Population_Access: scripts to model geographical accessibility of health services and compare coverage statistics of different gridded population datasets

First release of the code used to calculate accessibility to health services in sub-Saharan Africa, while evaluating the impact of using six different gridded population datasets. 

In this project we compared the difference in accessibility coverage estimates for six gridded population datasets: 1) WorldPop top-down constrained, 2) WorldPop top-down unconstrained, 3) HRSL, 4) GPWv4, 5) Landscan, and 6) Global Human Settlement Population (GHS-POP).

The R scripts are made to clip, project and prepare all input data for a geographic accessibility analysis. In addition it uses code to extract the most recent OpenStreetMap layers. The data preparation includes:

• Landcover: clipping and projection (R-script, 01_data_prep_landcover.R)
• Digital Elevation Model: data fetching, clipping, and projecting (R-script, 02_data_prep_dem_download.R & 02_data_prep_dem_process.R)
• Roads: data fetching and projecting (R-script, 03_data_prep_roads.R)
• Hydrography: data fetching of line and polygon features (R-script, 04_data_prep_hydro_lines.R & 05_data_prep_hydro_poly.R)
• Landcover merge: combining all input data in a merged land cover to which a travel scenario can be applied (R-script, 06_data_prep_merge_landcover.R)
• Friction layer: the transformation of a land cover merge to a friction layer that presents the cost of traversing a cell (R-script, 07_friction_layer.R)
• Health facility location: clipping point features to countries and projecting (R-script, 08_health_facilities.R)
• Accessibility analyis: cost-distance algorithm in arcpy that appliesa the eight directional least-cost path to the friction layer overlaid with health facility location (09_accessibility_analysis.py).
• Gridded population data: the fetching of some and preparation of several gridded population datasets (R-scripts, 10_download_population_worldpop.R & 11_clip_population.R)
• Accessibility coverage statistics: calculation of the population covered in several travel time catchments (i.e., 30, 60, 120, 150, and 180 minutes) (R-scripts, 13_extract_coverage_X.R)