GeoCue Corporation

LIDAR 1

LIDAR Processing Environment

LIDAR 1 CuePac is the first application Environment Pac for GeoCue. LIDAR 1 is designed to accommodate a wide variety of tools from the vendors of your choice, as well as software tools that you have internally developed.

LIDAR 1 Brochure

LIDAR 1 Overview Presentation

LIDAR 1 Workflow Guide v6.1

LYNX Mobile Mapping System

The LYNX MMS CuePac is a server-licensed collection of tools to enable support for the Optech LYNX Mobile Mapping System. Managing large Mobile Mapping System (MMS) projects (and 10 km is large!) is a daunting task without tools to manage and visualize the LIDAR and camera data. Features of this CuePac include:

• LYNX Multi-laser scanner data import
• Precise SBET Display
• TerraScan trajectory generation for LYNX
• Camera Station Import Support
• Camera calibration record management
• Display image in RasterVue when camera station is selected
• Project-wide data scaling to support millimeter scaling

The LYNX MMS CuePac augments the LIDAR 1 CuePac to provide complete LYNX data management, visualization and Terrasolid integration in an efficient multi-user workflow. As with all specialized support modules in GeoCue, complete support for optional project management tools such as Project Portal and Project Dashboard work “out of the box.”

LYNX MMS CuePac Brochure

FMAS

The Feature Measurement and Adjustment System (FMAS) CuePac is a system used to improve the horizontal accuracy of LIDAR data. This type of adjustment exploits the high relative accuracy of LIDAR data collects to allow use of the data in engineering scale applications. The FMAS CuePac can also be used to perform horizontal accuracy assessments of both LIDAR data and ortho photos. Using a control source such as Ground Control or orthos of known accuracy, FMAS provides functions to:

• Measure point and line control in LIDAR intensity images (LIDAR “Orthos”)
• Compute adjustment parameters between congruent lines (e.g. paint strips, pavement edge markings)
• Multi-measure points/lines to reduce operator location errors
• Provides complete statistics for Root-Mean-Square error analysis
• Generate affine adjustment parameters for horizontally correcting LIDAR data to the control
• Applying the affine data transformation to the LIDAR data on a project-wide basis using the GeoCue distributed processing system