Tree Species Classification with Random Forest Using Very High Spatial Resolution 8-Band WorldView-2 Satellite Data
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Abstract
Tree species diversity is a key parameter to describe forest ecosystems. It is, for example, important for issues such as wildlife habitat modeling and close-to-nature forest management. We examined the suitability of 8-band WorldView-2 satellite data for the identification of 10 tree species in a temperate forest in Austria. We performed a Random Forest (RF) classification (object-based and pixel-based) using spectra of manually delineated sunlit regions of tree crowns. The overall accuracy for classifying 10 tree species was around 82% (8 bands, object-based). The class-specific producer’s accuracies ranged between 33% (European hornbeam) and 94% (European beech) and the user’s accuracies between 57%…
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Authors
3Topics & keywords
Topics
Keywords
- Beech
- Remote sensing
- Random forest
- Scots pine
- Forestry
- Environmental science
- Tree (set theory)
- Geography
UN Sustainable Development Goals
- Life below water
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