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Estimation of Tree Stem Attributes using Terrestrial Photogrammetry with a Camera Rig
Department of Forest Resource Management, Swedish University of Agricultural Sciences, 90183 Umeå, Sweden.
Umeå University, Faculty of Science and Technology, Department of Computing Science.ORCID iD: 0000-0002-7657-6917
Department of Forest Resource Management, Swedish University of Agricultural Sciences, 90183 Umeå, Sweden.
2016 (English)In: Forests, ISSN 1999-4907, E-ISSN 1999-4907, Vol. 7, no 3, 61Article in journal (Refereed) Published
Abstract [en]

We propose a novel photogrammetric method for field plot inventory, designed for simplicity and time efficiency on-site. A prototype multi-camera rig was used to acquire images from field plot centers in multiple directions. The acquisition time on-site was less than two minutes. From each view, a point cloud was generated using a novel, rig-based matching of detected SIFT keypoints. Stems were detected in the merged point cloud, and their positions and diameters were estimated. The method was evaluated on 25 hemi-boreal forest plots of a 10-m radius. Due to difficult lighting conditions and faulty hardware, imagery from only six field plots was processed. The method performed best on three plots with clearly visible stems with a 76% detection rate and 0% commission. Dieameters could be estimated for 40% of the stems with an RMSE of 2.8-9.5 cm. The results are comparable to other camera-based methods evaluated in a similar manner. The results are inferior to TLS-based methods. However, our method is easily extended to multiple station image schemas, something that could significantly improve the results while retaining low commission errors and time on-site. Furthermore, with smaller hardware, we believe this could be a useful technique for measuring stem attributes in the forest.

Place, publisher, year, edition, pages
Basel, Switzerland: MDPI (Multidisciplinary Digital Publishing Institute) , 2016. Vol. 7, no 3, 61
Keyword [en]
forest inventory, point cloud, circle estimation, mobile mapping, stem diameter
National Category
Forest Science Computer and Information Science Computer Vision and Robotics (Autonomous Systems)
Research subject
Computer and Information Science; Computerized Image Analysis
Identifiers
URN: urn:nbn:se:umu:diva-117957DOI: 10.3390/f7030061ISI: 000373700800021OAI: oai:DiVA.org:umu-117957DiVA: diva2:910096
Funder
The Kempe Foundations, SMK-1033
Available from: 2016-03-08 Created: 2016-03-08 Last updated: 2017-11-30Bibliographically approved

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Forsman, MonaBörlin, Niclas
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