Background:Current automated forest investigation is facing a dilemma over how to achieve high tree-and plotlevel completeness while maintaining a high cost and labor efficiency.This study tackles the challenge by exp...Background:Current automated forest investigation is facing a dilemma over how to achieve high tree-and plotlevel completeness while maintaining a high cost and labor efficiency.This study tackles the challenge by exploring a new concept that enables an efficient fusion of aerial and terrestrial perspectives for digitizing and characterizing individual trees in forests through an Unmanned Aerial Vehicle(UAV)that flies above and under canopies in a single operation.The advantage of such concept is that the aerial perspective from the above-canopy UAV and the terrestrial perspective from the under-canopy UAV can be seamlessly integrated in one flight,thus grants the access to simultaneous high completeness,high efficiency,and low cost.Results:In the experiment,an approximately 0.5 ha forest was covered in ca.10 min from takeoff to landing.The GNSS-IMU based positioning supports a geometric accuracy of the produced point cloud that is equivalent to that of the mobile mapping systems,which leads to a 2–4 cm RMSE of the diameter at the breast height estimates,and a 4–7 cm RMSE of the stem curve estimates.Conclusions:Results of the experiment suggested that the integrated flight is capable of combining the high completeness of upper canopies from the above-canopy perspective and the high completeness of stems from the terrestrial perspective.Thus,it is a solution to combine the advantages of the terrestrial static,the mobile,and the above-canopy UAV observations,which is a promising step forward to achieve a fully autonomous in situ forest inventory.Future studies should be aimed to further improve the platform positioning,and to automatize the UAV operation.展开更多
Registration of TLS data is an important prerequisite to overcome the limitations of occlusion.Most existing registration methods rely on stems to determine the transformation parameters.However,the complexity of the ...Registration of TLS data is an important prerequisite to overcome the limitations of occlusion.Most existing registration methods rely on stems to determine the transformation parameters.However,the complexity of the registration problem increases dramatically as the number of stems grows.It is tricky to reduce the stems and determine the valid ones that can provide reliable registration transformation without a knowledge of the two scans.This paper presents an automatic and fast registration of TLS point clouds in forest areas.It reduces stems by selecting from the overlap areas,which are recovered from the mode-based key points that are detected from crowns.The proposed method was tested in a managed forest in Finland,and was compared with the stem-based registration method without reducing stems.The experiments demonstrated that the mean rotation error was 2.09′,and the mean errors in horizontal and vertical translation were 1.13 and 7.21 cm,respectively.Compared with the stem-based method,the proposed method improves the registration efficiency significantly(818 s vs 96 s)and achieves similar results in terms of the mean registration errors(1.94′for rotation error,0.83 and 7.38 cm for horizontal and vertical translation error,respectively).展开更多
基金supported in part by the Strategic Research Council at the Academy of Finland project“Competence Based Growth Through Integrated Disruptive Technologies of 3D Digitalization,Robotics,Geospatial Information and Image Processing/Computing-Point Cloud Ecosystem(293389,314312),Academy of Finland projects“Estimating Forest Resources and Quality-related Attributes Using Automated Methods and Technologies”(334830,334829)”,“Monitoring and understanding forest ecosystem cycles”(334060)。
文摘Background:Current automated forest investigation is facing a dilemma over how to achieve high tree-and plotlevel completeness while maintaining a high cost and labor efficiency.This study tackles the challenge by exploring a new concept that enables an efficient fusion of aerial and terrestrial perspectives for digitizing and characterizing individual trees in forests through an Unmanned Aerial Vehicle(UAV)that flies above and under canopies in a single operation.The advantage of such concept is that the aerial perspective from the above-canopy UAV and the terrestrial perspective from the under-canopy UAV can be seamlessly integrated in one flight,thus grants the access to simultaneous high completeness,high efficiency,and low cost.Results:In the experiment,an approximately 0.5 ha forest was covered in ca.10 min from takeoff to landing.The GNSS-IMU based positioning supports a geometric accuracy of the produced point cloud that is equivalent to that of the mobile mapping systems,which leads to a 2–4 cm RMSE of the diameter at the breast height estimates,and a 4–7 cm RMSE of the stem curve estimates.Conclusions:Results of the experiment suggested that the integrated flight is capable of combining the high completeness of upper canopies from the above-canopy perspective and the high completeness of stems from the terrestrial perspective.Thus,it is a solution to combine the advantages of the terrestrial static,the mobile,and the above-canopy UAV observations,which is a promising step forward to achieve a fully autonomous in situ forest inventory.Future studies should be aimed to further improve the platform positioning,and to automatize the UAV operation.
基金funded by the Key Program of the National Natural Science Foundation of China(No.41531177)the National Natural Science Foundation of China(No.41901403)+1 种基金the National Science Fund for Distinguished Young Scholars of China(No.41725005)Academy of Finland,Strategic Research Council at the Academy of Finland is gratefully acknowledged through project(314312)as well as Academy of Finland through projects(334830,334829,300066).
文摘Registration of TLS data is an important prerequisite to overcome the limitations of occlusion.Most existing registration methods rely on stems to determine the transformation parameters.However,the complexity of the registration problem increases dramatically as the number of stems grows.It is tricky to reduce the stems and determine the valid ones that can provide reliable registration transformation without a knowledge of the two scans.This paper presents an automatic and fast registration of TLS point clouds in forest areas.It reduces stems by selecting from the overlap areas,which are recovered from the mode-based key points that are detected from crowns.The proposed method was tested in a managed forest in Finland,and was compared with the stem-based registration method without reducing stems.The experiments demonstrated that the mean rotation error was 2.09′,and the mean errors in horizontal and vertical translation were 1.13 and 7.21 cm,respectively.Compared with the stem-based method,the proposed method improves the registration efficiency significantly(818 s vs 96 s)and achieves similar results in terms of the mean registration errors(1.94′for rotation error,0.83 and 7.38 cm for horizontal and vertical translation error,respectively).
