@prefix ocrer: <http://purl.org/net/OCRe/research.owl#> .
@prefix owl:   <http://www.w3.org/2002/07/owl#> .
@prefix scires: <http://vivoweb.org/ontology/scientific-research#> .
@prefix xsd:   <http://www.w3.org/2001/XMLSchema#> .
@prefix skos:  <http://www.w3.org/2004/02/skos/core#> .
@prefix rdfs:  <http://www.w3.org/2000/01/rdf-schema#> .
@prefix ocresd: <http://purl.org/net/OCRe/study_design.owl#> .
@prefix swo:   <http://www.ebi.ac.uk/efo/swo/> .
@prefix cito:  <http://purl.org/spar/cito/> .
@prefix geo:   <http://aims.fao.org/aos/geopolitical.owl#> .
@prefix ocresst: <http://purl.org/net/OCRe/statistics.owl#> .
@prefix dcterms: <http://purl.org/dc/terms/> .
@prefix vivo:  <http://vivoweb.org/ontology/core#> .
@prefix event: <http://purl.org/NET/c4dm/event.owl#> .
@prefix vann:  <http://purl.org/vocab/vann/> .
@prefix foaf:  <http://xmlns.com/foaf/0.1/> .
@prefix c4o:   <http://purl.org/spar/c4o/> .
@prefix fabio: <http://purl.org/spar/fabio/> .
@prefix vcard: <http://www.w3.org/2006/vcard/ns#> .
@prefix thkoeln: <http://cris.nrw/hisinone#> .
@prefix vitro: <http://vitro.mannlib.cornell.edu/ns/vitro/0.7#> .
@prefix vitro-public: <http://vitro.mannlib.cornell.edu/ns/vitro/public#> .
@prefix rdf:   <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
@prefix ocresp: <http://purl.org/net/OCRe/study_protocol.owl#> .
@prefix bibo:  <http://purl.org/ontology/bibo/> .
@prefix obo:   <http://purl.obolibrary.org/obo/> .
@prefix ro:    <http://purl.obolibrary.org/obo/ro.owl#> .

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        rdfs:label  "Journal Article"@en-US , "Journalartikel"@de-DE .

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        a                         thkoeln:Journalartikel , obo:BFO_0000002 , bibo:Document , obo:IAO_0000030 , owl:Thing , foaf:Document , thkoeln:Publikation , obo:BFO_0000031 , thkoeln:Artikel , obo:BFO_0000001 ;
        rdfs:label                "Hotspots in Urban Aareas" , "RDF description of Hotspots in Urban Aareas - https://fis.th-koeln.de/vivo/individual/publ_21467" ;
        thkoeln:artikelnummer     "102814" ;
        thkoeln:dokumententyp     "Wissenschaftlicher Artikel" ;
        thkoeln:peerReviewed      "true" ;
        thkoeln:sprache           "englisch" ;
        thkoeln:status            "validiert" ;
        thkoeln:subtitle          "A Novel Approach to Assess the Heat Mitigation Potential of Nature-based Solutions Using Microclimate Modelling" ;
        <http://cris.nrw/hisinone/hatForschungsfeld>
                <https://fis.th-koeln.de/vivo/individual/FF_001> ;
        <http://cris.nrw/hisinone/hatOrganisationseinheit>
                <https://fis.th-koeln.de/vivo/individual/11000450> ;
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                <http://cris.nrw/hisinone/RessourceText> ;
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                <https://fis.th-koeln.de/vivo/individual/cite_21467-0> , <https://fis.th-koeln.de/vivo/individual/cite_21467-2> , <https://fis.th-koeln.de/vivo/individual/cite_21467-1> ;
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                <http://cris.nrw/hisinone/OpenAccess> ;
        <http://purl.org/dc/elements/1.1/date>
                "2026-05-23T18:06:48"^^xsd:dateTime ;
        <http://purl.org/dc/elements/1.1/publisher>
                <https://fis.th-koeln.de/vivo> ;
        <http://purl.org/dc/elements/1.1/rights>
                <https://fis.th-koeln.de/vivo/termsOfUse> ;
        bibo:abstract             "The urban heat island (UHI) effect requires measures to reduce heat stress and the associated health impacts. Nature-based solutions (NbS) are proposed to improve microclimatic conditions. Previous research has mostly assessed the potential for the use of NbS based on heat load maps for entire cities, with the most heat-stressed areas having the highest cooling demand. However, the extent to which NbS have a small-scale impact within urban districts has hardly been investigated to date. To close this gap, we developed a mixed-method approach combining spatial investigations and microclimate modelling in a neighborhood in Cologne, Germany. Based on remote sensing data, cadastral data and field measurements, we delineated potential “urban hot spots” (UHS) and carried out GIS analyses to identify the areas with the greatest need for NbS due to cooling deficits. For these areas, we implemented different NbS in a “hotspot scenario” simulated with the physically based 3D microclimate model ENVI-met during a 20-year heat event in 2022. The model was previously validated based on a quality-controlled, densely distributed meteorological sensor network. Compared to the reference run, the scenario analyses showed statistically significant differences in air temperature of −0.5 K in the spatio-temporal average for the entire study area during the heat event and up to −5.3 K on average for locations within the UHS. Physiological equivalent temperature (PET) can be reduced by −0.9 K on a spatio-temporal average for the entire study area and up to −7.7 K within the UHS. This highlights the potential of identifying UHS for urban heat mitigation." ;
        bibo:doi                  "10.1016/j.uclim.2026.102814" ;
        bibo:volume               "65" ;
        vitro:mostSpecificType    thkoeln:Journalartikel ;
        vivo:dateTimeValue        <http://cris.nrw/date2026> ;
        vivo:freetextKeyword      "Urban heat island (UHI)" , "Climate change adaptation" , "Climate extremes" , "Urban hot spots (UHS)" , "Nature-based solutions (NbS)" , "Microclimatic modelling" ;
        vivo:hasPublicationVenue  <https://fis.th-koeln.de/vivo/individual/journal_10154> ;
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        rdfs:label                "Urban Climate" ;
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        rdfs:label  "Institute for Natural Resources Technology and Management" ;
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