Title :
Comparison of two vegetation classification techniques in China based on NOAA/AVHRR data and climate-vegetation indices of the Holdridge life zone
Author :
Li, Xiaobing ; Gong, Peng ; Pu, Ruiliang ; Shi, Peijun
Author_Institution :
Inst. of Resources Sci., Beijing Normal Univ., China
Abstract :
We have developed a new multi-source data set for integrated analysis of vegetation classification at a continental scale, and applied it in China. Two kinds of supervised classification methods, artificial neural network (NN) and maximum likelihood classification (MLC) algorithms were employed to classify the data set in order to ascertain which method is better for this new data set. Classification results were validated with the same test samples and field samples based on GPS. The accuracy of the classification by NN was better than by MLC
Keywords :
climatology; image classification; vegetation mapping; China; Holdridge life zone; NOAA/AVHRR data; artificial neural network algorithm; climate-vegetation indices; continental scale; integrated analysis; maximum likelihood classification algorithm; multi-source data set; supervised classification methods; vegetation classification techniques; Classification algorithms; Disaster management; Environmental management; Equations; Meteorology; Neural networks; Principal component analysis; Resource management; Temperature; Vegetation mapping;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2001. IGARSS '01. IEEE 2001 International
Conference_Location :
Sydney, NSW
Print_ISBN :
0-7803-7031-7
DOI :
10.1109/IGARSS.2001.977108
