August 15, 2019 Dataset Open Access

Arderne, Christopher; NIcolas, Claire; Zorn, Conrad; Koks, Elco E.

Dublin Core Export

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<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:creator>Arderne, Christopher</dc:creator>
  <dc:creator>NIcolas, Claire</dc:creator>
  <dc:creator>Zorn, Conrad</dc:creator>
  <dc:creator>Koks, Elco E.</dc:creator>
  <dc:date>2019-08-15</dc:date>
  <dc:description>Four primary global data outputs from the research:


	hv.gpkg: Dump of OpenStreetMap grid data, slightly cleaned and tagged. (C) OpenStreetMap contributors.
	targets.tif: Binary aster showing locations predicted to be connected to distribution grid.
	mv.gpkg: Vectorized predicted distribution line network.
	lv.tif: Raster of predicted low-voltage infrastructure in kilometres per cell.


This data was created with code in the following three repositories:


	https://github.com/carderne/gridfinder
	https://github.com/carderne/energy-infra
	https://github.com/carderne/accessestimator


Full steps to reproduce are contained in this file:


	https://github.com/carderne/energy-infra/blob/master/README.md


The data can be visualized at the following location:


	https://gridfinder.org
</dc:description>
  <dc:identifier>https://zenodo.org/record/3369107</dc:identifier>
  <dc:identifier>10.5281/zenodo.3369107</dc:identifier>
  <dc:identifier>oai:zenodo.org:3369107</dc:identifier>
  <dc:relation>doi:10.5281/zenodo.3369106</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>http://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:subject>electricity</dc:subject>
  <dc:subject>infrastructure</dc:subject>
  <dc:subject>power</dc:subject>
  <dc:title>Data from: Predictive mapping of the global power system using open data</dc:title>
  <dc:type>info:eu-repo/semantics/other</dc:type>
  <dc:type>dataset</dc:type>
</oai_dc:dc>