摘要
星载被动微波遥感数据以其全天候、穿透性以及不受云干扰等特点,在全球变化研究领域取得了广泛的应用,然而其较低的空间分辨率,限制了后期地物参数的反演精度。对国内外被动微波遥感数据空间分辨率提高方法进行介绍,重点介绍了基于图像处理技术的超分辨率增强和混合像元分解方法。通过对两类方法的介绍和评价,展望被动微波遥感数据混合像元分解方法的研究前景。被动微波遥感数据空间分辨率的有效提高,可以为更多的研究和应用领域服务。
Satellite-based passive microwave remote sensing data has wide applications in global environmental change research because of the characteristics of all-day observation, penetrability and uninfluenced by clouds. The main drawback of passive microwave remote sensing is the extreme low spatial resolution, which limits the precision of surface parameters retrieval. Due to the restriction of size and weight from sat- ellite payload, satellite passive microwave radiometer can not assemble a large antenna, which causes low spatial resolution. The spatial resolution improvement methods of passive microwave remote sensing data are introduced in the paper. The super spatial resolution method and passive microwave unmixing method based on image processing technology are mainly discussed. The research prospects of the unmixing meth- ods are proposed after the introduction and evaluation of present methods. The effective improvement of spatial resolution of passive microwave data can be used to service for more research and application fields well. The research results provide important information for passive microwave unmixing method with higher precision and more application field.
出处
《遥感技术与应用》
CSCD
北大核心
2012年第1期1-7,共7页
Remote Sensing Technology and Application
基金
中国科学院知识创新工程重要方向项目(KZCX2-YW-340)
国家自然科学基金项目(40971189、41101419)
中国博士后科学基金项目(20100471276)