LiDAR, Photogrammetry, and 3D Geospatial Modelling Program Course

Course Introduction

This advanced program provides a comprehensive foundation in LiDAR, photogrammetry, and 3D geospatial modelling technologies, equipping participants with the skills to capture, process, and analyze high-resolution spatial data for real-world applications across engineering, mapping, and environmental domains.

The course explores how laser scanning (LiDAR) and aerial photogrammetry systems are used to generate highly accurate 3D representations of terrain, infrastructure, and built environments. Emphasis is placed on integrating these technologies into modern GIS workflows for spatial intelligence.

Participants will gain hands-on understanding of point cloud processing, surface reconstruction, and 3D modelling techniques. These capabilities are essential for applications in urban planning, infrastructure development, mining, forestry, and disaster assessment.

A strong focus is placed on data acquisition methodologies, including UAV-based photogrammetry, terrestrial laser scanning, and airborne LiDAR systems. Learners will understand how to optimize sensor configurations and improve data accuracy for complex geospatial projects.

The program also introduces advanced computational techniques for processing large-scale 3D datasets, including classification, segmentation, and feature extraction. These methods are critical for converting raw spatial data into actionable intelligence.

By the end of the course, participants will be able to design and implement end-to-end 3D geospatial workflows, integrating LiDAR, photogrammetry, and GIS systems to support high-precision mapping and spatial decision-making.

Duration

10 Days

Who Should Attend

• GIS and geospatial analysts working with 3D spatial datasets
• Surveying and mapping professionals transitioning to LiDAR technologies
• Civil and infrastructure engineers involved in 3D modeling projects
• UAV/drone operators specializing in photogrammetry applications
• Remote sensing specialists handling high-resolution spatial data
• Urban planners and smart city development professionals
• Mining and geology professionals requiring terrain modeling expertise
• Forestry and environmental monitoring specialists
• Academic researchers in geoinformatics and spatial sciences
• Government agencies involved in infrastructure and land management

Course Objectives

• Enable participants to understand and apply LiDAR, photogrammetry, and 3D geospatial modelling technologies for advanced spatial analysis and real-world applications.
• Build expertise in UAV and airborne data acquisition techniques for high-resolution terrain and infrastructure mapping projects.
• Develop proficiency in point cloud processing, classification, and segmentation for accurate 3D spatial representation.
• Strengthen ability to generate digital elevation models, surface models, and 3D reconstructions from raw spatial datasets.
• Equip learners with skills to integrate LiDAR and photogrammetry outputs into GIS environments for advanced analysis.
• Enhance understanding of sensor calibration, flight planning, and data acquisition optimization techniques.
• Enable participants to apply 3D modelling techniques for urban planning, infrastructure design, and environmental assessment.
• Develop competency in handling large-scale geospatial datasets using advanced computational tools and workflows.
• Introduce machine learning approaches for automated feature extraction from 3D point cloud data.
• Strengthen visualization skills for producing high-quality 3D spatial models and interactive geospatial outputs.
• Prepare professionals to design end-to-end 3D geospatial mapping systems for industry and research applications.
• Enable practical application of LiDAR and photogrammetry in disaster assessment, mining, and smart city development.

Course Outline

Module 1: Foundations of 3D Geospatial Technologies

• Introduction to LiDAR, photogrammetry, and 3D geospatial modelling systems and their evolution
• Overview of spatial data types and 3D coordinate reference systems used in mapping workflows
• Importance of 3D geospatial data in modern engineering, planning, and environmental analysis
• Integration of 3D technologies into GIS and remote sensing ecosystems

Module 2: Principles of LiDAR Technology

• Fundamentals of laser scanning and LiDAR data acquisition principles
• Airborne, terrestrial, and mobile LiDAR system architectures and applications
• Understanding pulse return signals and point cloud generation mechanisms
• Accuracy considerations and error sources in LiDAR datasets

Module 3: Photogrammetry Fundamentals

• Principles of aerial photogrammetry and stereoscopic image interpretation
• Structure-from-motion (SfM) and multi-view geometry concepts
• Image overlap, orientation, and camera calibration techniques
• Generating 3D models from overlapping aerial imagery

Module 4: UAV Data Acquisition for Mapping

• UAV platform types and sensor configurations for photogrammetric surveys
• Flight planning strategies for optimal spatial data capture
• Regulatory considerations and safety protocols for UAV operations
• Real-time data acquisition and quality control methods

Module 5: Point Cloud Processing Techniques

• Introduction to point cloud datasets and data structure fundamentals
• Noise removal, filtering, and classification techniques for LiDAR data
• Segmentation of ground and non-ground features in 3D datasets
• Data optimization and compression techniques for large point clouds

Module 6: Digital Elevation and Surface Modelling

• Generation of digital elevation models (DEM) from LiDAR and photogrammetry
• Creation of digital surface models (DSM) for urban and terrain analysis
• Terrain interpolation and surface reconstruction techniques
• Accuracy assessment of elevation and surface models

Module 7: 3D Feature Extraction Methods

• Automated feature extraction from LiDAR and photogrammetric datasets
• Building, vegetation, and infrastructure detection techniques
• Machine learning applications for feature classification
• Integration of extracted features into GIS systems

Module 8: Georeferencing and Spatial Alignment

• Coordinate systems and georeferencing techniques for 3D datasets
• Registration of multi-source spatial data for integrated analysis
• Error correction and spatial adjustment methodologies
• Ensuring spatial accuracy across LiDAR and photogrammetry outputs

Module 9: UAV LiDAR Integration

• Combining UAV platforms with LiDAR sensors for high-resolution mapping
• Data synchronization between photogrammetry and laser scanning systems
• Hybrid workflows for enhanced spatial accuracy
• Applications in infrastructure inspection and environmental monitoring

Module 10: Urban 3D Modelling Applications

• Development of 3D city models using LiDAR and photogrammetry
• Smart city visualization and digital twin creation techniques
• Infrastructure mapping and building footprint extraction
• Urban planning and spatial simulation applications

Module 11: Environmental and Terrain Analysis

• Terrain classification and slope analysis using 3D datasets
• Vegetation structure mapping using LiDAR returns
• Floodplain and watershed modelling using elevation data
• Environmental change detection using 3D spatial models

Module 12: Infrastructure and Engineering Applications

• Road, bridge, and utility mapping using 3D geospatial data
• Structural analysis using LiDAR-based models
• Construction monitoring and progress tracking using UAV data
• Engineering-grade spatial accuracy assessment techniques

Module 13: Advanced Visualization Techniques

• 3D rendering and visualization of geospatial datasets
• Interactive modeling and virtual environment creation
• Web-based 3D GIS platforms and visualization tools
• Storytelling with spatial data for decision support

Module 14: Machine Learning for 3D Geospatial Data

• AI-based classification of point clouds and spatial features
• Deep learning applications in 3D object recognition
• Automated segmentation of LiDAR datasets
• Predictive modeling using 3D geospatial data

Module 15: Large-Scale Data Management

• Handling big LiDAR and photogrammetry datasets efficiently
• Cloud-based storage and processing of 3D spatial data
• Data compression and optimization techniques
• Workflow automation for large geospatial projects

Module 16: Future of 3D Geospatial Modelling

• Emerging trends in LiDAR and photogrammetry technologies
• Integration of autonomous systems in spatial data acquisition
• Digital twin evolution and smart infrastructure modeling
• Future applications in global geospatial intelligence systems

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808

Training Venue 

The training will be held at our Upskill Training Centre. We also offer training for a group (at a discount of 10% to 50%) at requested location all over the world. The Onsite course fee covers the course tuition, training materials, two break refreshments, buffet lunch, airport transfers, Upskill gift package, and guided tour.

Visa application, travel expenses, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Upskill certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808

Terms of Payment:

Unless otherwise agreed between the two parties’ payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.