Project 2 - JMoya
Judith Moya
2024-12-04
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.library(tidycensus)
#Q1
var <- c(poptotal='B03002_001E',
hispanic='B03002_012E')
st <-"WA"
ct <-"King"
df <- get_acs(geography = "tract", variables = var, count=ct,
state = st, output ="wide", year = 2021, geometry = TRUE)## Getting data from the 2017-2021 5-year ACS## Downloading feature geometry from the Census website. To cache shapefiles for use in future sessions, set `options(tigris_use_cache = TRUE)`.## Downloading: 15 kB Downloading: 15 kB Downloading: 15 kB Downloading: 15 kB Downloading: 15 kB Downloading: 15 kB Downloading: 15 kB Downloading: 15 kB Downloading: 15 kB Downloading: 15 kB Downloading: 15 kB Downloading: 15 kB Downloading: 15 kB Downloading: 15 kB Downloading: 15 kB Downloading: 15 kB Downloading: 15 kB Downloading: 15 kB Downloading: 15 kB Downloading: 15 kB Downloading: 31 kB Downloading: 31 kB Downloading: 35 kB Downloading: 35 kB Downloading: 35 kB Downloading: 35 kB Downloading: 35 kB Downloading: 35 kB Downloading: 35 kB Downloading: 35 kB Downloading: 35 kB Downloading: 35 kB Downloading: 35 kB Downloading: 35 kB Downloading: 35 kB Downloading: 35 kB Downloading: 35 kB Downloading: 35 kB Downloading: 35 kB Downloading: 35 kB Downloading: 35 kB Downloading: 35 kB Downloading: 35 kB Downloading: 35 kB Downloading: 35 kB Downloading: 35 kB Downloading: 52 kB Downloading: 52 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df <- na.omit(df)
tm_shape(df)+
tm_polygons(col = "hispanic_pct", title = "Hispanic %")+
tm_compass(type = "8star", position = c("right", "top"), size = 1)+
tm_scale_bar(position = c("left", "bottom"))+
tm_layout(legend.position = c("center", "bottom"),
legend.outside = TRUE,
legend.outside.position = "right")
#Q2
ADA_ramp<-st_read(dsn = "C:/Users/dejmo/OneDrive/Documents/URP Cert/URP 5363- Planning Methods I/Project 2/ADA_(American_with_Disabilities_Act)_Curb_Ramps___ada_ramp_point.shp")## Reading layer `ADA_(American_with_Disabilities_Act)_Curb_Ramps___ada_ramp_point' from data source `C:\Users\dejmo\OneDrive\Documents\URP Cert\URP 5363- Planning Methods I\Project 2\ADA_(American_with_Disabilities_Act)_Curb_Ramps___ada_ramp_point.shp'
## using driver `ESRI Shapefile'
## Simple feature collection with 4676 features and 26 fields
## Geometry type: POINT
## Dimension: XY
## Bounding box: xmin: 1225426 ymin: 70955.09 xmax: 1411831 ymax: 287486.6
## Projected CRS: NAD83(HARN) / Washington North (ftUS)king_tracts<- tracts(state = "WA", county = "King", cb=T)## Retrieving data for the year 2022## | | | 0% | |== | 2% | |=== | 4% | |===== | 7% | |======= | 10% | |========= | 13% | |=========== | 16% | |================================== | 48% | |==================================== | 51% | |====================================== | 54% | |======================================= | 55% | |========================================== | 59% | |============================================ | 62% | |============================================== | 65% | |================================================ | 68% | |=================================================== | 72% | |===================================================== | 75% | |======================================================= | 78% | |========================================================= | 82% | |============================================================ | 85% | |============================================================= | 88% | |================================================================ | 91% | |================================================================== | 95% | |======================================================================| 100%tm_shape(king_tracts)+
tm_borders()+
tm_shape(ADA_ramp)+
tm_dots(col="red", title = "ADA Ramp Location") +
tm_layout(frame = FALSE)
#Q3
metro_transit_routes<-st_read(dsn = "C:/Users/dejmo/OneDrive/Documents/URP Cert/URP 5363- Planning Methods I/Project 2/Transit_Routes_for_King_County_Metro___transitroute_line.shp")## Reading layer `Transit_Routes_for_King_County_Metro___transitroute_line' from data source `C:\Users\dejmo\OneDrive\Documents\URP Cert\URP 5363- Planning Methods I\Project 2\Transit_Routes_for_King_County_Metro___transitroute_line.shp'
## using driver `ESRI Shapefile'
## Simple feature collection with 146 features and 9 fields
## Geometry type: MULTILINESTRING
## Dimension: XY
## Bounding box: xmin: 1225211 ymin: 70794.9 xmax: 1405246 ymax: 320456.3
## Projected CRS: NAD83(HARN) / Washington North (ftUS)tm_shape(king_tracts)+
tm_borders()+
tm_shape(metro_transit_routes)+
tm_lines(lwd=2, col = "blue") +
tm_layout(frame = FALSE)
#Q4
parks<-st_read(dsn = "C:/Users/dejmo/OneDrive/Documents/URP Cert/URP 5363- Planning Methods I/Project 2/Parks_in_King_County___park_area.shp")## Reading layer `Parks_in_King_County___park_area' from data source
## `C:\Users\dejmo\OneDrive\Documents\URP Cert\URP 5363- Planning Methods I\Project 2\Parks_in_King_County___park_area.shp'
## using driver `ESRI Shapefile'## Warning in CPL_read_ogr(dsn, layer, query, as.character(options), quiet, : GDAL
## Message 1: organizePolygons() received an unexpected geometry. Either a
## polygon with interior rings, or a polygon with less than 4 points, or a
## non-Polygon geometry. Return arguments as a collection.## Warning in CPL_read_ogr(dsn, layer, query, as.character(options), quiet, : GDAL
## Message 1: Geometry of polygon of fid 1124 cannot be translated to Simple
## Geometry. All polygons will be contained in a multipolygon.## Warning in CPL_read_ogr(dsn, layer, query, as.character(options), quiet, : GDAL
## Message 1: organizePolygons() received an unexpected geometry. Either a
## polygon with interior rings, or a polygon with less than 4 points, or a
## non-Polygon geometry. Return arguments as a collection.## Warning in CPL_read_ogr(dsn, layer, query, as.character(options), quiet, : GDAL
## Message 1: Geometry of polygon of fid 1441 cannot be translated to Simple
## Geometry. All polygons will be contained in a multipolygon.## Simple feature collection with 1467 features and 13 fields
## Geometry type: MULTIPOLYGON
## Dimension: XY
## Bounding box: xmin: 1220335 ymin: 53899.29 xmax: 1583156 ymax: 287209.5
## Projected CRS: NAD83(HARN) / Washington North (ftUS)#set tmap to automatically check and fix geometries
tmap_options(check.and.fix = TRUE)
sf::st_is_valid(parks)## [1] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## [13] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## [25] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
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## [1465] TRUE TRUE TRUEsf::st_make_valid(parks)## Simple feature collection with 1467 features and 13 fields
## Geometry type: GEOMETRY
## Dimension: XY
## Bounding box: xmin: 1220335 ymin: 53899.29 xmax: 1583156 ymax: 287209.5
## Projected CRS: NAD83(HARN) / Washington North (ftUS)
## First 10 features:
## OBJECTID KC_FAC_FID KCPARKFID SITENAME SITETYPE
## 1 1 2662 6223001 Jenkins Creek Park Park Site
## 2 2 2805 5250702 Street End Park Park Site
## 3 3 5069 4261003 Blue Heron Park Park Site
## 4 4 5080 7242602 Azalea Park Park Site
## 5 5 2814 5250503 Tot Lot Park Park Site
## 6 6 7821 4231802 Linde Hill Park Park Site
## 7 7 8227 4261004 Whispering Willow Park Park Site
## 8 8 7217 4230203 Thayer Place Park Site
## 9 9 7133 3252406 Coe Play Park Park Site
## 10 10 2529 4232501 Bicentennial Park - Tukwila Park Site
## OWNER OWNERTYPE MANAGER MANAGETYPE
## 1 City of Covington City City of Covington City
## 2 City of Kirkland City City of Kirkland City
## 3 City of Lake Forest Park City City of Lake Forest Park City
## 4 City of Snoqualmie City City of Snoqualmie City
## 5 City of Kirkland City City of Kirkland City
## 6 City of Burien City City of Burien City
## 7 City of Lake Forest Park City City of Lake Forest Park City
## 8 City of Seattle City City of Seattle City
## 9 City of Seattle City City of Seattle City
## 10 City of Tukwila City City of Tukwila City
## MAINTD_BY MAINTTYPE SHAPE_Leng SHAPE_Area
## 1 City of Covington City 5632.3248 965530.821
## 2 City of Kirkland City 1489.6380 41080.857
## 3 City of Lake Forest Park City 746.2705 32094.864
## 4 City of Snoqualmie City 1225.8320 87437.482
## 5 City of Kirkland City 620.0069 22800.505
## 6 City of Burien City 846.9323 41232.508
## 7 City of Lake Forest Park City 729.5020 26398.692
## 8 City of Seattle City 239.6966 3341.999
## 9 City of Seattle City 341.9664 7012.632
## 10 City of Tukwila City 1324.8975 49923.600
## geometry
## 1 POLYGON ((1327665 135120.9,...
## 2 POLYGON ((1302344 248195.4,...
## 3 POLYGON ((1284219 277618.1,...
## 4 POLYGON ((1382829 199424.9,...
## 5 POLYGON ((1302069 251672.8,...
## 6 POLYGON ((1266982 177656.5,...
## 7 POLYGON ((1284264 278048.6,...
## 8 POLYGON ((1290335 189511.4,...
## 9 POLYGON ((1262672 237215.8,...
## 10 POLYGON ((1290668 169833.3,...tm_shape(king_tracts)+
tm_borders()+
tm_shape(parks)+
tm_polygons(col = "green") +
tm_layout(frame = FALSE) ## Warning: The shape parks is invalid (after reprojection). See sf::st_is_valid
#Warning message: The shape parks is invalid (after reprojection). See sf::st_is_valid
#Q5
metro_transit_routes <- st_make_valid(metro_transit_routes)
parks <- st_make_valid(parks)
metro_transit_routes<-st_transform(metro_transit_routes, crs = 4326)
parks<-st_transform(parks, crs = 4326)
clipped_routes <- st_intersection(metro_transit_routes, parks)## Warning: attribute variables are assumed to be spatially constant throughout
## all geometries#Q7
library(raster)## Loading required package: spDEM_SW <- raster("C:/Users/dejmo/OneDrive/Documents/URP Cert/URP 5363- Planning Methods I/Project 2/USGS_1_n48w123_20240327.tif")
DEM_SW <- setMinMax(DEM_SW)
cellStats(DEM_SW, max)## [1] 1346.843# view raster attributes
DEM_SW## class : RasterLayer
## dimensions : 3612, 3612, 13046544 (nrow, ncol, ncell)
## resolution : 0.0002777778, 0.0002777778 (x, y)
## extent : -123.0017, -121.9983, 46.99833, 48.00167 (xmin, xmax, ymin, ymax)
## crs : +proj=longlat +datum=NAD83 +no_defs
## source : USGS_1_n48w123_20240327.tif
## names : Layer_1
## values : -13.81634, 1346.843 (min, max)#Get min and max cell values from raster
#NOTE: this code may fail if the raster is too large
cellStats(DEM_SW, min)## [1] -13.81634cellStats(DEM_SW, max)## [1] 1346.843#Q8
plot(DEM_SW < 350, main = "Elevation Criteria", col = c("#ffffff", "#0000ff"))
#Q9
library(ggplot2)
library(rasterVis)## Warning: package 'rasterVis' was built under R version 4.4.2## Loading required package: latticeplot(terrain(DEM_SW, opt = "slope", unit = "degrees") < 3,
main = "Slope Criteria",
col = c("#ffffff", "#ff9900"))
#Q10
plot(terrain(DEM_SW, opt = "aspect", unit = "degrees") >22.5 &
terrain(DEM_SW, opt = "aspect", unit = "degrees") <157.5,
main = "Aspect Criteria")
#Q11 - Writeup
#Very few of King County, WA's census tracts show a concentration of Hispanic population living in poverty above 50%
#The initial focus during Project 1 was King County, WA's disabled population, specifically those with mobility and vision impairments. I continued this focus during Project 2 and obtained GIS data pertaining to ADA ramps, metro transit routes and their relationship with existing parks as all individuals should have access to recreational areas. Available data shows King County has both an extensive transit system plus numerous parks throughout but ADA ramp presence is concentrated in clusters in specific areas.
#Based on available DEM data for King County, WA, the min. elevation is -13.81634 while the max elevation is 1346.843.
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