Lidar Point Cloud Based Fully Automatic 3d Singl Tree Modelling in Forest and Evaluations of the Procedure
نویسندگان
چکیده
A whole procedure of fully automatic 3D single tree modelling based on LIDAR point cloud is introduced in the paper. The evaluation of the procedure is then delivered by verifying the modelling results with field collecting data in sample plots. With the procedure, individual trees are extracted not only from the top canopy layer but also from the sub canopy layer, 3D shape of the extracted individual tree crowns are reconstructed, from which important parameters such as crown height range, crown volume and crown contours at different height levels can be derived. For the evaluation of the performance, the procedure is implemented with LIDAR data of 25 sample plots where detailed field inventories have been accomplished. Results of the procedure such as the number of individual trees in each sample plot, the location of the detected individual trees are verified by a statistical comparison with the field collecting data. Further analysis on the evaluation results is delivered at the final.
منابع مشابه
Conditional Random Fields for Airborne Lidar Point Cloud Classification in Urban Area
Over the past decades, urban growth has been known as a worldwide phenomenon that includes widening process and expanding pattern. While the cities are changing rapidly, their quantitative analysis as well as decision making in urban planning can benefit from two-dimensional (2D) and three-dimensional (3D) digital models. The recent developments in imaging and non-imaging sensor technologies, s...
متن کاملA Lidar Point Cloud Based Procedure for Vertical Canopy Structure Analysis And 3D Single Tree Modelling in Forest
A procedure for both vertical canopy structure analysis and 3D single tree modelling based on Lidar point cloud is presented in this paper. The whole area of research is segmented into small study cells by a raster net. For each cell, a normalized point cloud whose point heights represent the absolute heights of the ground objects is generated from the original Lidar raw point cloud. The main t...
متن کاملComprehensive Analysis of Dense Point Cloud Filtering Algorithm for Eliminating Non-Ground Features
Point cloud and LiDAR Filtering is removing non-ground features from digital surface model (DSM) and reaching the bare earth and DTM extraction. Various methods have been proposed by different researchers to distinguish between ground and non- ground in points cloud and LiDAR data. Most fully automated methods have a common disadvantage, and they are only effective for a particular type of surf...
متن کاملAutomatic extraction of tree stem models from single terrestrial lidar scans in structurally heterogeneous forest environments
An important application of terrestrial laser scanning is the extraction of tree stem models for diameter at breast height (DBH) assessment and forest inventory. Much work has been done to automate this process using adjacent co-registered lidar scans. Existing studies, however, have focused on pre-registered point clouds obtained from commercial lidar systems. We envision an affordable and eff...
متن کاملDevelopment of a Procedure for Vertical Structure Analysis and 3d-single Tree Extraction within Forests Based on Lidar Point Cloud
A procedure for both vertical canopy structure analysis and 3D single tree extraction based on Lidar raw point cloud is presented in this paper. The whole study area is segmented into small study cells by a raster net. For each cell, a normalized point cloud whose point heights represent the absolute heights of the ground objects is generated from the original Lidar raw point cloud. The main tr...
متن کامل