LiDAR360 LiDAR point cloud data processing and analyzing software
LiDAR360 is a point cloud post-processing and industry application software independently developed by Beijing Digital Green Earth Technology Co. LiDAR360 is a point cloud post-processing and industry application software independently developed by Beijing Digital Green Earth Technology Co.
With more than 700 powerful and flexible functions, it solves the last-mile application problems of users and provides full life-cycle services for customers in the industries of topographic mapping, engineering surveying, forestry investigation, mine safety, and real-view 3D, etc.
1. Preprocessing
Add 3D control point report function:
Added automatic detection of the target corresponding to control points.
Added support for directly defining the coordinate transformation model in the control point report.
Add online solving function for DJI L1\L2 data, support process processing.
Optimize the airband leveling function, support the joint leveling of massive point clouds and images, and support the automatic identification of targets and matching of control points from point clouds/images.
Optimize the alignment function:
Add the function of customizing local spatial Cartesian coordinate system.
Support importing control points for alignment.
2. Data Management
Add point cloud color editing function
Add unit conversion function, support all data formats of the platform.
Add ASCII to vector/vector to ASCII function.
Added support for defining projection/reprojection raster, vector and ASCII data.
Added support for selecting the target coordinate system for defining projection/reprojection from the currently loaded data.
Added support for exporting LiTIN and LiModel data to obj and osgb formats.
Add 3D affine transformation transformation relationship calculation.
Optimize the normalization function to reduce the problem of feature cracking caused by terrain undulation.
Optimize the function of clustering by attributes, and support the selection of additional attributes in statistics.
Optimize point cloud to raster function, support hole repair.
Optimize the function of image frame division, support generating frame boundary lines.
Optimize the function of extracting by echo, support maximum 15 echoes.
3. Classification
Add support for road classification extraction.
Add building classification to support wall classification.
Optimize the deep learning classification function, and add many new scenarios.
Optimize the efficiency of ground point classification function, support parallel computing
Optimize the custom deep learning classification function:
Added support for defining trained models as independent tools.
Added support for image data labeling, training and inference
Add built-in lane classification model function
Optimize point cloud deep learning model
Optimize the classification editing function:
Added support for timed saving
Added semi-automatic classification function based on SAM large model.
Added support for creating seed point setting ranges for ground point classification in selected areas.
Optimize ground point simulation, support random distribution
Optimize memory consumption..
