CUBIZEN: Global Mapper, CityEngine & Creative Tech

Use exported coordinate data to automatically detect project site ranges in terrain profiles. This tutorial demonstrates how to leverage raw X, Y coordinate data from Global Mapper CSV exports to help ChatGPT automatically identify and highlight project site boundaries on a cross-section graph, eliminating the need for manual range input. Continuing from the last session, I had more conversations with ChatGPT. It really feels like talking to a human. The Problem with Manual Site Range Input In the previous post, I manually designated the "site" area. In other words: img 1 : Intersection of the profile line and the project site boundary in Global Mapper As shown in the image above, I manually identified the range where the cross-section line intersects with the project site boundary and input that range when ChatGPT generated the graph. Using CSV Coordinate Data for Automation However, look...

Export raw elevation data from Global Mapper to CSV and use ChatGPT to generate professional, high-fidelity terrain cross-sections. This tutorial demonstrates how to overcome the visual limitations of built-in GIS profile tools. By leveraging AI-driven Python scripting, you can create custom-shaded site areas, highlight steep slopes, and add precise leader-line annotations to your terrain analysis reports. Exporting Path Profile Data from Global Mapper Today, I’d like to share an experimental workflow for improving terrain profile visualization in Global Mapper. First, please run Global Mapper. img 1 : DEM created in Global Mapper with a line segment added for profile analysis With the DEM created, add a line segment. Now, let's extract the terrain profile. img 2 : Accessing Path Profile through the Analysis/Measurement menu After selecting the line segment, right-click and select Anal...