Assigment5

```{r}

library(sf) library(tigris) library(tmap) library(raster)

#Q 1 bexar_tracts<- tracts(state = “TX”, county = “Bexar”,cb=T) Bondline <- st_read(dsn = “C:/Users/haomi/Desktop/Urban Planning Methods I URP-5363-901-Fall 2023/Nov 07 - Week 12/BondProjectLines2017/BondProjectLines2017.shp”) Bondline <- st_transform(Bondline, crs=4326)

buffer_distance <- 0.01 Bondline <- st_buffer(Bondline, dist = buffer_distance)

tm_shape(bexar_tracts) + tm_borders() + tm_shape(Bondline) + tm_borders(lwd = 2, col = “green”) +
tm_layout(frame = FALSE)

#Q 2 Libraries <- st_read(dsn = “C:/Users/haomi/Desktop/Urban Planning Methods I URP-5363-901-Fall 2023/Nov 07 - Week 12/Libraries/Libraries.shp”) Libraries <- st_transform(Libraries, crs=4326)

tmap_mode(“view”) tm_shape(bexar_tracts) + tm_borders() + tm_shape(Libraries) + tm_dots(size = 0.2, col = “red”) +
tm_layout(title = “SA Libraries”, frame = FALSE)

#Q 3 LST <- raster(‘C:/Users/haomi/Desktop/Urban Planning Methods I URP-5363-901-Fall 2023/Nov 07 - Week 12/LC09_028040_20230826.tif’) LST <- setMinMax(LST) LST

#Q 4 LST = LST - 273.15 plot(LST, main=“Land Surface Temperature of Dallas”)

#Q 5 image(LST, zlim=c(40,100))

```