Skip to content

Instantly share code, notes, and snippets.

@d3netxer
Last active November 12, 2020 16:59
Show Gist options
  • Save d3netxer/7b117a2a784a8c8a9bac4bb6bf6d9e9b to your computer and use it in GitHub Desktop.
Save d3netxer/7b117a2a784a8c8a9bac4bb6bf6d9e9b to your computer and use it in GitHub Desktop.

Detailed Description of Layers

Functional Urban Areas (GHS-FUA 2015)

The GHS Functional Urban Areas (GHS-FUA) delineate the spatial entities representing the commuting area of the Urban Centres of 2015. (source: https://ghsl.jrc.ec.europa.eu/ghs_fua.php)

Urban Centers (WB calculation using GHS-POP 2015)

This dataset is processed using a GOST produced script and uses GHS-POP as the input (2015 epoch, 1km) (source: https://ghsl.jrc.ec.europa.eu/ghs_pop2019.php). The outputs are urban centres, which are defined by using the Degree of urbanization definition as contiguous grid cells with a density of at least 1,500 inhabitants per km2. An urban centre has population of at least 50,000. (https://ghsl.jrc.ec.europa.eu/degurbaDefinitions.php).

Urban built-up extents (WB Calculation using GHS-POP 2015)

This dataset is processed using a GOST produced script and uses GHS-POP as the input (2015 epoch, 1km) (source: https://ghsl.jrc.ec.europa.eu/ghs_pop2019.php). The outputs are urban clusters, which are defined by using the Degree of urbanization definition as contiguous grid cells with a density of at least 300 inhabitants per km2. An urban cluster has population of at least 5,000 (https://ghsl.jrc.ec.europa.eu/degurbaDefinitions.php).

Urban Centers (WB calculation using World-Pop 2020)

This dataset is processed using a GOST produced script and uses WorldPop as the input (2020 Unconstrained, 1km) (source: https://www.worldpop.org/geodata/summary?id=34627). The outputs are urban centres, which are defined by using the Degree of urbanization definition as contiguous grid cells with a density of at least 1,500 inhabitants per km2. An urban centre has population of at least 5,000 (https://ghsl.jrc.ec.europa.eu/degurbaDefinitions.php).

**GOST methodology: WorldPop is in the WGS84 projection, and grid cells in Uzbekistan are approximately .65 km2. Therefore, the density parameter was adjusted to at least 975 inhabitants per km2 to be comparable of the Degree of urbanization definition of contiguous grid cells needing a density of at least 1,500 inhabitants per km2.

Urban built-up extents (WB Calculation using World-Pop 2020)

This dataset is processed using a GOST produced script and uses WorldPop as the input (2020 Unconstrained, 1km) (source: https://www.worldpop.org/geodata/summary?id=34627). The outputs are urban clusters, which are defined by using the Degree of urbanization definition as contiguous grid cells with a density of at least 300 inhabitants per km2. An urban cluster has population of at least 5,000 (https://ghsl.jrc.ec.europa.eu/degurbaDefinitions.php).

**GOST methodology: WorldPop is in the WGS84 projection, and grid cells in Uzbekistan are approximately .65 km2. Therefore, the density parameter was adjusted to at least 195 inhabitants per km2 to be comparable of the Degree of urbanization definition of contiguous grid cells needing a density of at least 300 inhabitants per km2.

Urban built-up extents non-smooth (WB Calculation using World-Pop 2020)

This dataset is processed using a GOST produced script and uses WorldPop as the input (2020 Unconstrained, 1km) (source: https://www.worldpop.org/geodata/summary?id=34627). The outputs are urban clusters, which are defined by using the Degree of urbanization definition as contiguous grid cells with a density of at least 300 inhabitants per km2. An urban cluster has population of at least 5,000 (https://ghsl.jrc.ec.europa.eu/degurbaDefinitions.php).

**GOST methodology: WorldPop is in the WGS84 projection, and grid cells in Uzbekistan are approximately .65 km2. Therefore, the density parameter was adjusted to at least 195 inhabitants per km2 to be comparable of the Degree of urbanization definition of contiguous grid cells needing a density of at least 300 inhabitants per km2.

In addition this version is non-smoothed, and therefore gaps are not filled within the polygons.

1 hr Travel time extents from center points of large cities. (using OpenStreetMap)

This dataset is processed using a GOST produced script using a WorldPop population grid, OpenStreetmap network, and a dataset of city centers in UBZ. The output includes polygons that represent a driving time of 1 hour from the center of each city.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment