TY - JOUR
T1 - 3D Point Cloud Data in Conveying Information for Local Green Factor Assessment
AU - Jaalama, Kaisa
AU - Kauhanen, Heikki
AU - Keitaanniemi, Aino
AU - Rantanen, Toni
AU - Virtanen, Juho-Pekka
AU - Julin, Arttu
AU - Vaaja, Matti Tapio
AU - Ingman, Matias
AU - Ahlavuo, Marika
AU - Hyyppä, Hannu
PY - 2021/11/11
Y1 - 2021/11/11
N2 - 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.
AB - 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.
KW - point cloud
KW - green factor
KW - urban green infrastructure
KW - laser scanning
KW - photogrammetry
U2 - 10.3390/ijgi10110762
DO - 10.3390/ijgi10110762
M3 - Article
SN - 2220-9964
VL - 10
JO - ISPRS International Journal of Geo-Information
JF - ISPRS International Journal of Geo-Information
IS - 11
M1 - 762
ER -