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Forest Type Classification Method Using Multi-source Remote Sensing Data in Northeast China

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Abstract

Combined with the sentinel-1 radar and sentinel-2 optical data, the Random Forest (RF) method is used, and the overall classification accuracy is 90%, which is better than the classification result of a single data source.

© 2019 The Author(s)

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