Combining expert and crowd-sourced training data to map urban form and functions for the continental US

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dc.contributor.authorDemuzere, Matthiasen
dc.contributor.authorHankey, Steven C.en
dc.contributor.authorMills, Geralden
dc.contributor.authorZhang, Wenwenen
dc.contributor.authorLu, Tianjunen
dc.contributor.authorBechtel, Benjaminen
dc.contributor.departmentSchool of Public and International Affairsen
dc.date.accessioned2020-10-07T17:45:16Zen
dc.date.available2020-10-07T17:45:16Zen
dc.date.issued2020-08-11en
dc.description.abstractAlthough continental urban areas are relatively small, they are major drivers of environmental change at local, regional and global scales. Moreover, they are especially vulnerable to these changes owing to the concentration of population and their exposure to a range of hydro-meteorological hazards, emphasizing the need for spatially detailed information on urbanized landscapes. These data need to be consistent in content and scale and provide a holistic description of urban layouts to address different user needs. Here, we map the continental United States into Local Climate Zone (LCZ) types at a 100 m spatial resolution using expert and crowd-sourced information. There are 10 urban LCZ types, each associated with a set of relevant variables such that the map represents a valuable database of urban properties. These data are benchmarked against continental-wide existing and novel geographic databases on urban form. We anticipate the dataset provided here will be useful for researchers and practitioners to assess how the configuration, size, and shape of cities impact the important human and environmental outcomes.en
dc.description.notesThis work was conducted in the context of project ENLIGHT, funded by the German Research Foundation (DFG) under grant No. 437467569. We acknowledge all WUDAPT contributors for providing the training areas of the USA cities used in this study. We thank USGS and NASA for the free Landsat data, the Copernicus programme of ESA for the Sentinel data and the National Centers for Environmental Information at the National Oceanic and Atmospheric Administration (NOAA) for the DMSP-OLS data, all acquired via Google Earth Engine. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the sponsoring organizations. This publication was developed as part of the Center for Air, Climate and Energy Solutions (CACES), which was supported under Assistance Agreement No. R835873 awarded by the U.S. Environmental Protection Agency. It has not been formally reviewed by EPA. The views expressed in this document are solely those of authors and do not necessarily reflect those of the Agency. EPA does not endorse any products or commercial services mentioned in this publication. Moreover, we thank Jonas Kittner for help with Fig. 1. Open access funding provided by Projekt DEAL.en
dc.description.sponsorshipGerman Research Foundation (DFG)German Research Foundation (DFG) [437467569]; U.S. Environmental Protection AgencyUnited States Environmental Protection Agency [R835873]; Projekt DEALen
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1038/s41597-020-00605-zen
dc.identifier.eissn2052-4463en
dc.identifier.issue1en
dc.identifier.other264en
dc.identifier.pmid32782324en
dc.identifier.urihttp://hdl.handle.net/10919/100299en
dc.identifier.volume7en
dc.language.isoenen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.titleCombining expert and crowd-sourced training data to map urban form and functions for the continental USen
dc.title.serialScientific Dataen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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