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ONLINE COURSE – Remote Sensing With Aircraft And Drone LiDAR Sensors (RSLD01) This course will be delivered live
13th December 2021 - 17th December 2021
£450.00
Event Date
Monday, December 12th, 2021
Course Format
This is a ‘LIVE COURSE’ – the instructor will be delivering lectures and coaching attendees through the accompanying computer practical’s via video link, a good internet connection is essential.
Time Zone
TIME ZONE – GMT+1 – however all sessions will be recorded and made available allowing attendees from different time zones to follow.
Please email oliverhooker@prstatistics.com for full details or to discuss how we can accommodate you.
About This Course
Unmanned Airborne Vehicles (UAVs) equipped with consumer-grade imaging/ranging and direct geo-referencing systems have been proven as a potential Remote Sensing platform that could satisfy the needs of a wide range of civilian applications. The continuous developments in direct georeferencing and Remote Sensing (i.e., passive and active imaging sensors in the visible and infrared range – RGB cameras and LiDAR) is providing the professional geospatial community with ever-growing opportunities to provide accurate 3D information used in environmental research to collect information about the Earth, such as vegetation and tree species.
This 4-day course aims to provide participants with an integrated
end-to-end perspective going from measurement techniques to end-
user applications, covering issues related to LiDAR sensors coupled on aircraft and UAVs, computing exercises on the processing of 3D point clouds to produce geospatial products.
Intended Audiences
Any researchers (PhD and MSc students, post-docs, primary investigators) and environmental professionals who are specialised in a variety of Earth Science disciplines and wish to expand and improve their knowledge and skills.
Venue
Delivered remotely
Course Details
Availability – 30 places
Duration – 4 days
Contact hours – Approx. 24 hours
ECT’s – Equal to 2 ECT’s
Language – English
Teaching Format
The course will be divided into theoretical lectures to introduce and explain key concepts and theories, and practices with computing exercises on the processing of LiDAR data and point clouds. Afternoon practicals will be based on the topics covered in the morning lectures.
Assumed quantitative knowledge
Familiarity with Geographic Information Systems and geospatial data (i.e., raster and vector data) could be useful, but not mandatory. A basic understanding of physics radiation and proprieties of electromagnetic spectrum could be also useful, but not required.
Assumed computer background
No prior experience with LiDAR processing software, point cloud data or any programming language is required.
Equipment and software requirements
Attendees of the course must use a computer with any Operating System installed (GNU/Linux, MS Windows or MacOS). The course will use Open-Source software (FOSS) and some proprietary software which will be downloaded, installed and configured during the lectures.
PLEASE READ – CANCELLATION POLICY
Cancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered, contact oliverhooker@prstatistics.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited.
If you are unsure about course suitability, please get in touch by email to find out more oliverhooker@prstatistics.com
COURSE PROGRAMME
Monday 6th February – Classes from 10:00 to 17:00
Module 1: Fundamentals of Light Detection and Ranging (LiDAR) technique. Theoretical principles of a LiDAR systems. Electronic and sensor components. Main differences between spatial, aerial and terrestrial platforms. The physics of laser signals: Introduction to discrete and full-waveform LiDAR and signal return analysis. Resolutions and precisions achieved. Advantages and disadvantages of the technique. Practice: Introduction to LiDAR data, platforms and services. Overview of the available processing software and programming languages/libraries.
Tuesday 7th February – Classes from 10:00 to 17:00
Module 2: Interpretation of LiDAR data. Introduction to metrics/products such as Digital Elevation Models, Digital Terrain Models and Canopy Height Models. Tree delineation approaches and algorithms (ex. Watershed Algorithm). Discrete versus full-waveform LiDAR data. Echo Decomposition for peak point extraction. Voxelisation of full-waveform LiDAR data. Introduction to binary files: Discrete and full-waveform LiDAR LAS files formats. Practice: Tridimensional point cloud processing and analysis. Filtering, measuring and classification of LiDAR point clouds.
Monday 13th February – Classes from 10:00 to 17:00
Module 3: Managing and exploring a LAS dataset. Visualization advanced techniques, metadata analysis and content reports, LiDAR points classification into ground points and non-ground points, buildings and high vegetation classification. Coordinate Reference System transforms. LIDAR points triangulation into a TIN in order to create a Digital Elevation Model. Elevation contours extraction from a LiDAR point cloud and boundary polygon extraction. RGB colour sampled from an orthomosaic.
Tuesday 14th February – Classes from 10:00 to 17:00
Module 4: Different applications for LiDAR data: biodiversity monitoring, forest health monitoring, urban planning, wood trade, archaeology and heritage monitoring and automated driving. Other types of LiDAR systems: Space-based liDAR for measuring ice sheet mass balance, cloud and aerosol heights. Bathymetric LiDAR for the study of underwater depth of ocean floors. Practice: Post-processing of LiDAR products, Digital Terrain Model and elevation profile analysis. Measurements of distances, areas and volumes. Integration with external geospatial data in a Geographic Information System (GIS).
Course Instructor
Dr. Nelson Pires
– Works at: University of Porto, Portugal
– Delivers:
Remote Sensing with satellite multi-spectral sensors (RSMS01)
Remote Sensing with drone RGB and Near Infrared cameras (RSWD01)
Remote Sensing with aircraft and drone LiDAR sensors (RSLD)
Nelson holds a degree in Physics and Surveying Engineering, a MSc and PhD degrees in Surveying Engineering from University of Porto. With more than 10 years of experience in teaching at higher education institutions and doing research work in several geospatial subjects. Past and recent research includes subjects in atmospheric corrections with high-precision Global Navigation Satellite Systems analysis, aerial and close-range photogrammetric studies with drones for coastal monitoring and map production, multi-spectral and SAR-imaging Remote Sensing for ocean wind-generated waves and ocean dynamics.
ORCID: https://orcid.org/0000-0002-6629-8060