H
Harri Kaartinen
Researcher at University of Turku
Publications - 194
Citations - 9465
Harri Kaartinen is an academic researcher from University of Turku. The author has contributed to research in topics: Laser scanning & Point cloud. The author has an hindex of 50, co-authored 183 publications receiving 7843 citations. Previous affiliations of Harri Kaartinen include Academy of Finland & Helsinki University of Technology.
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Journal ArticleDOI
Fast Automatic Precision Tree Models from Terrestrial Laser Scanner Data
Pasi Raumonen,Mikko Kaasalainen,Markku Åkerblom,Sanna Kaasalainen,Harri Kaartinen,Mikko Vastaranta,Markus Holopainen,Mathias Disney,Philip Lewis +8 more
TL;DR: A new method for constructing quickly and automatically precision tree models from point clouds of the trunk and branches obtained by terrestrial laser scanning, validated using both measured and modeled terrestrial laser scanner data from real trees and detailed 3D models.
Journal ArticleDOI
Terrestrial laser scanning in forest inventories
Xinlian Liang,Xinlian Liang,Ville Kankare,Ville Kankare,Juha Hyyppä,Juha Hyyppä,Yunsheng Wang,Yunsheng Wang,Antero Kukko,Antero Kukko,Antero Kukko,Henrik Haggrén,Xiaowei Yu,Xiaowei Yu,Harri Kaartinen,Anttoni Jaakkola,Anttoni Jaakkola,Fengying Guan,Markus Holopainen,Markus Holopainen,Mikko Vastaranta,Mikko Vastaranta +21 more
TL;DR: In this article, the advances of applying terrestrial laser scanning (TLS) in forest inventories, discusses its properties with reference to other related techniques and discusses the future prospects of this technique.
Journal ArticleDOI
An International Comparison of Individual Tree Detection and Extraction Using Airborne Laser Scanning
Harri Kaartinen,Juha Hyyppä,Xiaowei Yu,Mikko Vastaranta,Hannu Hyyppä,Antero Kukko,Markus Holopainen,Christian Heipke,Manuela Hirschmugl,Felix Morsdorf,Erik Næsset,Juho Pitkänen,Sorin C. Popescu,Svein Solberg,Bernd-Michael Wolf,Jee-Cheng Wu +15 more
TL;DR: The accuracy of tree height, after removing gross errors, was better than 0.5 m in all tree height classes with the best methods investigated in this experiment, suggesting minimum curvature-based tree detection accompanied by point cloud-based cluster detection for suppressed trees is a solution that deserves attention in the future.
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A low-cost multi-sensoral mobile mapping system and its feasibility for tree measurements
TL;DR: A novel low-cost mini-UAV-based laser scanning system capable of not only recording point cloud data giving the geometry of the objects, but also simultaneously collecting image data, including overlapping images and the intensity of laser backscatter, as well as hyperspectral and thermal data is presented.
Journal ArticleDOI
Automatic detection of harvested trees and determination of forest growth using airborne laser scanning
TL;DR: In this paper, the applicability of small footprint, high sampling density airborne laser scanners for boreal forest change detection was demonstrated using a test site using a Toposys-1 laser scanner.