Course "Design of Forest Inventories based on Remote Sensing Data"

Written by Claudio Muñoz on

August 08, 2016

The course would carve out the benefit of airborne LiDAR and spectral information for inventory planning, processing and wall to wall interpolation, permanently focusing on an optimal cost efficiency and sufficient statistical relyability. Presenting examples of inventories for operational forest organisations in comparison with national forest inventories, the course is intended to be mainly practise-oriented and with a not to high scientific claim.

The course will be held on Friday 18th November in the morning (4 hours long). The instructor will be Dr. Günther Bronner who is the CEO and shareholder on Unweltdata GmbH.

The cost of course is US$30 per person. The participation to the course is strictly restricted to regularly registered ForestSat 2016 participants. For register, you must fill the Course Registration Form from your user account on the website www.forestsat2016.com

The proposed workshop would bring the following topics, combined with lots of examples from real projects:

• National forest inventories vs. inventories for forest companies.
• Permanent vs. temporary sample plots.
• Bitterlich angle count method vs. distinct circular sample plots.
• Linear sample plots.
• Regular vs. irregular inventory grids in plantations and natural grown forests.
• Concentration of sample plots in old grown forests.
• Stratification of forest areas by airborne LiDAR and spectral data (pre-fieldwork and post-fieldwork stratification).
• Clustering sample plots to minimize the effort of admission to sample plots.
• Forest inventory related GNSS-navigation.
• Referencing coordinates of fieldwork-assessed trees to a canopy height model.
• Combination of RS-based figures and fieldwork-based figures.
• Plausibility-check of terrestrial measured data by RS methods.
• Wall-to-wall interpolation based on RS data.
• Forest inventory related optimization of cost efficiency and accuracy.
• Representation of inventory results for operational management and decision support.
• RS-based update of inventory data after calamities.