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GM Help File - Add Discussion: Base Bin Size

kbellis Global Mapper UserTrusted User
edited February 2014 in Suggestion Box
Base Bin Size 01.PNG

The GM Help file I think would benefit from a discussion or a little primer as to what Base Bin Size means as well as the significance to specifying minimum height departures. Also maybe include a N.B. for user to take a peek at their metadata related to their point cloud; e.g., the bits regarding post spacings and what that means: Code:
              LiDAR was collected at a 2.0 meter nominal post spacing (2.0m GSD) for approximately 8200 square miles of Coastal areas 
              including parts of Maine, New Hampshire, Massachusetts, Rhode Island, Connecticut, and New York, as part of the 
              American Recovery and Reinvestment Act (ARRA) of 2010, while no snow was on the ground and rivers were at or below 
              normal levels.  Some areas of the project require 1.0 meter nominal post spacing (1.0m GSD), and a required 9.25cm 
              Vertical Accuracy.  Some areas along the coast of Massachusetts were to be collected under the constraints of Tidal 
              Conditions.  Project meets U.S. Geological Survey National Geospatial Program Base LiDAR Specification, Version 12.
If it's already in there, I could not find it; and if it isn't in there, it would be good to include.

This then segues into a related suggestion, but not for the Help file, rather for the interface; specifically, a tweak of the Auto Reclassification dialog:



  • global_mapper
    global_mapper Administrator
    edited February 2014
    The 'Point Spacing' option is already based on a somewhat smart algorithm for determining a native point density for the Lidar data set. Basically when you load a point cloud Global Mapper will chop the point cloud up into a bunch of boxes, then calculate the density of points in each box. Then any boxes that are mostly empty are ignored and the average and standard deviation of the density rest of the boxes is calculated and a point density for the point cloud chosen as the smaller of 1 standard deviation about the mean of the densities or halfway between the mean and maximum density. So basically a way to find a good representative density for the entire point cloud and remove spatial anomalies with no user input required.


    Global Mapper Guru
    Blue Marble Geographics for Coordinate Conversion, Image Reprojection and Vector Translation
  • kbellis
    kbellis Global Mapper User Trusted User
    edited February 2014
    Okay then... never mind :)
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