Large-Scale Mapping of Carbon Stocks in Riparian Forests with Self-Organizing Maps and the k-Nearest-Neighbor Algorithm

Large-Scale Mapping of Carbon Stocks in Riparian Forests with Self-Organizing Maps and the k-Nearest-Neighbor Algorithm

Among the machine learning tools being used in recent years for environmental applications such as forestry, self-organizing maps (SOM) and the k-nearest neighbor (kNN) algorithm have been used successfully. We applied both methods for the mapping of organic carbon (Corg) in riparian forests due to...

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Bibliographic Details
Main Authors: Leonhard Suchenwirth, Wolfgang Stümer, Tobias Schmidt, Michael Förster, Birgit Kleinschmit
Format: Article
Language:English
Published: MDPI AG 2014-07-01
Series:Forests
Subjects:
organic matter
machine learning algorithm
neural network
Danube Floodplain
RapidEye
additional geodata
Austria
Online Access:http://www.mdpi.com/1999-4907/5/7/1635

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