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Local climate zones classification method from Copernicus land monitoring service datasets: An ArcGIS-based toolbox

Local Climate Zones (LCZ) have become a worldwide standard for identifying land cover classes, according to their climate-relevant morphological parameters. The LCZ's are mostly used to evaluate urban climate performance, particularly the relationship between the urban heat island effect (UHI)...

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Autores principales: Oliveira, Ana, Lopes, António, Niza, Samuel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7718173/
https://www.ncbi.nlm.nih.gov/pubmed/33304834
http://dx.doi.org/10.1016/j.mex.2020.101150
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author Oliveira, Ana
Lopes, António
Niza, Samuel
author_facet Oliveira, Ana
Lopes, António
Niza, Samuel
author_sort Oliveira, Ana
collection PubMed
description Local Climate Zones (LCZ) have become a worldwide standard for identifying land cover classes, according to their climate-relevant morphological parameters. The LCZ's are mostly used to evaluate urban climate performance, particularly the relationship between the urban heat island effect (UHI) and the characteristics of the built-up environment. The World Urban Database and Access Portal Tools (WUDAPT) has provided a supervised LCZ classification method based only on moderate resolution free satellite imagery, mostly Landsat 7 or 8 (30 m pixel size, in the visible spectrum brands); however, its’ results are less accurate for European cities. Conversely, alternative geographic information system (GIS)-based methods developed so far require information that is hardly available to all, such as building footprints or heights. Here, the ArcGIS based LCZ from Copernicus Toolbox (LCZC) provides an alternative classification method that uses only freely accessible information from the Copernicus Land Monitoring Service (CLMS), being possible to replicate it in 800 European urban locations. The method combines Urban Atlas (UA) and Corine Land Cover (CLC) with Tree Cover Density, Dominant Leaf Type and Grassland information, to produce a higher-resolution baseline shapefile that is classified according to each feature's dominant characteristics. The LCZC toolbox output is a LCZ raster map. It has been validated in five European cities: Athens, Barcelona, Lisbon, Marseille, and Naples. • The LCZC toolbox provides an alternative LCZ GIS-based classification, based on freely accessible CLMS datasets. • The use of CLMS shapefile higher-resolution inputs, particularly the UA and CLC datasets, ensures an output LCZ map that has greater detail and higher accuracy. • The availability of CLMS information in 800 European urban areas guarantees that the method can be replicated in those locations.
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spelling pubmed-77181732020-12-09 Local climate zones classification method from Copernicus land monitoring service datasets: An ArcGIS-based toolbox Oliveira, Ana Lopes, António Niza, Samuel MethodsX Method Article Local Climate Zones (LCZ) have become a worldwide standard for identifying land cover classes, according to their climate-relevant morphological parameters. The LCZ's are mostly used to evaluate urban climate performance, particularly the relationship between the urban heat island effect (UHI) and the characteristics of the built-up environment. The World Urban Database and Access Portal Tools (WUDAPT) has provided a supervised LCZ classification method based only on moderate resolution free satellite imagery, mostly Landsat 7 or 8 (30 m pixel size, in the visible spectrum brands); however, its’ results are less accurate for European cities. Conversely, alternative geographic information system (GIS)-based methods developed so far require information that is hardly available to all, such as building footprints or heights. Here, the ArcGIS based LCZ from Copernicus Toolbox (LCZC) provides an alternative classification method that uses only freely accessible information from the Copernicus Land Monitoring Service (CLMS), being possible to replicate it in 800 European urban locations. The method combines Urban Atlas (UA) and Corine Land Cover (CLC) with Tree Cover Density, Dominant Leaf Type and Grassland information, to produce a higher-resolution baseline shapefile that is classified according to each feature's dominant characteristics. The LCZC toolbox output is a LCZ raster map. It has been validated in five European cities: Athens, Barcelona, Lisbon, Marseille, and Naples. • The LCZC toolbox provides an alternative LCZ GIS-based classification, based on freely accessible CLMS datasets. • The use of CLMS shapefile higher-resolution inputs, particularly the UA and CLC datasets, ensures an output LCZ map that has greater detail and higher accuracy. • The availability of CLMS information in 800 European urban areas guarantees that the method can be replicated in those locations. Elsevier 2020-11-19 /pmc/articles/PMC7718173/ /pubmed/33304834 http://dx.doi.org/10.1016/j.mex.2020.101150 Text en © 2020 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Method Article
Oliveira, Ana
Lopes, António
Niza, Samuel
Local climate zones classification method from Copernicus land monitoring service datasets: An ArcGIS-based toolbox
title Local climate zones classification method from Copernicus land monitoring service datasets: An ArcGIS-based toolbox
title_full Local climate zones classification method from Copernicus land monitoring service datasets: An ArcGIS-based toolbox
title_fullStr Local climate zones classification method from Copernicus land monitoring service datasets: An ArcGIS-based toolbox
title_full_unstemmed Local climate zones classification method from Copernicus land monitoring service datasets: An ArcGIS-based toolbox
title_short Local climate zones classification method from Copernicus land monitoring service datasets: An ArcGIS-based toolbox
title_sort local climate zones classification method from copernicus land monitoring service datasets: an arcgis-based toolbox
topic Method Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7718173/
https://www.ncbi.nlm.nih.gov/pubmed/33304834
http://dx.doi.org/10.1016/j.mex.2020.101150
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