Study on tree species identification of economic forest in Taihang Mountain based on UAV hyperspectral remote sensing
The economic forest planting area in Taihang Mountain Area was taken as the re-search object.Based on the hyperspectral remote sensing data of unmanned aerial vehicle,the hyperspectral characteristic database of different economic forest species was construc-ted,and the optimal identification model of economic forest species by hyperspectral remote sensing was obtained by using CART decision tree,maximum likelihood classifier(MLC),random forest(RF)and support vector machine(SVM).The results showed that:(1)The water vapor absorption bands of apple,apricot,persimmon,cherry and walnut were obvi-ously different around the reflection peak of 550 nm,between 750-950 nm and around 960 nm;(2)The simple ratio index(SR),carotenoid reflex index 2(CRI2),green band index(GRVI)and other 7 plants were more than 0.05,which were beneficial to the identification of economic forest species;(3)SVM was the best classification method based on spectral characteristic band,vegetation index and texture feature,which was better than MLC and RF algorithm.The overall accuracy(OA)was 95.11％and Kappa coefficient was 0.915 8.To sum up,based on the combination of characteristic band,vegetation index and texture features,the identification method of support vector machine(SVM)classification was the best identification method for six tree species.
economic foresttree species identificationUAVhyperspectralsupport vector machine
NETL
NSTL
万方数据
