#load race variables for dissimilarity analysis
census_vars <- load_variables(2020, "acs5", cache = TRUE)
race_vars <- c(white = "B03002_003",
black = "B03002_004",
hispanic = "B03001_003")
tarrant_race <- get_acs(
geography = "tract",
variables = race_vars,
state = "TX",
county = "Tarrant",
year = 2020,
geometry = TRUE,
output = "wide")## Getting data from the 2016-2020 5-year ACS## Downloading feature geometry from the Census website. To cache shapefiles for use in future sessions, set `options(tigris_use_cache = TRUE)`.##
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|======================================================================| 100%#arlington city limits
arlington_boundary <- st_read(dsn = "C:/Users/txs401/OneDrive - University of Texas at San Antonio/Desktop/Final Project/Sam/Municipal_Boundary/Municipal_Boundary.shp")## Reading layer `Municipal_Boundary' from data source
## `C:\Users\txs401\OneDrive - University of Texas at San Antonio\Desktop\Final Project\Sam\Municipal_Boundary\Municipal_Boundary.shp'
## using driver `ESRI Shapefile'
## Simple feature collection with 4 features and 4 fields
## Geometry type: POLYGON
## Dimension: XY
## Bounding box: xmin: 2357410 ymin: 6899355 xmax: 2418177 ymax: 6983111
## Projected CRS: NAD83 / Texas North Central (ftUS)arlington_boundary <- arlington_boundary[-c(1,2, 3),]
#set crs
arlington_boundary <- st_transform(arlington_boundary, crs = 4269)
tarrant_race <- st_transform(tarrant_race, crs = 4269)
#intersect race variables with city boundary
arlington_race <- st_intersection(arlington_boundary,tarrant_race)## Warning: attribute variables are assumed to be spatially constant throughout all
## geometries#sum of races
sum(arlington_race$whiteE) #white## [1] 192731sum(arlington_race$blackE) #black## [1] 117752sum(arlington_race$hispanicE) #hispanic## [1] 138762arlington_race$white_total <- sum(arlington_race$whiteE)
arlington_race$black_total <- sum(arlington_race$blackE)
arlington_race$hispanic_total <- sum(arlington_race$hispanicE)
arlington_race$nonwhite_total <- sum(arlington_race$blackE, arlington_race$hispanicE)
#white-black dissimilarity
arlington_race$wb <- abs(arlington_race$blackE/arlington_race$black_total
-arlington_race$whiteE/arlington_race$white_total)
#white-hispanic dissimilarity
arlington_race$wh <- abs(arlington_race$hispanicE/arlington_race$hispanic_total
-arlington_race$whiteE/arlington_race$white_total)
#white-non white dissimilarity
arlington_race$white_nonwhite <- abs((arlington_race$hispanicE + arlington_race$blackE)
/arlington_race$nonwhite_total
-arlington_race$whiteE
/arlington_race$white_total)#summarize
results_dissimilarity <- arlington_race %>%
group_by(GEOID) %>%
summarize(BWD = 0.5*sum(wb, na.rm=TRUE), HWD = 0.5*sum(wh, na.rm=TRUE),
WNWD = 0.5*sum(white_nonwhite, na.rm = TRUE))
## BWD: Black-White Dissimilarity Index; HWD: Hispanic-White Dissimilarity Index
tmap_mode("view") +
tm_shape(results_dissimilarity) +
tm_fill(col = c("BWD","HWD"), palette = "magma", alpha = 0.5) +
tm_borders() +
#tm_shape(arlington_trails) +
tm_lines(col = "#3ecf2f", lwd = 2)## tmap mode set to interactive viewing