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

Volume

4

fYear

2001

fDate

2001

Firstpage

1895

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 2001. IGARSS '01. IEEE 2001 International

Conference_Location

Sydney, NSW

Print_ISBN

0-7803-7031-7

Type

conf

DOI

10.1109/IGARSS.2001.977108

Filename

977108