{"data":{"id":"10.6084/m9.figshare.5307364","type":"dois","attributes":{"doi":"10.6084/m9.figshare.5307364","prefix":"10.6084","suffix":"m9.figshare.5307364","identifiers":[],"alternateIdentifiers":[],"creators":[{"name":"Bradbury, Kyle","nameType":"Personal","givenName":"Kyle","familyName":"Bradbury","affiliation":[],"nameIdentifiers":[{"schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-9847-0243","nameIdentifierScheme":"ORCID"}]},{"name":"Brigman, Benjamin","nameType":"Personal","givenName":"Benjamin","familyName":"Brigman","affiliation":[],"nameIdentifiers":[{"schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0001-7674-2439","nameIdentifierScheme":"ORCID"}]},{"name":"Gouttham Chandrasekar","affiliation":[],"nameIdentifiers":[]},{"name":"Collins, Leslie","nameType":"Personal","givenName":"Leslie","familyName":"Collins","affiliation":[],"nameIdentifiers":[]},{"name":"Shamikh Hossain","affiliation":[],"nameIdentifiers":[]},{"name":"Jeuland, Marc","nameType":"Personal","givenName":"Marc","familyName":"Jeuland","affiliation":[],"nameIdentifiers":[]},{"name":"Johnson, Timothy","nameType":"Personal","givenName":"Timothy","familyName":"Johnson","affiliation":[],"nameIdentifiers":[]},{"name":"Boning Li","affiliation":[],"nameIdentifiers":[]},{"name":"Trishul Nagenalli","affiliation":[],"nameIdentifiers":[]}],"titles":[{"title":"Power Plant Satellite Imagery Dataset"}],"publisher":"figshare","container":{},"publicationYear":2017,"subjects":[{"subject":"91305 Energy Generation, Conversion and Storage Engineering","subjectScheme":"FOR"},{"subject":"FOS: Mechanical engineering","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Mechanical engineering","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"90608 Renewable Power and Energy Systems Engineering (excl. Solar Cells)","subjectScheme":"FOR"},{"subject":"FOS: Electrical engineering, electronic engineering, information engineering","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Electrical engineering, electronic engineering, information engineering","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"90607 Power and Energy Systems Engineering (excl. Renewable Power)","subjectScheme":"FOR"},{"subject":"170203 Knowledge Representation and Machine Learning","subjectScheme":"FOR"},{"subject":"FOS: Psychology","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Psychology","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"90905 Photogrammetry and Remote Sensing","subjectScheme":"FOR"},{"subject":"FOS: Environmental engineering","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Environmental engineering","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"80104 Computer Vision","subjectScheme":"FOR"},{"subject":"FOS: Computer and information sciences","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Computer and information sciences","subjectScheme":"Fields of Science and Technology (FOS)"}],"contributors":[],"dates":[{"date":"2017-08-14","dateType":"Created"},{"date":"2017-08-16","dateType":"Updated"},{"date":"2017","dateType":"Issued"}],"language":null,"types":{"ris":"DATA","bibtex":"misc","citeproc":"dataset","schemaOrg":"Dataset","resourceType":"Dataset","resourceTypeGeneral":"Dataset"},"relatedIdentifiers":[],"relatedItems":[],"sizes":["20128627891 Bytes"],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"This dataset contains satellite imagery of 4,454 power plants within the United States. The imagery is provided at two resolutions: 1m (4-band NAIP iamgery with near-infrared) and 30m (Landsat 8, pansharpened to 15m). The NAIP imagery is available for the U.S. and Landsat 8 is available globally. This dataset may be of value for computer vision work, machine learning, as well as energy and environmental analyses.\u003cbr\u003eAdditionally, annotations of the specific locations of the spatial extent of the power plants in each image is provided. These annotations were collected via the crowdsourcing platform, Amazon Mechanical Turk, using multiple annotators for each image to ensure quality. Links to the sources of the imagery data, the annotation tool, and the team that created the dataset are included in the \"References\" section.\u003cbr\u003eTo read more on these data, please refer to the \"Power Plant Satellite Imagery Dataset Overview.pdf\" file. To download a sample of the data without downloading the entire dataset, download \"sample.zip\" which includes two sample powerplants and the NAIP, Landsat 8, and binary annotations for each.\u003cbr\u003e\u003cbr\u003eNote: the NAIP imagery may appear \"washed out\" when viewed in standard image viewing software because it includes a near-infrared band in addition to the standard RGB data.\u003cbr\u003e\u003cbr\u003e\u003cbr\u003e","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"xml":"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