Classification of Natural Areas in Northern Finland Using Remote Sensing Images and Ancillary Data

摘要

SYKE is performing new CORINE 2006 -classification for Finland. One of the aims is to make CORJNE classification in Northern Finland, meaning that classes like Natural grasslands and Moors and heathlands should be classified with higher accuracy. Also, some specific classes need to be interpreted for national purposes like mountain birch forests. This paper documents the first experiments made using decision tree classifier, optical and microwave remote sensing data as well as DEM and soil information. Classes are pine, spruce, deciduous tree forests, two classes of mountain birch, open bog, grasslands, heathlands and open rocks. The best overall accuracies were about 73%, when the overall accuracy of Maximum Likelihood Classification was about 58%.