benmarwick · April 27, 2018 22:17 · geranwen · Mar 9, 2021 · markbneal · Feb 18, 2022
diff --git a/gistfile1.txt b/gistfile1.txt

 library(sf) 
 library(tidyverse)

 # read in the shapefile first, that gives us the CRS for the analysis
 polygons <- st_read("polygons.shp")

 # read in the points
 points <- read_csv('points.csv')

 # convert the points to an sf object
 points_sf <- st_as_sf(points, coords = c("decimalLongitude", "decimalLatitude"))

 # set CRS for the points to be the same as shapefile
 st_crs(points_sf) <- st_crs(polygons)

 # plot to see how they relate
 ggplot() +
  geom_sf(data = polygons) +
  geom_sf(data = points_sf) +
  theme_minimal()

 # some points are out of the polygon, lets filter out
 # so we get only points in the polygon
 points_sf_joined <- 
  st_join(points_sf, polygons) %>%  # spatial join to get intersection of points and poly
  filter(!is.na(rgn_name)) # rgn_name just one col from the polygon data that I chose to filter on, could use any. The idea is to get only the points that fall in the polygon

 # plot again 
 ggplot() +
  geom_sf(data = polygons) +
  geom_sf(data = points_sf_joined) +
  theme_minimal()

 # we see only points in the polygon, great!

 # the st_bbox method is less ideal because the bbox is the rectangle that the polygon fits in, not the exact shape of the polygon. With a spatial join, we can filter by location in/out of the exact shape of the polygon.

	library(sf)
	library(tidyverse)

	# read in the shapefile first, that gives us the CRS for the analysis
	polygons <- st_read("polygons.shp")

	# read in the points
	points <- read_csv('points.csv')

	# convert the points to an sf object
	points_sf <- st_as_sf(points, coords = c("decimalLongitude", "decimalLatitude"))

	# set CRS for the points to be the same as shapefile
	st_crs(points_sf) <- st_crs(polygons)

	# plot to see how they relate
	ggplot() +
	geom_sf(data = polygons) +
	geom_sf(data = points_sf) +
	theme_minimal()

	# some points are out of the polygon, lets filter out
	# so we get only points in the polygon
	points_sf_joined <-
	st_join(points_sf, polygons) %>% # spatial join to get intersection of points and poly
	filter(!is.na(rgn_name)) # rgn_name just one col from the polygon data that I chose to filter on, could use any. The idea is to get only the points that fall in the polygon

	# plot again
	ggplot() +
	geom_sf(data = polygons) +
	geom_sf(data = points_sf_joined) +
	theme_minimal()

	# we see only points in the polygon, great!

	# the st_bbox method is less ideal because the bbox is the rectangle that the polygon fits in, not the exact shape of the polygon. With a spatial join, we can filter by location in/out of the exact shape of the polygon.