Global Mapper LiDAR Processing and Surface Modelling Training Course

Course overview

LiDAR projects often fail to deliver usable terrain, asset or vegetation intelligence because point-cloud data arrives in mixed formats, coordinate systems and classifications, then is processed with inconsistent settings. Survey, engineering, environmental and GIS teams need repeatable workflows that turn LAS/LAZ collections into defensible digital terrain models, surface models, contours, elevation change outputs and analysis-ready datasets. This course focuses on using Global Mapper to inspect, clean, classify, filter and model LiDAR data while retaining clear evidence of the processing decisions made.

Participants work through the Global Mapper LiDAR workflow from data import and projection checks to point-cloud inspection, automatic and manual classification, noise removal, ground extraction and raster surface generation. They create DEMs, DTMs and DSMs; derive contours, hillshades, slope and aspect layers; calculate cut-and-fill or elevation differences; and export results for CAD, GIS and client delivery. The course also addresses practical quality-control checks, resolution selection, vertical datum awareness, breakline considerations and the consequences of using incorrect classes or interpolation settings.

Instructor demonstrations are followed by structured lab exercises using realistic airborne LiDAR datasets. Participants build a documented processing workflow, including a classified point cloud, terrain and surface rasters, derivatives and a map layout suitable for technical review. The final exercise requires participants to process a supplied LiDAR tile set against a stated project brief and produce a concise processing record that identifies inputs, settings, outputs and quality checks.

The course suits professionals who need to produce or assess LiDAR-derived surfaces in Global Mapper rather than simply view point clouds. It is particularly relevant where teams support engineering design, flood assessment, corridor mapping, forestry, asset surveys, land development or environmental reporting.

Course objectives

By the end of this course, participants will be able to:

• Import and validate LAS/LAZ point clouds using Global Mapper projection, metadata and elevation checks
• Inspect point density, return attributes, classifications and spatial coverage with Global Mapper LiDAR tools
• Classify ground, vegetation, buildings and noise points using automated and manual editing methods
• Create DTM, DSM and DEM rasters by selecting suitable point classes, gridding methods and output resolutions
• Generate contours, hillshades, slope and aspect layers from LiDAR-derived elevation models
• Calculate elevation differences and cut-and-fill volumes between terrain surfaces
• Apply quality-control checks for voids, spikes, classification errors, vertical offsets and raster artefacts
• Produce an export-ready LiDAR processing package containing source data, surfaces, derivatives and documented settings

Benefits of attending

Target competencies

Who should attend

• GIS Analysts — who need to convert point-cloud surveys into dependable terrain and surface datasets
• Surveyors and Geomatics Technicians — who prepare, check or deliver LiDAR outputs for mapping and design work
• Civil Engineering Technicians — who require terrain models, contours and volume inputs for site and corridor projects
• Remote Sensing Analysts — who need practical Global Mapper workflows for classification and elevation modelling
• Environmental and Forestry Officers — who analyse canopy, ground elevation and terrain conditions from LiDAR surveys
• Infrastructure Asset Managers — who need to assess LiDAR-derived evidence for planning, maintenance and risk decisions

Requirements and prerequisites

Participants should be comfortable using a Windows desktop environment, managing project files and navigating basic GIS data such as vector layers, raster imagery and coordinate reference systems. Familiarity with GIS concepts including layers, attributes, projections, metres versus feet and raster resolution is helpful. Some experience of Global Mapper is useful but not essential; the course begins with interface and data-management fundamentals before moving into LiDAR tools. No prior LiDAR classification experience, programming knowledge, CAD expertise or advanced remote-sensing background is required. Complete beginners should expect a technically practical week with guided exercises and time to practise core workflows.

Training methodology

The course combines short instructor-led explanations with step-by-step Global Mapper demonstrations and extended hands-on labs. Participants work with supplied LAS/LAZ datasets representing terrain, vegetation and built features, progressively building a LiDAR processing project each day. Exercises include diagnosing coordinate and classification problems, comparing gridding choices, generating surfaces and reviewing outputs against a project brief. Small-group discussions examine processing decisions and likely downstream consequences. On the final day, each participant completes a capstone workflow and records the settings, checks and deliverables they would apply in their own workplace.

Course outline

Day 1: LiDAR data foundations and Global Mapper workspace

• Global Mapper interface, Control Center and workspace configuration
• LAS and LAZ file structure, point attributes and return information
• Coordinate reference systems, horizontal units and vertical elevation units
• Importing LiDAR tiles and reviewing layer metadata
• Point-cloud display modes, shader settings and class-based visualisation
• Spatial coverage, point-density and overlap inspection
• Project workspaces, layer organisation and source-data traceability

Workshop: Participants import a multi-tile LAS/LAZ survey, verify its coordinate system and units, inspect coverage and attributes, and save a structured Global Mapper workspace.

Day 2: Point-cloud filtering and classification

• ASPRS LAS classification codes and class-selection strategy
• LiDAR Quality Control and point-cloud query tools
• Automatic ground classification settings and terrain assumptions
• Noise, low-point and high-point filtering methods
• Vegetation and building point classification workflows
• Manual point selection, reclassification and deletion tools
• Cross-section and 3D inspection for classification validation

Workshop: Participants classify a supplied mixed land-cover point cloud, remove noise, inspect results in profile view and export a checked classified LAS dataset.

Day 3: DTM, DSM and DEM surface production

• Selecting ground, first-return and all-return points for surface objectives
• LiDAR gridding workflows in Create Elevation Grid
• Grid spacing, cell size and point-density trade-offs
• Interpolation methods and void-filling behaviour
• Generating digital terrain models from ground-class points
• Generating digital surface models from canopy and structure returns
• Raster metadata, elevation units and surface-quality review

Workshop: Participants create and compare DTM and DSM outputs from the same LiDAR dataset, documenting selected classes, grid resolution and interpolation settings.

Day 4: Terrain analysis, contours and change measurement

• Hillshade generation and illumination settings for terrain interpretation
• Slope and aspect analysis from LiDAR-derived elevation grids
• Contour creation, interval selection and smoothing controls
• Watershed and flow-direction analysis using terrain surfaces
• Surface comparison with the Combine/Compare Terrain tools
• Cut-and-fill volume calculation and reporting units
• Identifying spikes, edge effects, voids and interpolation artefacts

Workshop: Participants generate contours and terrain derivatives, then compare two elevation surfaces to produce a cut-and-fill result and an exception map.

Day 5: Quality assurance, export and project application

• LiDAR processing checklists and reproducible workflow documentation
• Vertical datum awareness and control-point comparison principles
• Raster and vector output formats for GIS, CAD and web delivery
• Exporting GeoTIFF, LAS/LAZ, DXF and shapefile deliverables
• Map Layout Editor for technical maps and processing summaries
• Batch conversion and scripted workflow options in Global Mapper
• Capstone project review and workplace implementation planning

Workshop: Participants complete a capstone LiDAR processing brief and deliver a classified point cloud, DTM, DSM, contours, terrain derivatives, map layout and processing record.

Tools & standards covered

Global Mapper, Global Mapper LiDAR Module, LAS/LAZ, ASPRS LAS Classification Standard

A typical training day

Live online deliveries follow the same structure in the East Africa Time zone, with shorter screen blocks and longer breaks.

What the fee includes

How you can take this course

Certification

Participants who complete the full five days receive the Skillset Development Certificate of Completion, stating the course title, course code, dates and delivery format — suitable for professional-development records and employer reimbursement.

Frequently asked questions