In-Class Exercise 2: Geospatial Data Wrangling

Published

January 16, 2023

Modified

March 17, 2023

Install of sf & tidyverse

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pacman::p_load(sf, tidyverse, funModeling)

Importing Geospatial

The geoBoundaries data set

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geoNGA <- st_read("data/geospatial/",
                  layer = "geoBoundaries-NGA-ADM2") %>%
  st_transform(crs = 26392)

Reading layer `geoBoundaries-NGA-ADM2' from data source 
  `C:\Users\la935\Desktop\IS415 - GAA\IS415 - GAA (New)\In-Class_Ex\In-Class_Ex02\data\geospatial' 
  using driver `ESRI Shapefile'
Simple feature collection with 774 features and 6 fields
Geometry type: MULTIPOLYGON
Dimension:     XY
Bounding box:  xmin: 2.668534 ymin: 4.273007 xmax: 14.67882 ymax: 13.89442
Geodetic CRS:  WGS 84

The NGA data set

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NGA <- st_read("data/geospatial/",
                  layer = "nga_admbnda_adm2_osgof_20190417") %>%
  st_transform(crs = 26392)

Reading layer `nga_admbnda_adm2_osgof_20190417' from data source 
  `C:\Users\la935\Desktop\IS415 - GAA\IS415 - GAA (New)\In-Class_Ex\In-Class_Ex02\data\geospatial' 
  using driver `ESRI Shapefile'
Simple feature collection with 774 features and 16 fields
Geometry type: MULTIPOLYGON
Dimension:     XY
Bounding box:  xmin: 2.668534 ymin: 4.273007 xmax: 14.67882 ymax: 13.89442
Geodetic CRS:  WGS 84

Importing Aspatial Data

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wp_nga <- read_csv("data/aspatial/WPdx.csv") %>%
  filter(`#clean_country_name` == "Nigeria")

Converting Aspatial Data into Geospatial

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wp_nga$Geometry = st_as_sfc(wp_nga$`New Georeferenced Column`)
wp_nga

# A tibble: 95,008 × 71
   row_id `#source`      #lat_…¹ #lon_…² #repo…³ #stat…⁴ #wate…⁵ #wate…⁶ #wate…⁷
    <dbl> <chr>            <dbl>   <dbl> <chr>   <chr>   <chr>   <chr>   <chr>  
 1 429068 GRID3             7.98    5.12 08/29/… Unknown <NA>    <NA>    Tapsta…
 2 222071 Federal Minis…    6.96    3.60 08/16/… Yes     Boreho… Well    Mechan…
 3 160612 WaterAid          6.49    7.93 12/04/… Yes     Boreho… Well    Hand P…
 4 160669 WaterAid          6.73    7.65 12/04/… Yes     Boreho… Well    <NA>   
 5 160642 WaterAid          6.78    7.66 12/04/… Yes     Boreho… Well    Hand P…
 6 160628 WaterAid          6.96    7.78 12/04/… Yes     Boreho… Well    Hand P…
 7 160632 WaterAid          7.02    7.84 12/04/… Yes     Boreho… Well    Hand P…
 8 642747 Living Water …    7.33    8.98 10/03/… Yes     Boreho… Well    Mechan…
 9 642456 Living Water …    7.17    9.11 10/03/… Yes     Boreho… Well    Hand P…
10 641347 Living Water …    7.20    9.22 03/28/… Yes     Boreho… Well    Hand P…
# … with 94,998 more rows, 62 more variables: `#water_tech_category` <chr>,
#   `#facility_type` <chr>, `#clean_country_name` <chr>, `#clean_adm1` <chr>,
#   `#clean_adm2` <chr>, `#clean_adm3` <chr>, `#clean_adm4` <chr>,
#   `#install_year` <dbl>, `#installer` <chr>, `#rehab_year` <lgl>,
#   `#rehabilitator` <lgl>, `#management_clean` <chr>, `#status_clean` <chr>,
#   `#pay` <chr>, `#fecal_coliform_presence` <chr>,
#   `#fecal_coliform_value` <dbl>, `#subjective_quality` <chr>, …

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wp_sf <- st_sf(wp_nga, crs=4326)
wp_sf

Simple feature collection with 95008 features and 70 fields
Geometry type: POINT
Dimension:     XY
Bounding box:  xmin: 2.707441 ymin: 4.301812 xmax: 14.21828 ymax: 13.86568
Geodetic CRS:  WGS 84
# A tibble: 95,008 × 71
   row_id `#source`      #lat_…¹ #lon_…² #repo…³ #stat…⁴ #wate…⁵ #wate…⁶ #wate…⁷
 *  <dbl> <chr>            <dbl>   <dbl> <chr>   <chr>   <chr>   <chr>   <chr>  
 1 429068 GRID3             7.98    5.12 08/29/… Unknown <NA>    <NA>    Tapsta…
 2 222071 Federal Minis…    6.96    3.60 08/16/… Yes     Boreho… Well    Mechan…
 3 160612 WaterAid          6.49    7.93 12/04/… Yes     Boreho… Well    Hand P…
 4 160669 WaterAid          6.73    7.65 12/04/… Yes     Boreho… Well    <NA>   
 5 160642 WaterAid          6.78    7.66 12/04/… Yes     Boreho… Well    Hand P…
 6 160628 WaterAid          6.96    7.78 12/04/… Yes     Boreho… Well    Hand P…
 7 160632 WaterAid          7.02    7.84 12/04/… Yes     Boreho… Well    Hand P…
 8 642747 Living Water …    7.33    8.98 10/03/… Yes     Boreho… Well    Mechan…
 9 642456 Living Water …    7.17    9.11 10/03/… Yes     Boreho… Well    Hand P…
10 641347 Living Water …    7.20    9.22 03/28/… Yes     Boreho… Well    Hand P…
# … with 94,998 more rows, 62 more variables: `#water_tech_category` <chr>,
#   `#facility_type` <chr>, `#clean_country_name` <chr>, `#clean_adm1` <chr>,
#   `#clean_adm2` <chr>, `#clean_adm3` <chr>, `#clean_adm4` <chr>,
#   `#install_year` <dbl>, `#installer` <chr>, `#rehab_year` <lgl>,
#   `#rehabilitator` <lgl>, `#management_clean` <chr>, `#status_clean` <chr>,
#   `#pay` <chr>, `#fecal_coliform_presence` <chr>,
#   `#fecal_coliform_value` <dbl>, `#subjective_quality` <chr>, …

Projection Transformation

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wp_sf <- wp_sf %>%
  st_transform(crs = 26392)

st_crs(wp_sf)

Coordinate Reference System:
  User input: EPSG:26392 
  wkt:
PROJCRS["Minna / Nigeria Mid Belt",
    BASEGEOGCRS["Minna",
        DATUM["Minna",
            ELLIPSOID["Clarke 1880 (RGS)",6378249.145,293.465,
                LENGTHUNIT["metre",1]]],
        PRIMEM["Greenwich",0,
            ANGLEUNIT["degree",0.0174532925199433]],
        ID["EPSG",4263]],
    CONVERSION["Nigeria Mid Belt",
        METHOD["Transverse Mercator",
            ID["EPSG",9807]],
        PARAMETER["Latitude of natural origin",4,
            ANGLEUNIT["degree",0.0174532925199433],
            ID["EPSG",8801]],
        PARAMETER["Longitude of natural origin",8.5,
            ANGLEUNIT["degree",0.0174532925199433],
            ID["EPSG",8802]],
        PARAMETER["Scale factor at natural origin",0.99975,
            SCALEUNIT["unity",1],
            ID["EPSG",8805]],
        PARAMETER["False easting",670553.98,
            LENGTHUNIT["metre",1],
            ID["EPSG",8806]],
        PARAMETER["False northing",0,
            LENGTHUNIT["metre",1],
            ID["EPSG",8807]]],
    CS[Cartesian,2],
        AXIS["(E)",east,
            ORDER[1],
            LENGTHUNIT["metre",1]],
        AXIS["(N)",north,
            ORDER[2],
            LENGTHUNIT["metre",1]],
    USAGE[
        SCOPE["Engineering survey, topographic mapping."],
        AREA["Nigeria between 6°30'E and 10°30'E, onshore and offshore shelf."],
        BBOX[3.57,6.5,13.53,10.51]],
    ID["EPSG",26392]]