研究目的
To develop algorithms for calibration of mobile laser scanner data that will also work in difficult forest environments, to develop algorithms for stem diameter estimation, and to validate these algorithms on forest plots in northern Sweden.
研究成果
The calibration of the initial 3D positions of laser returns derived from an initial trajectory, estimated with a medium precision INS during long time measurements in forest with disturbed GNSS signals, made the used MLS system suitable for the estimation of tree positions and stem diameters. The method for calibration of laser return positions from a person-carried MLS was developed and used on field plots in northern Sweden, including forest with low vegetation, to estimate tree stem diameters. Similar estimates were obtained from the two estimation methods, which indicate the success of the method that was used to calibrate 3D point cloud data, also using sensor trajectories that have high position errors due to disturbed signals of global navigation satellite systems below forest canopies.
研究不足
The study was limited to six field plots in northern Sweden. The accuracy of stem diameter estimates was affected by the presence of low vegetation and branches near the ground. Small trees (DBH < 100 mm) were less likely to be detected.
1:Experimental Design and Method Selection:
The study used a mobile laser scanning (MLS) system with algorithms for automatic derivation of tree stem center positions and stem diameters. A novel method for calibration of the position for laser returns based on tree spines derived from laser data was presented.
2:Sample Selection and Data Sources:
The system was validated on six 20-m radius field plots in northern Sweden. Data were collected using a Velodyne VLP-16 laser scanner and an Inertial Navigation System (INS).
3:List of Experimental Equipment and Materials:
Velodyne VLP-16 laser scanner, NovAtel SPAN-IGM-S1 INS, GPS-702-GG antenna, and a computer for data logging and time synchronization.
4:Experimental Procedures and Operational Workflow:
The MLS system was carried by a person walking along predefined trajectories on the field plots. Laser data were collected and processed using dynamic calibration, horizontal object-based calibration, vertical object-based calibration, tree stem segmentation, spine calibration, merge segments, smooth spine calibration, and estimation of stem profiles.
5:Data Analysis Methods:
Stem diameters were estimated using circle fit estimates from individual scan revolutions and from the composed 3D point cloud. Root-Mean-Square-Error (RMSE) and bias were calculated for validation.
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