LiDAR remote sensing

(04-GEO-OMA4-242-m01)

Lecturer

Julia Rieder

ECTS

5 ECTS

 

Aim

The course provides a practical introduction to LiDAR technology and point cloud analysis. Students gain hands-on experience with LiDAR data, from acquisition principles to processing and interpretation, and learn how LiDAR supports applications such as terrain modelling, forestry, and others. The course emphasizes critical understanding of data quality, limitations, and real-world use cases

Content

This course provides an overview of the scientific field surrounding LiDAR as a key technology for three-dimensional Earth observation. The course covers the fundamentals of LiDAR remote sensing, point cloud data structures, and processing methodologies across platforms ranging from spaceborne and airborne systems to terrestrial and mobile laser scanning. Furthermore, the course highlights current developments and emerging analytical possibilities enabled by advanced point cloud analysis and discusses future potential as LiDAR technologies and methodologies continue to evolve and converge with related disciplines.

 

Coding

Coding examples and individual work will be covered

Software

Various software programs will be used, but mainly OpenSource software such as R.

Techniques

Different techniques will be introduced and practically applied.
w

Content

The content of scientific with regard to the audience will be discussed.

General Course News and Updates

EAGLE students coding with sweets

EAGLE students coding with sweets

Today our EAGLE students applied data munging, pipes, plotting and statistics using colour distribution of sweets. They specifically used the dplyr, ggplot, kableExtra and others to compute derivatives, rearrange the data, plot it and run statistics on colour...

read more
Spatial Python block course

Spatial Python block course

Last week Steven Hill and Thorsten Dahms gave a course that introduced EAGLE students to Python-based spatial data analysis. The advantages and challenges of different python libraries, data sets and methods were covered in hands-on exercises and also discussed...

read more