Assignment 5 -JMoya
Judith Moya
2024-11-27
library(sf)## Linking to GEOS 3.12.1, GDAL 3.8.4, PROJ 9.3.1; sf_use_s2() is TRUElibrary(tmap)## Breaking News: tmap 3.x is retiring. Please test v4, e.g. with
## remotes::install_github('r-tmap/tmap')library(tigris)## To enable caching of data, set `options(tigris_use_cache = TRUE)`
## in your R script or .Rprofile.#Q1
storm_channel <-st_read("C:/Users/dejmo/OneDrive/Documents/URP Cert/URP 5363- Planning Methods I/Assignment 5/StormChannels/StormChannels.shp")## Reading layer `StormChannels' from data source
## `C:\Users\dejmo\OneDrive\Documents\URP Cert\URP 5363- Planning Methods I\Assignment 5\StormChannels\StormChannels.shp'
## using driver `ESRI Shapefile'
## Simple feature collection with 12042 features and 17 fields
## Geometry type: MULTILINESTRING
## Dimension: XY
## Bounding box: xmin: 2024999 ymin: 13600410 xmax: 2249487 ymax: 13824430
## Projected CRS: NAD83 / Texas South Central (ftUS)corridor_plan <-st_read("C:/Users/dejmo/OneDrive/Documents/URP Cert/URP 5363- Planning Methods I/Assignment 5/CorridorPlans/CorridorPlans.shp")## Reading layer `CorridorPlans' from data source
## `C:\Users\dejmo\OneDrive\Documents\URP Cert\URP 5363- Planning Methods I\Assignment 5\CorridorPlans\CorridorPlans.shp'
## using driver `ESRI Shapefile'
## Simple feature collection with 12 features and 4 fields
## Geometry type: POLYGON
## Dimension: XY
## Bounding box: xmin: 2058688 ymin: 13665110 xmax: 2178301 ymax: 13793820
## Projected CRS: NAD83 / Texas South Central (ftUS)storm_channel<-transform(storm_channel,crs = 4326)
corridor_plan<-transform(corridor_plan,crs = 4326)
#Q2
intersected_channel <- st_intersection(storm_channel, corridor_plan)## Warning: attribute variables are assumed to be spatially constant throughout
## all geometriesbexar_ct <-tracts(state = "TX", county = "Bexar", cb=T)## Retrieving data for the year 2022## | | | 0% | |= | 1% | |= | 2% | |== | 2% | |== | 3% | |=== | 4% | |=== | 5% | |==== | 5% | |==== | 6% | |===== | 7% | |===== | 8% | |====== | 8% | |====== | 9% | |======= | 10% | |======= | 11% | |======== | 11% | |========= | 12% | |========= | 13% | |========== | 15% | |=========== | 15% | |============ | 17% | |============= | 18% | |============== | 20% | |================ | 22% | |================ | 23% | |================= | 24% | |================== | 26% | |=================== | 28% | |===================== | 30% | |====================== | 32% | |========================== | 38% | |============================ | 40% | |============================= | 42% | |=============================== | 44% | |================================ | 46% | |==================================== | 52% | |======================================== | 57% | |=========================================== | 61% | |============================================== | 66% | |================================================= | 71% | |===================================================== | 76% | |========================================================= | 81% | |============================================================ | 86% | |=============================================================== | 91% | |================================================================== | 94% | |=================================================================== | 96% | |===================================================================== | 99% | |======================================================================| 100%tm_shape(bexar_ct)+
tm_borders()+
tm_shape(intersected_channel)+
tm_lines(col="red")
#Q4
library(raster)## Loading required package: spLST <- raster("C:/Users/dejmo/OneDrive/Documents/URP Cert/URP 5363- Planning Methods I/Assignment 5/LC09_028040_20230826.tif")
#Q5
LST <- setMinMax(LST)
LST <- LST - 273.15
cellStats(LST, max)## [1] 61.28771library(ggplot2)
library(rasterVis)## Warning: package 'rasterVis' was built under R version 4.4.2## Loading required package: latticegplot(LST)+
geom_tile(aes(fill = value))+
scale_fill_viridis_c() +
labs(title = "Digital Elevation Model", fill = "Elevation")+
theme_minimal()
#Q6
plot(LST > 40, main = "LST>40",
col = c("#ffffff", "#0000ff"))
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