How can you get the most out of LiDAR technology for geospatial analysis? In this one-on-one course, you’ll discover how to collect, analyze, and apply LiDAR data to create surprisingly detailed maps and models. You’ll receive personalized guidance and work with online modules and hands-on assignments that you can apply right away, allowing you to experience the power of LiDAR for yourself.
LiDAR, or Light Detection and Ranging, is a technology that uses laser pulses to collect detailed 3D information about the surrounding environment. Unlike traditional photography, LiDAR can see through objects such as trees and vegetation. This makes it particularly useful for applications such as forest monitoring, urban planning, and mapping hard-to-reach areas.
LiDAR works by emitting laser pulses and measuring the time it takes for the reflections of these pulses to return to the sensor. These measurements help to record distances to objects and terrain elevations with extreme precision. In recent years, LiDAR has been increasingly used in biodiversity research, forest health monitoring, and the development of autonomous vehicles.
Thanks to LiDAR’s precision, we can create much more detailed maps than is possible with other technologies. This makes LiDAR a powerful tool for collecting geospatial data that is essential for scientific and commercial applications.
In this course, you will learn the basic principles of LiDAR technology and how it is applied in various sectors. You will gain insight into the collection, analysis, and application of LiDAR data to create detailed maps and terrain models. After completing the course, you will be able to effectively apply LiDAR in practice.
You will learn about the various applications of LiDAR, such as in forest monitoring, urban planning, and autonomous vehicles. Additionally, you will discover how LiDAR plays a key role in collecting geospatial data. We will also discuss how you can use this data for both scientific and commercial purposes. Furthermore, you’ll gain a clear understanding of the various platforms on which LiDAR is deployed, such as aerial and satellite platforms, and the specific advantages of each platform.
During the course, you will also learn how LiDAR data can improve decision-making across various industries, from construction and forestry to environmental science. Additionally, practical examples will be presented of how LiDAR can increase efficiency and reduce costs, for example by reducing fieldwork.
Blended learning combines self-paced online learning with interactive sessions, allowing you to gain both theoretical knowledge and practical experience in LiDAR technology and applications. The online modules offer you the flexibility to study at your own pace. They include interactive lessons on the fundamentals of LiDAR, the collection of LiDAR data, and the application of this data in various fields, such as forest monitoring and urban planning.
During the hands-on sessions, you’ll immediately apply the knowledge you’ve gained. You’ll work with real LiDAR data and receive guidance from experts in the field. You’ll learn how to correctly collect, analyze, and integrate LiDAR data into geospatial systems, such as GIS. You’ll also discover how to use different platforms to acquire LiDAR data and how to use this data for accurate analyses and mapping.
The combination of flexible online learning and hands-on sessions ensures that you not only learn how to work with LiDAR but also how to effectively use LiDAR data in various contexts. After completing this course, you will be able to independently collect, analyze, and apply LiDAR data, enabling you to make better-informed, data-driven decisions in your field.
You’ll receive 1-on-1 guidance. After signing up, our course coordinator will contact you to schedule your first session.
After completing this course, you will be able to:
Do you have questions about the course content? Or are you unsure whether the course aligns with your learning goals or preferences? Would you prefer an in-house or private course? We’d be happy to help.
