Extract Geodata from different sources

Introduction

This vignette provides some guidance to USAID/OHA Data Analysts on how to extract geospatial data from different sources

Geospatial Datasets

PEPFAR/ICPI GIS Cluster provides a global geospatial data set that define the boundaries of PEPFAR countries organizational units. This data set contains all country, SNU, PSNU and Community boundaries along with their respective unique identification id (uid) and have been used thematic mapping and other spatial analyses. Other external data sources such as Naturalearh and GADM have also been very helpful.

Below are different ways analysts could / should be using this package to extract PEPFAR geodata for their respective countries.

Prerequisites

library(glamr)         # OHA/SI utility package
library(gisr)          # OHA/SI geospatial package 
library(sf)            # Spatial data management

Locate and setup vector data path

Current PEPFAR Geospatial data sets can be found under OHA/SI Google Drive SI Folder and in Spatial Files sub-folder.

In order to take full advantage of all the OHA/SI R packages, it’s recommended to setup the location of your data directories. These should ideally be outside your github projects directory. One of the directories should be dedicated to geospatial data and should be set using glamr::set_paths(folderpath_vector = "<my-geodata-folder>").

Below is an example. This assumes your R / Github projects folder is under Documents folder on your local computer and your working off a R Project in a sub-folder. In this example, your geospatial data folder will be a sibling of your R / Github projects folder.

curr_path <- "C:/Users/<username>/Documents/projects/gisr" # Windows
#or 
#curr_path <- "~/Documents/projects/gisr"                  # Mac or linux

geopath <- "../../Geodata"

glamr::set_paths(folderpath_vector = geopath)

# verify path
glamr::si_path(type = "path_vector")

The geospatial data path is now set. Download PEPFAR VcPepfarPolygons.shp file from the above mentioned Google Drive to the newly set local folder.

Read geospatial data

Time to test some of the gisr functions. Let

# this works for the perfect setup with the default parameters values
spdf_pepfar <- get_vcpolygons(folderpath = geopath) 

# for custom use, you will need to specify the path and name of the file
spdf_pepfar <- get_vcpolygons(folderpath = "../myshapefiles", name = "pepfar.shp")

# Explore outputs
spdf_pepfar %>% glimpse()

spdf_pepfar

Now that the PEPFAR Boundaries shapefile can be accessed and read in R, how does one extract specific boundaries for their countries?

Extract country orgunit boundaries

In order to extract country specific boundaries, you will need to provide the country name and the orgunit level. Below is an example for South Africa.

cntry <- "South Africa"

Extract country boundaries

cntry_lvl <- grabr::get_ouorglevel(
  operatingunit = cntry,
  country = cntry,
  org_type = "country",
  username = datim_user(),
  password = datim_pwd()
)

# Country boundaries
spdf_cntry <- spdf_pepfar %>% 
  extract_boundaries(country = cntry, 
                     level = cntry_lvl,
                     username = datim_user(),
                     password = datim_pwd())

spdf_cntry

Extract PSNU boundaries

psnu_lvl <- grabr::get_ouorglevel(
  operatingunit = cntry,
  country = cntry,
  org_type = "prioritization",
  username = datim_user(),
  password = datim_pwd()
)

# psnu boundaries
spdf_psnu <- spdf_pepfar %>% 
  extract_boundaries(country = cntry, 
                     level = cntry_lvl,
                     username = datim_user(),
                     password = datim_pwd())

spdf_psnu

Extract all country boundaries


spdf_all <- cntry_polygons(spdf = spdf_pepfar, cntry = cntry)

spdf_all$country
spdf_all$snu1
spdf_all$prioritization
spdf_all$community

Download pre-parsed geodata

PEPFAR Geospatial dataset have already been parsed out and can be downloaded to a local directory.

# Download country boundaries
download_shapefiles(country = cntry, org_label = "country")

# Download PSNU boundaries
download_shapefiles(country = cntry, org_label = "prioritization")

Extract Data from other sources

Contextual geospatial data sets can also be extracted from external sources using get_admin0(), get_admin1(), get_adm_boundaries()

Export Geospatial Data to local drive

Take a look at spdf_export()

Baboyma Kagniniwa

2021-09-10