LP360 now has a full set of feature analysis and editing tools for working with the geometries of features – points, lines and polygons – in your project[1]. As often happens with LP360 features, the initial driver for adding this capability was a very specific problem; editing the toes of stockpiles being used in volume…
You can do part of a synoptic QA/QC on LIDAR data using either LP360 command line executables or the Point Cloud Statistics Extractor, which is one of the Point Cloud Tasks found within the LP360 GUI. Some general QA/QC information that can be gathered includes, but is not limited to, projection information, GPS time format,…
The recently published United States Geological Survey National Geospatial Program’s LIDAR Base Specification Version 1.01 specifies that the “requirements for relative accuracy within overlap between adjacent swaths of data should be less than or equal to 10 cm RMSEz”. In version 2011.1, LP360 introduced a new tool which allows for the ability to check the…
LIDAR datasets are large and require extensive quality control and quality assurance procedures to ensure desired accuracies and product results. Statistics play an important role in evaluating LIDAR data in an efficient manner during such this QA/QC process. Statistics can be calculated for the LIDAR project dataset as a whole, for each file in the…
