Application of airborne remote sensing for forest data collection Gatis Erins, Foran Baltic The Foran SingleTree method based on a laser system developed by the Swedish Defense Research Agency is the first commercial method for single tree measurements. It describes the forest with higher accuracy than those field-based methods that are traditionally used for forest operational planning.
APPLICATION OF AIRBORNE REMOTE SENSING FOR FOREST DATA COLLECTION FTPC2009, 9-10 November 2009
Customer needs Actual information on forest resources (quantitative) Assessment of forest resources (qualitative) Information on spatial distribution of resources (landscape level) Precise, reliable and comparable data Forest data in digital format and applicable for scenario planning, analysis, etc.
FORAN SingleTree - background Swedish Defense Research Agency (FOI), dept of Laser Systems 1996 New methods and tools for laser data classification (ground, vegetation, buildings), ground modeling, tree identification and 3D modeling of buildings Development and test of methods and tools for automatic 3Denvironment modeling using remote sensing data Co-operation with Swedish University of Agriculture (SLU) for forest applications, resulting in a PhD thesis FORAN Remote Sensing established in Linköping 2007 FORAN SingleTree method - first commercial single tree-level based production line
Airborne remote sensing
High resolution surface and terraim models
Identification of single trees Single trees are detected by analysis of surface model and point data Ref. Persson, Å., Holmgren, J. & Söderman, U. 2002: Detecting and measuring individual trees using an airborne laser scanner, Photogrammetric Engineering & Remote Sensing, Vol. 68, No. 9, Sept. Persson Å., Holmgren J., and Söderman U. 2003 Detection, measurements, and species classification of individual trees for forest inventory and visualisation, in Proceeding of the ScandLaser Scientific Workshop on Airborne Laser Scanning of Forests, ISSN 1401-1204, Umeå, Sweden.
Tree species classification For each tree the laser point distribution is analyzed. The result is used for a first classification of tree specie (pine, spruce, broadleaf) Local field data is used to train the classifier Källa: FOI
Tree species classification The quality of the tree species classification can be increased if spectral information from images are used together with laser data. Different broadleaves species can be classified using hyperspectral image data Local field data is used to train the classifier Pine Spruce Deciduous Ref. Holmgren, J., Persson, Å., and Söderman, U. 2008. Species identification of individual trees by combining high resolution LiDAR data with multi-spectral images, in Special issue of International Journal of Remote Sensing - 3D Remote Sensing in Forestry, Volume 29, Issue 5, March, Pages 1537-1552
Airborne LIDAR and hyperspectral data Customer SingleTree data Local field data
FORAN Forest Inventory Different types of layers SingleTree ForestGrid Resource inventory Aggregated stands
Other forestry applications 3D visualizations of forest areas Forest vitality index Improved management planning - Climate change adaptation - Ecological landscape approach - Communication
Evaluations performed by Swedish Forest Industry Research Institute SKOGFORSK FORAN SingleTree describes the forest with higher acuracy than those field-based methods that are traditionally used for forest operational planning. As a whole, the conclusion is that FORAN SingleTree delivers improved tree and forest inventory data if compeered with traditional data collection methods for operational planning.
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