3D Point Cloud Data in Conveying Information for Local Green Factor Assessment

The importance of ensuring the adequacy of urban ecosystem services and green infrastructure has been widely highlighted in multidisciplinary research. Meanwhile, the consolidation of cities has been a dominant trend in urban development and has led to the development and implementation of the green...

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Autores principales:	Kaisa Jaalama, Heikki Kauhanen, Aino Keitaanniemi, Toni Rantanen, Juho-Pekka Virtanen, Arttu Julin, Matti Vaaja, Matias Ingman, Marika Ahlavuo, Hannu Hyyppä
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	point cloud green factor urban green infrastructure laser scanning photogrammetry Geography (General) G1-922
Acceso en línea:	https://doaj.org/article/974368db25fe4023b98e48eb886d8032
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id	oai:doaj.org-article:974368db25fe4023b98e48eb886d8032
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spelling	oai:doaj.org-article:974368db25fe4023b98e48eb886d80322021-11-25T17:53:04Z3D Point Cloud Data in Conveying Information for Local Green Factor Assessment10.3390/ijgi101107622220-9964https://doaj.org/article/974368db25fe4023b98e48eb886d80322021-11-01T00:00:00Zhttps://www.mdpi.com/2220-9964/10/11/762https://doaj.org/toc/2220-9964The importance of ensuring the adequacy of urban ecosystem services and green infrastructure has been widely highlighted in multidisciplinary research. Meanwhile, the consolidation of cities has been a dominant trend in urban development and has led to the development and implementation of the green factor tool in cities such as Berlin, Melbourne, and Helsinki. In this study, elements of the green factor tool were monitored with laser-scanned and photogrammetrically derived point cloud datasets encompassing a yard in Espoo, Finland. The results show that with the support of 3D point clouds, it is possible to support the monitoring of the local green infrastructure, including elements of smaller size in green areas and yards. However, point clouds generated by distinct means have differing abilities in conveying information on green elements, and canopy covers, for example, might hinder these abilities. Additionally, some green factor elements are more promising for 3D measurement-based monitoring than others, such as those with clear geometrical form. The results encourage the involvement of 3D measuring technologies for monitoring local urban green infrastructure (UGI), also of small scale.Kaisa JaalamaHeikki KauhanenAino KeitaanniemiToni RantanenJuho-Pekka VirtanenArttu JulinMatti VaajaMatias IngmanMarika AhlavuoHannu HyyppäMDPI AGarticlepoint cloudgreen factorurban green infrastructurelaser scanningphotogrammetryGeography (General)G1-922ENISPRS International Journal of Geo-Information, Vol 10, Iss 762, p 762 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	point cloud green factor urban green infrastructure laser scanning photogrammetry Geography (General) G1-922
spellingShingle	point cloud green factor urban green infrastructure laser scanning photogrammetry Geography (General) G1-922 Kaisa Jaalama Heikki Kauhanen Aino Keitaanniemi Toni Rantanen Juho-Pekka Virtanen Arttu Julin Matti Vaaja Matias Ingman Marika Ahlavuo Hannu Hyyppä 3D Point Cloud Data in Conveying Information for Local Green Factor Assessment
description	The importance of ensuring the adequacy of urban ecosystem services and green infrastructure has been widely highlighted in multidisciplinary research. Meanwhile, the consolidation of cities has been a dominant trend in urban development and has led to the development and implementation of the green factor tool in cities such as Berlin, Melbourne, and Helsinki. In this study, elements of the green factor tool were monitored with laser-scanned and photogrammetrically derived point cloud datasets encompassing a yard in Espoo, Finland. The results show that with the support of 3D point clouds, it is possible to support the monitoring of the local green infrastructure, including elements of smaller size in green areas and yards. However, point clouds generated by distinct means have differing abilities in conveying information on green elements, and canopy covers, for example, might hinder these abilities. Additionally, some green factor elements are more promising for 3D measurement-based monitoring than others, such as those with clear geometrical form. The results encourage the involvement of 3D measuring technologies for monitoring local urban green infrastructure (UGI), also of small scale.
format	article
author	Kaisa Jaalama Heikki Kauhanen Aino Keitaanniemi Toni Rantanen Juho-Pekka Virtanen Arttu Julin Matti Vaaja Matias Ingman Marika Ahlavuo Hannu Hyyppä
author_facet	Kaisa Jaalama Heikki Kauhanen Aino Keitaanniemi Toni Rantanen Juho-Pekka Virtanen Arttu Julin Matti Vaaja Matias Ingman Marika Ahlavuo Hannu Hyyppä
author_sort	Kaisa Jaalama
title	3D Point Cloud Data in Conveying Information for Local Green Factor Assessment
title_short	3D Point Cloud Data in Conveying Information for Local Green Factor Assessment
title_full	3D Point Cloud Data in Conveying Information for Local Green Factor Assessment
title_fullStr	3D Point Cloud Data in Conveying Information for Local Green Factor Assessment
title_full_unstemmed	3D Point Cloud Data in Conveying Information for Local Green Factor Assessment
title_sort	3d point cloud data in conveying information for local green factor assessment
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/974368db25fe4023b98e48eb886d8032
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3D Point Cloud Data in Conveying Information for Local Green Factor Assessment

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