Abstract: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. Diameters 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.

Diameter at breast height has been estimated from mobile laser scanning using a new set of methods. A 2D laser scanner was mounted facing forward, tilted nine degrees downwards, on a car. The trajectory was recorded using inertial navigation and visual SLAM (simultaneous localization and mapping). The laser scanner data, the trajectory and the orientation were used to calculate a 3D point cloud. Clusters representing trees were extracted line-wise to reduce the effects of uncertainty in the positioning system. The intensity of the laser echoes was used to filter out unreliable echoes only grazing a stem. The movement was used to obtain measurements from a larger part of the stem, and multiple lines from different views were used for the circle fit. Two trigonometric methods and two circle fit methods were tested. The best results with bias 2.3% (6 mm) and root mean squared error 14% (37 mm) were acquired with the circle fit on multiple 2D projected clusters. The method was evaluated compared to field data at five test areas with approximately 300 caliper-measured trees within a 10-m working range. The results show that this method is viable for stem measurements from a moving vehicle, for example a forest harvester.

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ABSTRACT:The objective of this work was to create a method to measure stem attributes of standing trees on field plots in the forest using terrestrial photogrammetry. The primary attributes of interest are the position and the diameter at breast height (DBH). The developed method creates point clouds from images from three or more calibrated cameras attached to a calibrated rig. SIFT features in multiple images in combination with epipolar line filtering are used to make high quality matching in images with large amounts of similar features and many occlusions. After projection of the point cloud to a simulated ground plane, RANSAC filtering is applied, followed by circle fitting to the remaining points. To evaluate the algorithm, a camera rig of five Canon digital system cameras with a baseline of 123 cm and up to 40 cm offset in height was constructed. The rig was used in a field campaign at the Remningstorp forest test area in southern Sweden. Ground truth was collected manually by surveying and manual measurements. Initial results show estimated tree stem diameters within 10% of the ground truth. This suggest that terrestrial photogrammetry is a viable method to measure tree stem diameters on circular field plots.

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