41 additions and 84 deletions

2
.gitignore vendored
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@ -4,5 +4,3 @@
.Ruserdata .Ruserdata
data/* data/*
figures/*

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

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

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@ -7,74 +7,47 @@ ifelse(!dir.exists(file.path(getwd(), figure_dir)), dir.create(file.path(getwd()
# set colors # set colors
colors <- list(darkblue = "#062e57", colors <- list(darkblue = "#062e57",
lightblue = "#b1dcf3", lightblue = "#b1dcf3")
lightgrey = "#6D6D6D")
# set dimensions of figures # set dimensions of figures
width <- 8 width <- 8.5
height <- 10 height <- 11
units <- "in" units <- "in"
res <- 600 res <- 600
margin <- 0 margin <- 0
# set state to highlight
state <- c("Wisconsin")
# plot map # plot map
plot_map <- function () { plot_map <- function () {
plot(sf::st_geometry(extent_poly), plot(sf::st_geometry(extent_poly),
col = colors$lightblue, col = colors$darkblue,
border = NA) border = "black")
plot(sf::st_geometry(political$geometry), plot(sf::st_geometry(data$NHDWaterbody),
col = colors$lightgrey, col = colors$lightblue,
border = NA, border = NA,
add = TRUE) add = TRUE)
plot(sf::st_geometry(political[political$NAME_En %in% state, ]), plot(sf::st_geometry(data$NHDArea),
col = colors$darkblue, col = colors$lightblue,
border = NA, border = NA,
add = TRUE) add = TRUE)
plot(sf::st_geometry(data$NHDWaterbody), plot(sf::st_geometry(data$NHDFlowline),
col = colors$lightblue, col = colors$lightblue,
border = NA, lwd = data$NHDFlowline$TotDASqKM^0.3204*0.0446,
add = TRUE) border = NA,
plot(sf::st_geometry(data$NHDArea), add = TRUE)
col = colors$lightblue,
border = NA,
add = TRUE)
plot(sf::st_geometry(data$NHDFlowline),
col = colors$lightblue,
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 # save figure
# tiff(filename = paste0(figure_dir,"/map.tiff"), tiff(filename = paste0(figure_dir,"/map.tiff"),
# width = width, width = width,
# height = height, height = height,
# units = units, units = units,
# res = res, res = res,
# compression = "lzw") compression = "lzw")
# par(mai=c(margin, margin, margin, margin)) par(mai=c(margin, margin, margin, margin))
# par(mar=c(1,1,1,1)) par(mar=c(1,1,1,1))
# plot_map() plot_map()
# dev.off() 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()
png(filename = paste0(figure_dir, "/map.png"), png(filename = paste0(figure_dir, "/map.png"),
width = width, width = width,

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@ -6,10 +6,10 @@ Downloads USGS data for a given location and makes a pretty map of the rivers. T
1. Clone the repository 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). 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: 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 - `01_download_data.R` - This will take the longest. The whole of Wisconsin downloads ~12GB of data
- `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. - `02_process_data.R`
- `03_make_figures.R` - This generates figures in a `figures` directory in the repo. - `03_make_figures.R`
## Example figure ## Example figure
![example figure](example.png) ![example figure](figures/map.png)

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

1 latitude longitude
2 47.73208 47.33402 -93.55154 -93.10419
3 41.49273 42.43754 -86.64896 -86.832

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@ -1,3 +0,0 @@
latitude,longitude
48.50775,-124.91972
46.88398,-122.07015
1 latitude longitude
2 48.50775 -124.91972
3 46.88398 -122.07015

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@ -1,3 +0,0 @@
latitude,longitude
49.17657,-125.43151
45.23644,-115.81455
1 latitude longitude
2 49.17657 -125.43151
3 45.23644 -115.81455

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@ -1,3 +0,0 @@
latitude,longitude
47.73208,-93.55154
41.49273,-86.64896
1 latitude longitude
2 47.73208 -93.55154
3 41.49273 -86.64896