Other updates to version 25 of Global Mapper include the ability to compare kriging outputs to control data as cross-validation and improvements to the creation of estimated tree footprints extracted from point clouds. These settings can also be applied to further train existing classification methods to tailor the tool for particular datasets and workflows. Users can create their automatic point cloud classifications and train Global Mapper to find specific objects in their point clouds. Also included are new segmentation processes for ground and noise classifications, such as the segmentation-based “Max Likelihood” methods, which were previously only available for non-ground points, but are better tailored for modern point cloud generation and collection approaches.Ī new Custom Feature Classification Training tool (Beta) lets users define additional custom classifications based on unique attributes and spatial patterns. This integrated tool allows users to manage automatic classifications, segmentation, and feature extraction from one window, providing the ability to share settings and run multiple processes simultaneously. The Automatic Point Cloud Analysis tool is the new hub of point cloud classification and extraction in Global Mapper Pro. Version 25 of Global Mapper Pro includes a new Point Cloud Custom Classification Training tool, existing tools redesign, and Pixels to Points processing speed improvements. What’s New in Global Mapper Pro 25 - Wed 10:00 EDT What’s New in Global Mapper Standard v25 - Wed 10:00 EDT See live demonstrations of the new tools by joining the Blue Marble team at our two-part webinar series: Keep an eye out for the standard blog to be released next Tuesday! Read about the Top New Features in Global Mapper Pro v25 here.
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