Travel time to cities and ports in the year 2015
travel_time_to_cities_x.tif (x has values from 1 to 12)
The value of each pixel is the estimated travel time in minutes to the nearest urban area in 2015. There are 12 data layers based on different sets of urban areas, defined by their population in year 2015 (see PDF report).
travel_time_to_ports_x (x ranges from 1 to 5)
The value of each pixel is the estimated travel time to the nearest port in 2015. There are 5 data layers based on different port sizes.
Raster Dataset, GeoTIFF, LZW compressed
Byte (16 bit Unsigned Integer)
No data value
30 arc seconds
Upper left -180, 85
Lower left -180, -60
Upper right 180, 85
Lower right 180, -60
Spatial Reference System (SRS)
EPSG:4326 - WGS84 - Geographic Coordinate System (lat/long)
Updates may follow for future years, but these are dependent on the availability of updated inputs on travel times and city locations and populations.
Travel time to the nearest city or port was estimated using an accumulated cost function (accCost) in the gdistance R package (van Etten, 2018). This function requires two input datasets: (i) a set of locations to estimate travel time to and (ii) a transition matrix that represents the cost or time to travel across a surface.
The set of locations were based on populated urban areas in the 2016 version of the Joint Research Centre’s Global Human Settlement Layers (GHSL) datasets (Pesaresi and Freire, 2016) that represent low density (LDC) urban clusters and high density (HDC) urban areas (https://ghsl.jrc.ec.europa.eu/datasets.php). These urban areas were represented by points, spaced at 1km distance around the perimeter of each urban area.
Marine ports were extracted from the 26th edition of the World Port Index (NGA, 2017) which contains the location and physical characteristics of approximately 3,700 major ports and terminals. Ports are represented as single points
The transition matrix was based on the friction surface (https://map.ox.ac.uk/research-project/accessibility_to_cities) from the 2015 global accessibility map (Weiss et al, 2018).
The R code used to generate the 12 travel time maps is included in the report “A suite of global accessibility indicators for sustainable rural development” (Nelson, 2019) that can be downloaded with these data layers.