Aim

In this module you will gain a detailed understanding of the advantages and challenges of Earth observation using Light Detection and Ranging (LiDAR) systems. Compared to other types of remote sensing data, the data from active Light Detection and Ranging (LiDAR) systems is of particular importance for local studies, where the 3D component (height) of objects is of relevance. Commonly LiDAR data is applied it in the field of digital terrain modelling, in forestry – e.g. for canopy height assessment, or urban structure applications. LiDAR embraces a range of active remote sensing systems mounted on different platforms, which provide valuable information for characterization of horizontal and vertical structure of the earth surface by measuring the travel time of laser pulses in visible and near-infrared spectral domains. The quality of scanning depends on the nature of the LIDAR system (discrete-return or full waveform) as well as on a set of other terrain- and data-driven factors. This course provides you with an overview on the theory and applications of LiDAR data, with a particular focus on airborne laser scanning. Following the initial theoretical sections on the principles and basic characteristics of LiDAR data, diverse practical steps and exercises will be implemented to provide real-world examples to illustrate how the LiDAR point clouds can be applied to extract information on terrain, surface and vegetation. These information will be further employed to model vegetation structural attributes on multiple spatial scales ranging from single trees to landscape levels.

Content

Block 1: Introduction to LiDAR (how does laser scanning work?)

• Reminder on general remote sensing issues: difference between active and passive sensing
•  History of LiDAR measurements
•  Basics of LiDAR data measurements (platforms, sensors)
• Airborne vs. spaceborne LiDAR: history, applications and data access
• Measurement of travel time of laser light (pulsed time of flight)
• On the concept of “structure”: why a third dimension is crucial?

Block 2: Principles of LiDAR measurements

• Platform navigation, orientation and positioning
• Difference between types of data acquisitions: discrete return and echo waveform
• The recorded parameters: elevation, height, signal intensity and co.
• The concept of „single-pulse“ vs. „multiple-pulse“
• How are the incoming returns recorded? first come- first served!
• Terrestrial LiDAR measurement: one position, rotating scanner
• Data formats and big data-management: each byte matters!

Block 3: Elevation models:

• General thoughts: why are the elevation models essential?
• Digital terrain models
• Digital surface models
• Normalized DSM (Canopy height models)
• Application fields: Forest, landscape and habitat representations

• Magnified focus on Forest (basic and derived parameters): Diameter at breast height,  height, tree type proportions, tree type mapping, crown closure, stem count, growing stock und aboveground biomass
• Single tree measurements
• Urban: City models, roof top and building footprints

Block 4: Exercises in Open-Source domain of LiDAR data processing (Fusion/LDV, LASTools, R)

• Exercises on point cloud processing
  • Import, export, visualizations and rendering
  • Sample measurements, single tree measurements and associated tasks
  • Elevation models
  • Data trimming, cropping, smoothing and generalizing
  • Catalog and descriptive communication
• Extraction of metrics for modeling purposes
  • Thoughts on metrics
  • Intensity: yes or no?
  • Multi-scale metric extraction
  • Multi-source metric extraction

• Class works and workshops (CIP-Pool/Homework)
• Literature review, discussion groups and public presentations

 

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