时间域混合像元分析在海冰密集度变化研究中的应用  

Temporal Mixture Analysis Application in Monitoring the Antarctic Sea Ice Concentration Variability

作　　者：毕海波[1,2] 李双双[3] 

机构地区：[1]中国科学院研究生院,北京100049 [2]中国科学院遥感应用研究所,北京100101 [3]中国人民大学信息学院,北京100872

出　　处：《光谱学与光谱分析》2012年第4期1032-1037,共6页Spectroscopy and Spectral Analysis

基　　金：国家高科技研究发展计划(863计划)项目(2006AA09Z137)资助

摘　　要：传统意义混合像元分析方法是对有不同光谱特征的地物进行分解(spectral mixture analysis,SMA),得到各个组分在该像元内所占的百分数。而将光谱域的混合像元分析延伸至时间域内(temporalmixture analysis,TMA),提取的表征时间特性的端元用于像元分解所得残差小于8.5%,说明TMA提取南极地区海冰密集度时间变化特性具有可行性。将获取的多年平均端元用于2005年和2010年海冰密集度数据,得到残差分别为(1.4±2.42)%和(1.7±2.87)%,高于多年平均残差精度(1±1.53)%,在一定程度上反映某年海冰密集度数据相对多年平均值的变化。因此,TMA为全球变暖背景下的海冰密集度的时空特性研究提供了新思路。Temporal mixture analysis （TMA） is deduced from spectral mixture analysis （SMA）. They are algebraically identical except for that TMA is applied to temporal spectra and thus can extract the temporal characteristics of features. The ice concentration is diverse across the Antarctic sea through different periods, and TMA has a great potential to obtain this variability as an environmental normal. In the present study, sea ice concentration data remotely sensed by AMSR-E from 2003 to 2010 were used and seven typical endmembers were captured, standing for temporally different sea ice classification. TMA can also be uti- lized in change analysis of Antarctic sea ice concentration for its capability to record the spatial distribution of temporal characteristics, allowing further study of regional or global climatic variations. In short, TMA supplies a new method for researchers to investigate the spatial and temporal variability of polar sea ice.

关 键 词：海冰密集度 南极 TMA AMSR-E SMACC 被动微波遥感 

分 类 号：P76[天文地球—海洋科学]