R Notebook
Lauren DeMarco Assignment 3
library(terra)## Warning: package 'terra' was built under R version 4.2.3## terra 1.7.71library(tidyterra)## Warning: package 'tidyterra' was built under R version 4.2.3##
## Attaching package: 'tidyterra'## The following object is masked from 'package:stats':
##
## filterlibrary(sp)## Warning: package 'sp' was built under R version 4.2.3library(ggplot2)
library(ggthemes)## Warning: package 'ggthemes' was built under R version 4.2.3library(urbnmapr)
library(sf)## Warning: package 'sf' was built under R version 4.2.3## Linking to GEOS 3.11.0, GDAL 3.5.3, PROJ 9.1.0; sf_use_s2() is TRUEsetwd("/Users/laurendemarco/Downloads/DIDA370")
rast <- rast("NE1_50M_SR_W.tif")
#rast <- terra::project(rast, "EPSG:32116", method = "bilinear")
rast## class : SpatRaster
## dimensions : 5400, 10800, 3 (nrow, ncol, nlyr)
## resolution : 0.03333333, 0.03333333 (x, y)
## extent : -180, 180, -90, 90 (xmin, xmax, ymin, ymax)
## coord. ref. : lon/lat WGS 84 (EPSG:4326)
## source : NE1_50M_SR_W.tif
## colors RGB : 1, 2, 3
## names : NE1_50M_SR_W_1, NE1_50M_SR_W_2, NE1_50M_SR_W_3map 1 static
plot(rast) #on it own it is a full world map
#need to use the crop function and a US states basemap to map only the United States
#state_map.shp
states <- get_urbn_map("states", sf = TRUE)
states %>%
st_transform("EPSG:32116")## old-style crs object detected; please recreate object with a recent sf::st_crs()plot (states)## old-style crs object detected; please recreate object with a recent sf::st_crs()
## old-style crs object detected; please recreate object with a recent sf::st_crs()
## old-style crs object detected; please recreate object with a recent sf::st_crs()
## old-style crs object detected; please recreate object with a recent sf::st_crs()
## old-style crs object detected; please recreate object with a recent sf::st_crs()
## old-style crs object detected; please recreate object with a recent sf::st_crs()
## old-style crs object detected; please recreate object with a recent sf::st_crs()
## old-style crs object detected; please recreate object with a recent sf::st_crs()
## old-style crs object detected; please recreate object with a recent sf::st_crs()
## old-style crs object detected; please recreate object with a recent sf::st_crs()
## old-style crs object detected; please recreate object with a recent sf::st_crs()
## old-style crs object detected; please recreate object with a recent sf::st_crs()
## old-style crs object detected; please recreate object with a recent sf::st_crs()
## old-style crs object detected; please recreate object with a recent sf::st_crs()
#running this before the next cell is the the only way I was able to get it to work
#storing the crs info into variable
#Found the info for how to do this here, https://gis.stackexchange.com/questions/111226/how-to-assign-crs-to-rasterlayer-in-r
crs_rast <- crs(rast)
crs_states <- st_crs(states)## old-style crs object detected; please recreate object with a recent sf::st_crs()#make states' geometry to match raster CRS if they are not the same
#i learned how to work with if statements in HARP 150 and HARP 151
if (!identical(crs_rast, crs_states)) {
states <- st_transform(states, crs = crs_rast) #getting the info to match between state and raster data
}## old-style crs object detected; please recreate object with a recent sf::st_crs()US_map <- mask(rast, states) #working with the st_crop and crop functions did not work for me, so I tried the mask function which I saw here: https://datacarpentry.org/semester-biology/materials/spatial-data-cropping-R/ and it did work! ##
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plot(US_map)
#create the US map only with the state outline, same thing before just displayed differently
ggplot()+
geom_spatraster(data = US_map)+
geom_sf(data = states, mapping = aes(), color = "pink")+
theme_map()+
scale_fill_whitebox_c(
na.value = "white")+
labs(title = "Map of US",
fill = "Fill")+
theme(plot.title = element_text(hjust = 0.5, size = 16),
legend.position="right")## <SpatRaster> resampled to 5e+05 cells for plotting
## ! `tidyterra::geom_spatraster()`: Plotting 3 overlapping layers: NE1_50M_SR_W_1, NE1_50M_SR_W_2, and NE1_50M_SR_W_3. Either:
##
## Use `facet_wrap(~lyr)` for faceting or
##
## Use `aes(fill = <name_of_layer>)` for displaying single layers
map 2 dynamic 2 variable
library(leaflet)## Warning: package 'leaflet' was built under R version 4.2.3#my map of NY counties
counties <- get_urbn_map("counties", sf = TRUE)
#filter the data to get just NYS
counties <- counties %>%
filter(state_abbv == "NY") %>%
st_transform("EPSG:4326")## old-style crs object detected; please recreate object with a recent sf::st_crs()#base leaflet map
leaflet() %>%
leaflet::addPolygons(data = counties,
color = "green")#hogs by inventory
hogs <- st_read("N-30.xls")## Multiple layers are present in data source /Users/laurendemarco/Downloads/DIDA370/N-30.xls, reading layer `Hogs'.
## Use `st_layers' to list all layer names and their type in a data source.
## Set the `layer' argument in `st_read' to read a particular layer.## Warning in CPL_read_ogr(dsn, layer, query, as.character(options), quiet, :
## automatically selected the first layer in a data source containing more than
## one.## Reading layer `Hogs' from data source
## `/Users/laurendemarco/Downloads/DIDA370/N-30.xls' using driver `XLS'## Warning: no simple feature geometries present: returning a data.frame or tbl_dfhogs#do not need all the hog data, just this
hogs_updated <- hogs %>%
select (Field1, Field2, Field5)
#rename columns
colnames(hogs_updated) <- c("county_name","2012","1997")
#only take specifc columns from the datasete
hogs_updated <- hogs_updated[7:63, ] #learned how to do this in DIDA 325 final project working with manipulting and cleaning data #in counties data could drop the word "County" and " " to create uniformity for a future merge
counties$county_name <- gsub("County", "", counties$county_name)
counties$county_name <- gsub(" ", "", counties$county_name)
hogs_updated$county_name <- gsub(" ", "", hogs_updated$county_name)#combined dataset with the hog data and geospatial data
merged_county <- merge(counties, hogs_updated, by = "county_name", all.x = TRUE) #learned how to do merges this past summer working as an analyst intern, but also can include a link on syntax: https://www.rdocumentation.org/packages/base/versions/3.6.2/topics/merge
#select columns from one big dataframe
updated_data <- merged_county %>%
select(county_name, "2012", "1997", geometry)
updated_data$`2012` <- as.numeric(updated_data$`2012`) #making sure the year columns are numeric, learned in DIDA 325## Warning: NAs introduced by coercionupdated_data$`1997` <- as.numeric(updated_data$`1997`)## Warning: NAs introduced by coercion#2012 data
map1 <- leaflet() %>%
addTiles() %>% # Add default tile layer
addPolygons(data = updated_data,
fillColor = ~colorQuantile("YlOrRd", updated_data$`2012`)(`2012`), # Fill color based on 2012 data
fillOpacity = 0.6, # Opacity of fill
color = "black",
weight = 1, # Border color
popup = ~paste("County:", county_name, "<br>", "2012 Data:", `2012`)) %>%
addLegend("bottomright",
pal = colorQuantile("YlOrRd", updated_data$`2012`),
values=updated_data$'2012',
title = '2012',
group = "2012")
map1#1997 data
map2 <- leaflet() %>%
addTiles() %>% # Add default tile layer
addPolygons(data = updated_data,
fillColor = ~colorQuantile("YlOrRd", updated_data$`1997`)(`1997`), # Fill color based on 1997 data
fillOpacity = 0.6, # Opacity of fill
color = "black",
weight = 1, # Border color
popup = ~paste("County:", county_name, "<br>", "1997 Data:", `1997`)) %>%
addLegend("bottomright",
pal = colorQuantile("YlOrRd", updated_data$`1997`),
values=updated_data$'1997',
title = '1997',
group = "1997")
map2Combining the two maps and making it dynamic, Final map 2
leaflet() %>%
addProviderTiles(providers$CartoDB.Positron) %>%
addPolygons(data = updated_data,
fillColor = ~colorQuantile("YlOrRd", updated_data$`2012`)(`2012`),
fillOpacity = 0.6,
color = "black",
weight = 1,
popup = ~paste("County:", updated_data$county_name, "<br>", "2012 Data:", updated_data$`2012`),
group = "2012") %>%
addPolygons(data = updated_data,
fillColor = ~colorQuantile("YlOrRd", updated_data$`1997`)(`1997`),
fillOpacity = 0.6,
color = "black",
weight = 1,
popup = ~paste("County:", updated_data$county_name, "<br>", "1997 Data:", updated_data$`1997`),
group = "1997") %>%
addLegend("bottomright",
pal = colorQuantile("YlOrRd", updated_data$`2012`),
values=updated_data$'2012',
title = '2012',
group = "2012") %>%
addLegend("bottomright",
pal = colorQuantile("YlOrRd", updated_data$`1997`),
values=updated_data$'1997',
title = '1997',
group = "1997") %>%
addLayersControl(overlayGroups = c("2012", "1997"),
options = layersControlOptions(collapsed = FALSE))