%0 Journal Article
%T Application of Linear Spectral Mixture Analysis in Extracting Areca Thematic Information from SPOT Image<br>应用光谱混合分析法从SPOT影像提取槟榔树专题信息
%A XU Jun
%A LI Ce
%A HUANG Xuan
%A <br>许珺
%A 李策
%A 黄绚
%J 遥感技术与应用
%D 2000
%I 
%X There are many areca trees planted in Taiwan for economic reason. But the areca will do great harm to environment and people's health, and it will lead to slope erosion for its shallow root, so the planting of areca must be controlled. Remote sensing provides a useful means to monitoring the planted area of areca. But the planted densities of areca are usually low, it is difficult to identify the arecas by ordinary methods even in high ground resolution remote sensing images such as SPOT. Linear spectral mixture analysis is a method to look a pixel as composed of many different kinds of endnumbers, and it can calculate the proportion of each kind of endnumber in each pixel, so it is useful to identify the small objects in the images. In this paper, linear spectral mixture analysis is used to calculate the density of areca. Some countermeasures were put forward to make up the shortcoming of less spectral resolution of SPOT images. Then the result of linear spectral mixture analysis was compared with those of maximum likeness classification and extraction by threshold. It can be found that the result from linear spectral mixture analysis can not only extract the correct area of areca, but also calculate its density, and it is much better than those of other two methods.
%K Linear spectral mixture analysis
%K Areca trees
%K SPOT image<br>像无分解
%K 槟榔树
%K 遥感
%K 光谱混合分析法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=6F56B81324C1B239DA82AE08A4344F0C&aid=3D5868A0F722A732044FE02B144D0D16&yid=9806D0D4EAA9BED3&vid=23CCDDCD68FFCC2F&iid=CA4FD0336C81A37A&sid=E514EE58E0E50ECF&eid=6AC2A205FBB0EF23&journal_id=1004-0323&journal_name=遥感技术与应用&referenced_num=0&reference_num=12