{"data":{"id":"10.4121/558f6150-a3e9-4960-82b2-cd2115c070d4","type":"dois","attributes":{"doi":"10.4121/558f6150-a3e9-4960-82b2-cd2115c070d4","prefix":"10.4121","suffix":"558f6150-a3e9-4960-82b2-cd2115c070d4","identifiers":[],"alternateIdentifiers":[],"creators":[{"name":"Teeuwen, Roos","nameType":"Personal","givenName":"Roos","familyName":"Teeuwen","nameIdentifiers":[{"nameIdentifier":"0000-0002-1886-0258","nameIdentifierScheme":"https://orcid.org/"}],"affiliation":[]},{"name":"Psyllidis, Achilleas","givenName":"Achilleas","familyName":"Psyllidis","affiliation":[],"nameIdentifiers":[]},{"name":"Milias, Vasileios","givenName":"Vasileios","familyName":"Milias","affiliation":[],"nameIdentifiers":[]},{"name":"Bozzon, A. (Alessandro)","nameType":"Personal","givenName":"A. (Alessandro)","familyName":"Bozzon","nameIdentifiers":[{"nameIdentifier":"0000-0002-3300-2913","nameIdentifierScheme":"https://orcid.org/"}],"affiliation":[]}],"titles":[{"title":"GreenspacePerception (Github) code repository: analysis underlying the publication \"How well do NDVI and OpenStreetMap data capture people’s visual perceptions of urban greenspace?\""}],"publisher":"4TU.ResearchData","container":{},"publicationYear":2024,"subjects":[{"subject":"Urban and Regional Planning","subjectScheme":"Australian and New Zealand Standard Research Classification (ANZSRC), 2008","classificationCode":"1205"},{"subject":"FOS: Social and economic geography","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Physical Geography and Environmental Geoscience","subjectScheme":"Australian and New Zealand Standard Research Classification (ANZSRC), 2008","classificationCode":"0406"},{"subject":"FOS: Earth and related environmental sciences","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Public Health (excl. Specific Population Health)","subjectScheme":"Australian and New Zealand Standard Research Classification (ANZSRC), 2008","classificationCode":"9204"},{"subject":"Earth Sciences","subjectScheme":"Australian and New Zealand Standard Research Classification (ANZSRC), 2008","classificationCode":"04"},{"subject":"Built Environment and Design","subjectScheme":"Australian and New Zealand Standard Research Classification (ANZSRC), 2008","classificationCode":"12"},{"subject":"Health","subjectScheme":"Australian and New Zealand Standard Research Classification (ANZSRC), 2008","classificationCode":"92"},{"subject":"Urban greenspace"},{"subject":"Visual perception"},{"subject":"OpenStreetMap"},{"subject":"NDVI"},{"subject":"Crowdsourcing"},{"subject":"Time: 2023"}],"contributors":[{"name":"TU Delft, Faculty Of Industrial Design Engineering, Department Of Human-Centred Artificial Intelligence","nameType":"Organizational","affiliation":[],"contributorType":"Other","nameIdentifiers":[]}],"dates":[{"date":"2024-04-15","dateType":"Issued"}],"language":"en","types":{"ris":"COMP","bibtex":"misc","citeproc":"article","schemaOrg":"SoftwareSourceCode","resourceType":"Software","resourceTypeGeneral":"Software"},"relatedIdentifiers":[{"relationType":"IsSupplementTo","relatedIdentifier":"10.1016/j.landurbplan.2024.105009","relatedIdentifierType":"DOI"},{"relationType":"References","relatedIdentifier":"https://github.com/rflteeuwen/GreenspacePerception/blob/main/README.md","relatedIdentifierType":"URL"}],"relatedItems":[],"sizes":[],"formats":["Jupyter Notebooks (.ipynb); Excel (.xlsx)"],"version":"2","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":"These notebooks allow to collect spatial data, specifically NDVI, OpenStreetMap and Google Street View metadata, and conduct the quantitative analysis to research how well NDVI and OpenStreetMap data capture what people visually perceive as being urban greenspaces. These notebooks were used in complementation by data collection through a crowdsourcing questionnaire to collect people's perceptions of places presented in Google Street View imagery. The quantitative analysis was followed up by a qualitative analysis, of which the codebook is added to this repository as well as an .xlsx file.This code was developed for three cities in Europe: Barcelona, Rotterdam, and Gothenburg, but can be adapted to fit other geographical contexts.","descriptionType":"Abstract"}],"geoLocations":[{"geoLocationPlace":"Barcelona; Rotterdam; Gothenburg"}],"fundingReferences":[{"awardTitle":"Early Environmental quality and life-course mental health effects","funderName":"European 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