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多山地区植被类型遥感调查 ——以金沙江流域滇西北部分为例
引用本文:朱翔,李卓卿,朱云燕,王宝荣,杨树华.多山地区植被类型遥感调查 ——以金沙江流域滇西北部分为例[J].云南环境科学,2001,20(Z1):11-16.
作者姓名:朱翔  李卓卿  朱云燕  王宝荣  杨树华
作者单位:朱翔(云南省环境科学研究所信息中心,云南,昆明,650034)       李卓卿(云南省环境科学研究所信息中心,云南,昆明,650034)       朱云燕(云南省环境科学研究所信息中心,云南,昆明,650034)       王宝荣(云南大学生态学与地植物学研究所,云南,昆明,650091)       杨树华(云南大学生态学与地植物学研究所,云南,昆明,650091)
摘    要:通常,要想从卫星图片获得象滇西北这样多山地区的信息和植被图或土地利用图是很困难的.由于地表覆盖多样性和电磁辐射率有限,很难解读这些地区的遥感资料 .由于同物异谱或同谱异物,电脑监测分类尤难解读.为满足区域调查快速发展的要求,提高自读能力,本文介绍了一种分区解读,分层解读和人机互助的方法,这些地区现有的研究结果也用于调查,获得了令人满意的结果.

关 键 词:多山地区  地表覆盖  植被  遥感
文章编号:1006-947X(2001)增-0011-06
修稿时间:2000年10月14

Interpreation of Remotely Sensed Image for Vegetation Types in Mountainous Area.
ZHU Xiang ,LI huo-qing ,ZHU Yun-yan ,WANG Bao-rong ,YANG Shu-hua.Interpreation of Remotely Sensed Image for Vegetation Types in Mountainous Area.[J].Yunnan Environmental Science,2001,20(Z1):11-16.
Authors:ZHU Xiang  LI huo-qing  ZHU Yun-yan  WANG Bao-rong  YANG Shu-hua
Institution:ZHU Xiang 1,LI huo-qing 1,ZHU Yun-yan 1,WANG Bao-rong 2,YANG Shu-hua 2
Abstract:It is usually difficult to obtain information and make vegetation maps or land use maps in mountainous areas ,such as the north-west of Yunnan Province,China from satellite image.Because of the diversity of the land covers and the difference of the electromangnetic radiation , it is difficult to interpret the remotely sensed data in these areas,especially with the super Vised Classifiaation on computers,due to the probability that some different land features have same spectra,nhile some same land features have different spectra.To meet the need of fast regional investigation and to improve the effciency of auto-interpretation , this paper describes a method of interpreting region by region,picking up layer by layer,and mutual support of man and computer,The existing research results in these areas are also put into use in the interpretation.Satisfied results have been achieved the application of this method.
Keywords:mountainous area  land cover  vegatation  supervised-classification  interpretation of remotely sensied data  
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