Exploring methods for developing local climate zones to support climate research

Meteorological and climate prediction models at the urban scale increasingly require more accurate and high-resolution data. The Local Climate Zone (LCZ) system is an initiative to standardize a classification scheme of the urban landscape, based mainly on the properties of surface structure (e.g.,...

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Autores: Sigler Leibowitz, Laurence|||0000-0002-6334-077X, Gilabert, Joan, Villalba Mendez, Gara
Tipo de recurso: artículo
Fecha de publicación:2022
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/378457
Acceso en línea:https://hdl.handle.net/2117/378457
https://dx.doi.org/10.3390/cli10070109
Access Level:acceso abierto
Palabra clave:Urban climatology
Local Climate Zones (LCZs)
climatology
geographical information systems (GISs)
land surface temperature (LST)
World Urban Database and Access Portal Tools (WUDAPT)
Google Earth Engine (GEE)
Urban land use
Climatologia urbana
Àrees temàtiques de la UPC::Enginyeria civil::Geologia
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spelling Exploring methods for developing local climate zones to support climate researchSigler Leibowitz, Laurence|||0000-0002-6334-077XGilabert, JoanVillalba Mendez, GaraUrban climatologyLocal Climate Zones (LCZs)climatologygeographical information systems (GISs)land surface temperature (LST)World Urban Database and Access Portal Tools (WUDAPT)Google Earth Engine (GEE)Urban land useClimatologia urbanaÀrees temàtiques de la UPC::Enginyeria civil::GeologiaMeteorological and climate prediction models at the urban scale increasingly require more accurate and high-resolution data. The Local Climate Zone (LCZ) system is an initiative to standardize a classification scheme of the urban landscape, based mainly on the properties of surface structure (e.g., building, tree height, density) and surface cover (pervious vs. impervious). This approach is especially useful for studying the influence of urban morphology and fabric on the surface urban heat island (SUHI) effect and to evaluate how changes in land use and structures affect thermal regulation in the city. This article will demonstrate three different methodologies of creating LCZs: first, the World Urban Database and Access Portal Tools (WUDAPT); second, using Copernicus Urban Atlas (UA) data via a geographic information system (GIS) client directly; and third via Google Earth Engine (GEE) using Oslo, Norway as the case study. The WUDAPT and GEE methods incorporate a machine learning (random forest) procedure using Landsat 8 imagery, and offer the most precision while requiring the most time and familiarity with GIS usage and satellite imagery processing. The WUDAPT method is performed principally using multiple GIS clients and image processing tools. The GEE method is somewhat quicker to perform, with work performed entirely on Google’s sites. The UA or GIS method is performed solely via a GIS client and is a conversion of pre-existing vector data to LCZ classes via scripting. This is the quickest method of the three; however, the reclassification of the vector data determines the accuracy of the LCZs produced. Finally, as an illustration of a practical use of LCZs and to further compare the results of the three methods, we map the distribution of the temperature according to the LCZs of each method, correlating to the land surface temperature (LST) from a Landsat 8 image pertaining to a heat wave episode that occurred in Oslo in 2018. These results show, in addition to a clear LCZ-LST correspondence, that the three methods produce accurate and similar results and are all viable options.20222022-07-0120222022-12-16journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/378457https://dx.doi.org/10.3390/cli10070109reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/3784572026-05-27T15:37:01Z
dc.title.none.fl_str_mv Exploring methods for developing local climate zones to support climate research
title Exploring methods for developing local climate zones to support climate research
spellingShingle Exploring methods for developing local climate zones to support climate research
Sigler Leibowitz, Laurence|||0000-0002-6334-077X
Urban climatology
Local Climate Zones (LCZs)
climatology
geographical information systems (GISs)
land surface temperature (LST)
World Urban Database and Access Portal Tools (WUDAPT)
Google Earth Engine (GEE)
Urban land use
Climatologia urbana
Àrees temàtiques de la UPC::Enginyeria civil::Geologia
title_short Exploring methods for developing local climate zones to support climate research
title_full Exploring methods for developing local climate zones to support climate research
title_fullStr Exploring methods for developing local climate zones to support climate research
title_full_unstemmed Exploring methods for developing local climate zones to support climate research
title_sort Exploring methods for developing local climate zones to support climate research
dc.creator.none.fl_str_mv Sigler Leibowitz, Laurence|||0000-0002-6334-077X
Gilabert, Joan
Villalba Mendez, Gara
author Sigler Leibowitz, Laurence|||0000-0002-6334-077X
author_facet Sigler Leibowitz, Laurence|||0000-0002-6334-077X
Gilabert, Joan
Villalba Mendez, Gara
author_role author
author2 Gilabert, Joan
Villalba Mendez, Gara
author2_role author
author
dc.subject.none.fl_str_mv Urban climatology
Local Climate Zones (LCZs)
climatology
geographical information systems (GISs)
land surface temperature (LST)
World Urban Database and Access Portal Tools (WUDAPT)
Google Earth Engine (GEE)
Urban land use
Climatologia urbana
Àrees temàtiques de la UPC::Enginyeria civil::Geologia
topic Urban climatology
Local Climate Zones (LCZs)
climatology
geographical information systems (GISs)
land surface temperature (LST)
World Urban Database and Access Portal Tools (WUDAPT)
Google Earth Engine (GEE)
Urban land use
Climatologia urbana
Àrees temàtiques de la UPC::Enginyeria civil::Geologia
description Meteorological and climate prediction models at the urban scale increasingly require more accurate and high-resolution data. The Local Climate Zone (LCZ) system is an initiative to standardize a classification scheme of the urban landscape, based mainly on the properties of surface structure (e.g., building, tree height, density) and surface cover (pervious vs. impervious). This approach is especially useful for studying the influence of urban morphology and fabric on the surface urban heat island (SUHI) effect and to evaluate how changes in land use and structures affect thermal regulation in the city. This article will demonstrate three different methodologies of creating LCZs: first, the World Urban Database and Access Portal Tools (WUDAPT); second, using Copernicus Urban Atlas (UA) data via a geographic information system (GIS) client directly; and third via Google Earth Engine (GEE) using Oslo, Norway as the case study. The WUDAPT and GEE methods incorporate a machine learning (random forest) procedure using Landsat 8 imagery, and offer the most precision while requiring the most time and familiarity with GIS usage and satellite imagery processing. The WUDAPT method is performed principally using multiple GIS clients and image processing tools. The GEE method is somewhat quicker to perform, with work performed entirely on Google’s sites. The UA or GIS method is performed solely via a GIS client and is a conversion of pre-existing vector data to LCZ classes via scripting. This is the quickest method of the three; however, the reclassification of the vector data determines the accuracy of the LCZs produced. Finally, as an illustration of a practical use of LCZs and to further compare the results of the three methods, we map the distribution of the temperature according to the LCZs of each method, correlating to the land surface temperature (LST) from a Landsat 8 image pertaining to a heat wave episode that occurred in Oslo in 2018. These results show, in addition to a clear LCZ-LST correspondence, that the three methods produce accurate and similar results and are all viable options.
publishDate 2022
dc.date.none.fl_str_mv 2022
2022-07-01
2022
2022-12-16
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/378457
https://dx.doi.org/10.3390/cli10070109
url https://hdl.handle.net/2117/378457
https://dx.doi.org/10.3390/cli10070109
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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