Journal
EUROPEAN JOURNAL OF FOREST RESEARCH
Volume 131, Issue 4, Pages 1071-1089Publisher
SPRINGER
DOI: 10.1007/s10342-011-0577-2
Keywords
Forest cover mapping; Remote sensing; Forest inventory; Low mountain range; Central Europe; Spatially adaptive classification approach
Categories
Funding
- INTERREG IVB in Northwest Europe
- EU
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Due to high variation in forest communities, forest structure and the fragmentation of the forested area in Central Europe, satellite-based forest inventory methods have to meet particularly high-quality requirements. This study presents an innovative method to combine official forest inventory information at stand level with multidate satellite imagery using a spatially adaptive classification approach for producing wall-to-wall forest cover maps of important tree species and management classes across multiple ownership regions in a heterogeneous low mountain range in Germany. The classification approach was applied to a 5,200-km(2) area (about 2,080 km(2) of forest land, mostly mixed forests) located in the Eifel mountain range in Central Europe. In comparison with conventional classifiers, our results demonstrate a significant increase in classification accuracy in the order of 12%. The method was tested with ASTER images but holds the potential to be used for regular state forest inventories based on standard and novel earth observation data supplied for instance from the SPOT-5 and RapidEye sensors.
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