Research objectives:

• LiDAR data are freely accessible for several German federal states.
• Several algorithms and packages have been developed to extract single tree information. Ongoing research is concerned with this topic.
• The aim of this work is to suggest a combination of methods to obtain a complete state-wide set of individual tree parameters (e.g. trunk foot coordinates, height, species, dbh, crown base, crown width, stem volume, crown volume).
• Parameters will be derived mostly from LiDAR-Data while also considering related research as well as further data sources.
• Suggesting an appropriate combination of sources/algorithms for obtaining such a dataset.

Methods:

• Single tree inventory data is available as reference data.
• Comparison of algorithms from different R packages (e.g. lidR).
• Optimization of parameter settings for different forest characteristics.
• Integrating results of already existing research e.g. for the identification of the tree species.
• Statistical evaluation of the suggested methods.

Contact:

Line Grottian                                                                                                                           03334/3820-383                                                                                                          line.grottian@thuenen.de

Marco Natkhin                                                                                                             03334/3820-340                                                                                                              marco.natkhin@thuenen.de                                                                                                        

Thünen-Institut für Waldökosysteme                                                                                             Alfred-Möller-Straße 1                                                                                                                           16225 Eberswalde

Generating/Estimating individual tree data based on freely available LiDAR-Data on federal state-level for storm damage risk assessment

Research objectives:

The leaf area index (LAI) and the degree of canopy cover are important parameters in forests for the modelling of energy and water balance. There are different methods to determine LAI and each method has it's drawbacks and uncertainties. The aim of this work is to compare different approaches for LAI and the degree of canopy cover determination. What is the best method to get an annual LAI-curve of a small forest area (<1 ha)?

Methods:

Measurements:

• Specific Leaf Area (SLA in cm²/g) & tree physiology & litter fall traps …
• UAV-derived LAI data
• Analysis of hemispherical photographs                                                                                  Fisheye + DSLR –camera +O-Mount&WinSCANOPY                                                             Solariscope SOL300

Statistical analysis

Photogrammetric analysis

Consideration of:

• Vegetation dynamics
• Sample design
• Weather conditions
• Scale
• Beech vs. scots pine

Phenological observations

Contact:                                                                                                                                              Marco Natkhin                                                                                                                                     03334/3820-340                                                                                                                      marco.natkhin@thuenen.de                                                                                                                                    Thünen-Institut für Waldökosysteme                                                                                                    Alfred-Möller-Straße 1                                                                                                                          16225 Eberswalde

Determining LAI at plot scale