Drone Mapping: Advanced LiDAR, Structure-from-Motion Photogrammetry, and GNSS/GPS Data Processing Techniques for Engineering Applications

• Registration: Open until July 27, 2026
• Course Dates: August 6 & 7, 2026
• PDH: 16
• Price: $1,499
• Location: 2127 Innerbelt Business Center Drive, St. Louis, MO 63114
  
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The Advanced LiDAR, Structure-from-Motion Photogrammetry, and GNSS/GPS Data Processing Techniques for Engineering Applications Bootcamp, the fourth in our Drone Mapping series, builds on the Introduction to Drone Mapping with LiDAR & SfM Photogrammetry for Engineering Applications course (1 of 4 in the Bootcamp Bundle) and applies concepts from the GPS / GNSS RTK and PPK Mapping and Data Processing for Drone Mapping and Geotechnical Site Assessments course (3 of 4). The focus is a hands‑on, in‑depth exploration of drone‑acquired data processing, mapping deliverable creation, and accuracy assessment.

Students will work directly with real‑world data sets, completing every step of the SfM photogrammetry and LiDAR (LAS) processing workflows. By the end, they will be able to generate the 2D and 3D products commonly used in environmental and engineering applications and evaluate the accuracy and precision of their outputs.By the end of the course students should be able to:

• Integrate GNSS corrections into drone-acquired data to align imagery, apply ground control/check points, and generate DEM/DSM, contours, and orthomosaics.
• Apply error-reduction techniques to eliminate noisy data from SfM point clouds.
• Process and classify LiDAR (LAS) point clouds to produce engineering-ready terrain surfaces and hydrologically conditioned DEMs.
• Quantify and communicate accuracy using check points, vertical checks, and standardized QA/QC reporting.
• Export and share deliverables to CAD/GIS environments (Civil 3D, MicroStation, ArcGIS Pro) with clear metadata and datum specifications.

DAY 1 — Advanced SfM + GNSS Workflows for Engineering

1. Introduction & Engineering Context

• Typical use cases for environmental and engineering applications
• Engineering accuracy requirements (sub‑decimeter goals)
• Overview / Review of SfM, LiDAR, and GNSS principles
• Defining resolution and accuracy needs for projects

2. Data Processing Considerations and Philosophy

• Data and Image Organization
• Associated data
• Field notes, Mission logs, GNSS data, GIS / CAD Data, non-survey imagery, etc.
• “SOP” approach
• Reproducibility
• Training
• QA/QC

3. Review of GNSS fundamentals

• Constellations (GPS, GLONASS, Galileo, BeiDou)
• Carrier‑phase vs code‑based solutions
• Positioning methods: RTK vs PPK vs PPP

• How drones capture GNSS: onboard RTK/PPK receivers, event markers
• GNSS metadata in UAS workflows (camera events, time tagging, IMU sync)

• Understanding accuracy, dilution of precision (DOP), and baseline length

Hands-On:

Format GNSS Data for import to SfM and LiDAR software.

4. SfM Photogrammetry Processing

• High‑precision alignment using GNSS‑corrected camera positions
• Ground control and check points: GNSS + GCPs
• Noise / Error reduction techniques
• Dense reconstruction optimization
• Point classification and vegetation removal
• DEM, DSM, Contours, and orthomosaic generation for engineering surfaces

5. SfM QA/QC with GNSS‑Integrated Workflows

• RMSE computation (XYZ) using Check Points
• Vertical accuracy checks
• Reporting accuracy for engineering stakeholders

6. Engineering‑Grade SfM Deliverables

• DEM/DSM generation with hydrologic conditioning
• Mesh outputs for structural modeling
• Orthomosaics & planimetric features
• Exporting to Civil 3D, MicroStation, ArcGIS Pro
• Documenting GNSS metadata & accuracy summaries

Hands‑On:
Process a set of drone-acquired images to produce DEM, DSM, Contours, and Orthomosaic image. Calculate horizontal and vertical accuracy of products.

DAY 2 — LiDAR + Trajectory/GNSS‑Driven Processing + Hybrid Workflows

1. LiDAR + GNSS/IMU Integration

• How LiDAR depends on high‑quality trajectories
• Understanding LiDAR system components:
• Laser scanner
• GNSS receiver
• IMU
• Time synchronization (key failure point)
• Error sources: IMU drift, GNSS outages, lever‑arm offsets

2. LAS Data Overview

• LAS data formats
• XLAS vs LAS vs LASD
• XYZ, Intensity, and RGB information

3. LAS Data Processing and Point Cloud Classification

• Anchor points, ground control, and breaklines
• Ground classification techniques
• Workflow for generating DEM, DSM, Contours

4. Surface Modeling for Engineering

• Creating hydrologically correct DEMs
• Surface smoothing vs preserving critical edges
• Cross‑sections
• Change detection

Hands‑On:
Process a LAS data set, classify groundpoints, and produce a DEM and contours.

5. Data Management and Sharing

• Determining the appropriate resolution of final products
• Exporting products for AutoCAD
• Final reporting standards (metadata, errors, datum specifications)
• Archiving and storing data