Gist to calculate the areas of SF CBDs, commercial land use, and total parcel area

cbd_areas.R

library(sf)
library(mapview)
library(tidyverse)
library(measurements)
library(units)
library(glue)

# Dissolve and summarize CBD parcel areas
cbd_parcels <- st_read("data/cbd_parcels.shp")
cbds_area <- cbd_parcels %>%
  group_by() %>%
  summarize() %>%
  mutate(area = st_area(.)) %>%
  pull()

# Convert to square miles, already in square meter units
units(cbds_area) = "mi2"

# Get land use from DataSF
# Note: "The commercial data was not updated; the commercial data will be updated in next year's 2024 release."
# Cf. https://sfplanninggis.s3.amazonaws.com/LUDB_2023_Summary.pdf
sf_landuse <- st_read("https://data.sfgov.org/resource/fdfd-xptc.geojson?$limit=9999999")
# totalcomm = Total Commercial Only Sq Ft
# Cf. https://data.sfgov.org/Geographic-Locations-and-Boundaries/San-Francisco-Land-Use-2023/fdfd-xptc/about_data
comm_area <- sf_landuse %>%
  st_drop_geometry() %>%
  summarize(comm_area = sum(as.numeric(totalcomm))) %>%
  pull()

# Convert from square feet to square miles
units(comm_area) <- as_units("ft2")
units(comm_area) = "mi2"

# SF area
# doesn't include area of the streets
sf_area <- sf_landuse %>%
  st_transform(7131) %>%
  group_by() %>%
  summarize() %>%
  mutate(area = st_area(.)) %>%
  pull()

# convert to square miles, already in square meter units
units(sf_area) = "mi2"

# Statements
glue("CBDs in San Francisco cover {scales::percent(as.numeric(cbds_area/comm_area), accuracy = 0.1)} of all commercially zoned land in the city.")
# CBDs in San Francisco cover 15.2% of all commercially zoned land in the city.
glue("CBDs cover {scales::percent(as.numeric(cbds_area/sf_area), accuracy = 0.1)} of San Francisco.")
# CBDs cover 4.5% of San Francisco.