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.
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Content

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

General Course News and Updates

EAGLE M.Sc. thesis in the Arctic

EAGLE M.Sc. thesis in the Arctic

Our EAGLE student Ronja Seitz is conducting her field work for her Master thesis in the Arctic, on Svalbard. She started collecting her data in June to build up a timeseries with UAS multispectral data to investigate disturbances like rain on snow (ROS) events and...

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Master Defense: Comparing the suitability of remote sensing and wildlife camera time series for deriving phenological metrics of understory vegetation in temperate forests of Upper Franconia, Bavaria

Master Defense: Comparing the suitability of remote sensing and wildlife camera time series for deriving phenological metrics of understory vegetation in temperate forests of Upper Franconia, Bavaria

On September 18, Sarah Schneider will present her master thesis "Comparing the suitability of remote sensing and wildlife camera time series for deriving phenological metrics of understory vegetation in temperate forests of Upper Franconia, Bavaria" at 14:00 in...

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