摘要
热带森林地区生物量占全球森林总生物量的40%,对于维护全球碳平衡具有重要的意义。为了给热带森林的变化监测提供有效的基础数据,采用面向对象分类方法,基于K&C(Kyoto andCarbon)PALSAR正射校正合成产品数据,研究了利用多尺度分割、特征提取及规则集建立等方法进行热带森林制图。结果表明:极化比值(HV/HH)对森林较敏感,所采用的分类方法能够很好地识别出森林,两个时相的分类结果也能够清楚地反映森林的变化情况。
Tropical forest plays important role in keeping carbon balance by its biomass,which occupies 40% of the world.In order to provide basic data for tropical forest change monitoring,object-oriented classification methods was applied to study tropical forest mapping technology using Ortho-rectified PALSAR images.The study includes multi-scales segmentation,feature extraction and rules establishment and so on.The study results show that the ratio of polarization features（HV/HH） is sensitive for forest and the object-oriented classification methods can identify forest primely,meanwhile the different classification results reflect the changes of forest between 2007 and 2009 clearly.
出处
《遥感技术与应用》
CSCD
北大核心
2012年第3期436-442,共7页
Remote Sensing Technology and Application
基金
国家自然科学基金项目"多维度微波成像的陆地遥感应用研究"(60890074)
