摘要
乌兰布和沙漠是我国主要的沙漠之一,近年来,其快速扩张已严重影响当地的生态安全。荒漠植被是该地区最重要的生态防护屏障,准确掌握植被分布状况具有重要意义。以乌兰布和沙漠的典型地区为研究对象,通过NDVI计算、主成分分析以及基于灰度共生矩阵纹理特征相结合的方法,对ALOS多光谱影像进行分析,综合NDVI和均值纹理作为分类指标,确定合适的阈值范围,采用决策树分类方法进行植被信息提取。研究表明,决策树分类可有效运用纹理等辅助信息,与传统分类方法相比能够取得更好的分类效果。
Ulan Buh Desert is one of China's major deserts.In recent years its rapid expansion has seriously affected the local ecological security.Desert vegetation is the most important ecological protection barrier in this region.Gaining the knowledge accurately of the distribution of vegetation is important.Calculated ND-VI,and integrated principal component analysis combined with Gray Level Co-occurrence Matrix texture analysis to analysis the ALOS image in the reserch area.Using NDVI and mean texture as the classification indices,the article determined the appropriate threshold range,and abstracted the vegetation information by using the decision tree method.The result shows that the decision tree method could use texture and other auxiliary information effectively,and achieve better classification results compared with traditional classifi-cation method.
出处
《遥感技术与应用》
CSCD
北大核心
2010年第5期687-694,共8页
Remote Sensing Technology and Application
基金
阿拉善SEE生态协会项目(SEEA0905YWL001)资助
关键词
NDVI
主成分分析
灰度共生矩阵
乌兰布和沙漠
荒漠植被
决策树分类
NDVI
Principal component analysis
Gray level co-occurrence matrix
Ulan Buh Desert
Desert vegetation
Decision tree classification