Data concerning mobility, urban infrastructure, urban services, urban  environment, and urban heat.

cities

Cities

Data related to human mobility patterns, transportation systems and infrastructure, and  vehicle electrification.

mobility

Mobility

### Overview  
  
Accessibility to cities quantifies the time it takes to travel to the nearest urban center via surface transport as of 2015. The dataset uses data on roads, railways, rivers, water bodies, and foot travel on different land cover types. It also includes information on topographical conditions (slope angle and elevation) and additional time for crossing national borders. The dataset was sourced from a variety of resources that each specialize in a specific mode of land transportation.

  
  
The data was created with the goal of understanding how travel time varies for different urban centers. Urban centers typically have higher concentrations of important resources and infrastructure than rural regions. Improving accessibility to these resources is integral to improving equality around the world. 

  
  
The dataset was created by the Malaria Atlas Project (MAP) with travel time in minutes at a 30 arc second spatial resolution (approximately 1 km at the equator).  
  
### Methodology  
  
Researchers first created a model that calculated the travel time for each pixel (1 km²) on earth. It was based on travel time information on roads, railways, and bodies of water. Additionally, information on land cover types, topographic conditions (slope and elevation), and national borders were included, as they usually affect travel time.  An algorithm was then applied to the model to determine the fastest travel times between destinationsThe road and railway datasets were created by merging Open Street Map (OSM) data with a distance-to-roads product derived from the Google roads database from November 2016 and March 2016. Data on river travel was taken from CIA World Data Bank II vector rivers dataset, lake travel from global surface-water occurrence dataset, and ocean travel from the automatic Identification System (AIS) and Voluntary Observing Ship (VOS) program. Undeveloped land was given a baseline speed of movement (by foot) using the MODIS MCD12Q1 land cover product. The final data was adjusted to account for topographical properties using Global Multi-resolution Terrain Elevation Dataset 2010 (GMTED2010) and a one hour travel penalty was added for any border crossing.

  
  
An urban center is defined as a contiguous area with 1,500 or more inhabitants per km² or a majority of built-up land cover coincident with a population center of at least 50,000 inhabitants. Cities were identified using the above assumption based on the Global Human Settlement Grid of High-Density Land Cover (GHS-HDC) data set and country borders were taken from the UN Global Administrative Units Layer (GAUL). Because cities are typically clusters of many cells rather than individual points, they are effectively treated as polygons when calculating travel time from a given point. The accessibility surface map was generated using the cumulative cost function within Google Earth Engine. The map was validated by testing its travel time calculations between 53,091 points compared to travel time estimates calculated by Google Maps. 

  
  
The final accessibility map was presented in raster format with a spatial resolution of 30 arc seconds (around 1 km at the equator). For the full documentation, please see the source [methodology](https://www.nature.com/articles/nature25181).  
  
### Additional Information  
  
Resource Watch shows only a subset of the dataset. For access to the full dataset and additional information, click on the “Learn more” button.  
  
### Visualizing the Data  
  
Our team reformatted this dataset before displaying it on Resource Watch.  
  
### Disclaimer  
  
Excerpts of this description page were taken from the source metadata.

Water, Peace & Security

Accessibility to Cities

2015 Accessibility to Cities