Dataset Open Access
Kruitwagen, Lucas;
Story, Kyle;
Friedrich, Johannes;
Byers, Logan;
Skillman, Sam;
Hepburn, Cameron
<?xml version='1.0' encoding='utf-8'?> <resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd"> <identifier identifierType="DOI">10.5281/zenodo.5005868</identifier> <creators> <creator> <creatorName>Kruitwagen, Lucas</creatorName> <givenName>Lucas</givenName> <familyName>Kruitwagen</familyName> <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0003-2663-395X</nameIdentifier> <affiliation>University of Oxford</affiliation> </creator> <creator> <creatorName>Story, Kyle</creatorName> <givenName>Kyle</givenName> <familyName>Story</familyName> <affiliation>Descartes Labs Inc</affiliation> </creator> <creator> <creatorName>Friedrich, Johannes</creatorName> <givenName>Johannes</givenName> <familyName>Friedrich</familyName> <affiliation>World Resources Institute</affiliation> </creator> <creator> <creatorName>Byers, Logan</creatorName> <givenName>Logan</givenName> <familyName>Byers</familyName> <affiliation>World Resources Institute</affiliation> </creator> <creator> <creatorName>Skillman, Sam</creatorName> <givenName>Sam</givenName> <familyName>Skillman</familyName> <affiliation>Descartes Labs Inc</affiliation> </creator> <creator> <creatorName>Hepburn, Cameron</creatorName> <givenName>Cameron</givenName> <familyName>Hepburn</familyName> <affiliation>University of Oxford</affiliation> </creator> </creators> <titles> <title>A global inventory of solar photovoltaic generating units - dataset</title> </titles> <publisher>Zenodo</publisher> <publicationYear>2021</publicationYear> <subjects> <subject>photovoltaic solar</subject> <subject>remote sensing</subject> <subject>geospatial data</subject> <subject>computer vision</subject> </subjects> <dates> <date dateType="Issued">2021-10-27</date> </dates> <language>en</language> <resourceType resourceTypeGeneral="Dataset"/> <alternateIdentifiers> <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/5005868</alternateIdentifier> </alternateIdentifiers> <relatedIdentifiers> <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.5005867</relatedIdentifier> </relatedIdentifiers> <version>1.0.0</version> <rightsList> <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights> <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights> </rightsList> <descriptions> <description descriptionType="Abstract"><p>This is the data repository accompanying Kruitwagen, L., Story, K., Friedrich, J., Byers, L., Skillman, S., &amp; Hepburn, C. (2021) A global inventory of photovoltaic solar generating units, <strong>Nature, </strong><em>forthcoming</em>. This repository contains the training, cross-validation, test, and predicted data set as described in the publication. The contents of this repository are briefly summarised here, see the publication for further details.</p> <p><strong>Repository contents:</strong></p> <p><em>trn_tiles.geojson:&nbsp;</em>18,570&nbsp;rectangular areas-of-interest used for sampling training patch data.</p> <p><em>trn_polygons.geojson:&nbsp;</em>36,882&nbsp;polygons obtained from OSM in 2017&nbsp;used to label training patches.</p> <p><em>cv_tiles.geojson:&nbsp;</em>560&nbsp;rectangular areas-of-interest used for sampling cross-validation data seeded from <a href="https://www.wri.org/research/global-database-power-plants">WRI GPPDB</a></p> <p><em>cv_polygons.geojson:&nbsp;</em>6,281 polygons corresponding to all PV solar generating units present in cv_tiles.geojson at the end of 2018.</p> <p><em>test_tiles.geojson:&nbsp;</em>122 rectangular regions-of-interest used for building the test set.</p> <p><em>test_polygons.geojson: </em>7,263 polygons corresponding to all utility-scale (&gt;10kW) solar generating units present in test_tiles.geojson at the end of 2018.</p> <p><em>predicted_polygons.geojson:&nbsp;</em>68,661 polygons corresponding to predicted polygons in global deployment, capturing the status of deployed photovoltaic solar energy generating capacity at the end of 2018.</p></description> </descriptions> </resource>
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