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Volume 10
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10.3390/ijgi10110762
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Article

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

by
Kaisa Jaalama
1,2,*,
Heikki Kauhanen
1,
Aino Keitaanniemi
1,
Toni Rantanen
1,
Juho-Pekka Virtanen
1,2,
Arttu Julin
1,
Matti Vaaja
1,
Matias Ingman
1,
Marika Ahlavuo
1 and
Hannu Hyyppä
1,2
1
Department of Built Environment, Aalto University, 02150 Espoo, Finland
2
Finnish Geospatial Research Institute FGI, 02430 Kirkkonummi, Finland
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2021, 10(11), 762; https://doi.org/10.3390/ijgi10110762
Submission received: 1 September 2021 / Revised: 29 October 2021 / Accepted: 6 November 2021 / Published: 11 November 2021
(This article belongs to the Special Issue Advancements in Geospatial Planning and Assessment of Green Infrastructure in Cities of the Future)
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Abstract

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.
Keywords: point cloud; green factor; urban green infrastructure; laser scanning; photogrammetry point cloud; green factor; urban green infrastructure; laser scanning; photogrammetry

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MDPI and ACS Style

Jaalama, K.; Kauhanen, H.; Keitaanniemi, A.; Rantanen, T.; Virtanen, J.-P.; Julin, A.; Vaaja, M.; Ingman, M.; Ahlavuo, M.; Hyyppä, H. 3D Point Cloud Data in Conveying Information for Local Green Factor Assessment. ISPRS Int. J. Geo-Inf. 2021, 10, 762. https://doi.org/10.3390/ijgi10110762

AMA Style

Jaalama K, Kauhanen H, Keitaanniemi A, Rantanen T, Virtanen J-P, Julin A, Vaaja M, Ingman M, Ahlavuo M, Hyyppä H. 3D Point Cloud Data in Conveying Information for Local Green Factor Assessment. ISPRS International Journal of Geo-Information. 2021; 10(11):762. https://doi.org/10.3390/ijgi10110762

Chicago/Turabian Style

Jaalama, Kaisa, Heikki Kauhanen, Aino Keitaanniemi, Toni Rantanen, Juho-Pekka Virtanen, Arttu Julin, Matti Vaaja, Matias Ingman, Marika Ahlavuo, and Hannu Hyyppä. 2021. "3D Point Cloud Data in Conveying Information for Local Green Factor Assessment" ISPRS International Journal of Geo-Information 10, no. 11: 762. https://doi.org/10.3390/ijgi10110762

APA Style

Jaalama, K., Kauhanen, H., Keitaanniemi, A., Rantanen, T., Virtanen, J.-P., Julin, A., Vaaja, M., Ingman, M., Ahlavuo, M., & Hyyppä, H. (2021). 3D Point Cloud Data in Conveying Information for Local Green Factor Assessment. ISPRS International Journal of Geo-Information, 10(11), 762. https://doi.org/10.3390/ijgi10110762

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