College of Forestry
Segmentation
Tree and sub-tree segmentation algorithms
Background
Technological advancements allows forest inventory using individual trees as measurement units. However, the errors associated with ground delineation, tree identification, or estimation of height to the base of the crown hinder the widespread application of spatial explicit tree-level forest inventories.
Objective
The projects are focused on individual tree segmentation or identification and measurement of parts of the tree, such as branches, knots, or leaves, use as input point clouds obtained from airborn sensors, terrestrial scanning, or photogrammetric techniques. The projects produced two major algorithms: one that identifies trees from ALS (called TrEx),and one that measure the stem from photogrammetric point clouds or lidar.
Products
TrEx is implemented as a stand alone software implemented in Java that can be download as a freeware. DOWNLOAD TrEx.
A Phuython implementation of TrEx, more functional and faster can be found on Github.
Both implmentations can be used under the GNU General Public License
Publications
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Garms , C.G. and Strimbu, B.M.Impact of stem lean on estimation of Douglas-fir (Pseudotsuga menziesii) diameter and volume using mobile lidar scans. Canadian Journal of Forest Research. https://doi.org/10.1139/cjfr-2020-0484
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Strimbu BM, Qi C, Sessions J 2019. Accurate Geo-Referencing of Trees with No or Inaccurate Terrestrial Location Devices. Remote Sensing 11(16): 1877-1897
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Maturbong B, Wing M, Strimbu BM, Burnett M. 2019. Forest inventory sensivity to UAS-based image processing algorithms. Annals of Forest Research 62(1)
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Fang R. and Strimbu B.M. 2019 Comparison of Mature Douglas-Firs’ Crown Structures Developed with Two Quantitative Structural Models Using TLS Point Clouds for Neighboring Trees in a Natural Regime Stand Remote Sensing 11(14): 1661-1687
- Strimbu, V.F., Strimbu, B.M., 2015. A graph-based segmentation algorithm for tree crown extraction using airborne LiDAR data. ISPRS Journal of Photogrammetry and Remote Sensing 104, 30-43.