%0 Journal Article
%T VEGETATION CLASSIFICATION OF MULTISPECTRAL REMOTELY SENSED DATA USING NEURAL NETWORK<br>应用神经网络和多谱段遥感数据对大屿山岛土地覆盖分类的研究
%A YANG Jian
%A CHI Hong-Kang
%A and MO Mo
%A <br>杨健
%A 池宏康
%A 莫沫
%J 植物生态学报
%D 2002
%I Editorial Office of Chinese Journal of Plant Ecology
%X Neural Networks have been proposed as a means of classifying remotely sensed data. In this paper, we address a land cover classification problem using multi-spectral Landsat Thematic Mapper(TM) data employing ANN. We design a MLP (Multi Layer Perceptron)Neural Network to classify the land cover type and compare the result with the conventional classification schemes. The results show that the neural network is superior to some of the classical statistical methods.
%K Neural Network
%K Remote sensing
%K Land cover<br>神经网络
%K 遥感
%K 土地覆盖
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=90BA3D13E7F3BC869AC96FB3DA594E3FE34FBF7B8BC0E591&jid=2F2173CCFF292BF447DC2681EA33BBAE&aid=EC5A23E00B27A386&yid=C3ACC247184A22C1&vid=96C778EE049EE47D&iid=0B39A22176CE99FB&sid=D46BA3D3D4B3C585&eid=847B14427F4BF76A&journal_id=1005-264X&journal_name=植物生态学报&referenced_num=0&reference_num=10