摘要
湖泊面积变化监测具有重要的科学和社会意义,使用中低分辨率卫星遥感数据进行大面积的湖泊面积变化监测有很多优势,但易受混合像元的影响。本文根据湖泊水体的遥感特性,发展了使用中低分辨率卫星遥感数据的混合像元分解算法,应用线性多端元混合像元分解技术,自动、快速地得到在每个像元中湖泊所占的面积百分比;在上述分类结果的基础上,基于地物的空间依存现象,建立空间吸引力的概念,用循环迭代的方法实现超过遥感影像自身分辨率的湖泊亚像元填图。在针对青藏高原不同季节不同地区的Modis影像的实践中,显示混合像元分解算法可以提供较高精度的软分类结果;使用迭代方法进行亚像元填图是简单高效的,具有很大的应用潜力。
Lakes are valuable water-systems, used for production of drinking water, fisheries and recreation, and can be an. important indirect indicator of climatic change. MODIS data is suitable for regional to global operational observation as moderate resolution imaging spectroradiometer, costing little and having high temporal coverage. But the mixed pixel is a common problem. The objective of the study is to develop high accuracy sub-pixel mapping algorithm. Firstly, we use the multi-endmenber linear spertral unmixing spatially the water body technique to estimate the within mixed pixels corres lake fraction in the each mixed pixel, and develop an algorithm, to locate ponding to the water proportion in the pixed. The algorithm produces a finer sub-pixel lake map relative to the source MODIS image. The results indicate that it is an effcient and promising sub-pixel mapping algorithm.
出处
《水科学进展》
EI
CAS
CSCD
北大核心
2006年第3期376-382,共7页
Advances in Water Science
基金
中国科学院遥感应用研究所知识创新资助项目(CX000056)
关键词
亚像元
混合像元分解
湖泊
青藏高原
sub-pixed mapping
linear mixture analysis
lake
Tibetan Plateau
