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被动微波遥感估算雪水当量研究进展与展望
引用本文:车涛,李新.被动微波遥感估算雪水当量研究进展与展望[J].地球科学进展,2004,19(2):204-210.
作者姓名:车涛  李新
作者单位:中国科学院寒区旱区环境与工程研究所,甘肃,兰州,730000
基金项目:国家自然科学基金项目“中国西部地区陆面数据同化系统研究”(编号 :90 2 0 2 0 14 ),“青藏高原积雪和冻土的被动微波遥感监测研究”(编号 :499710 60 )资助
摘    要:被动微波遥感可以透过云层,全天候地提供地表一定深度的信息。星载被动微波遥感传感器的时间分辨率很高,在冰冻圈动态研究中有着重要的地位。在最近的二三十年中,大量被动微波遥感的应用都是在美国、加拿大、欧洲等地,而我国在这方面的研究相对较少。首先介绍了被动微波遥感数据在监测积雪方面的国内外研究进展,对现存的雪水当量(SWE)估算算法(和模型)的适用性进行讨论。然后,详细讨论了我国西部的青藏高原地区雪水当量的估算,阐明了利用SSM/I数据估算青藏高原地区雪水当量的复杂性,并指出了其复杂性产生的原因,提出了解决问题的方法,为该地区积雪动态的进一步研究提供了理论依据。

关 键 词:被动微波  遥感  雪水当量  SSM/I  青藏高原
文章编号:1001-8166(2004)02-0204-07
修稿时间:2003年2月9日

THE DEVELOPMENT AND PROSPECT OF ESTIMATING SNOW WATER EQUIVALENT USING PASSIVE MICROWAVE REMOTE SENSING DATA
CHE Tao,LI Xin.THE DEVELOPMENT AND PROSPECT OF ESTIMATING SNOW WATER EQUIVALENT USING PASSIVE MICROWAVE REMOTE SENSING DATA[J].Advance in Earth Sciences,2004,19(2):204-210.
Authors:CHE Tao  LI Xin
Institution:Cold and Arid Regions Environmental and Engineering Research Institute, CAS, Lanzhou 730000, China
Abstract:Snow water equivalent (SWE) is an important factor in the variable study of snow storage. However, the only adequately way to estimate the spatial coverage and temporal changes of snow cover in a regional scale is via remote sensing. Passive microwave data, as a complement for visible remote sensing data, despite of its coarse resolution, have the capability to penetrate clouds and snow cover and to provide dual polarization information at different frequencies. In fact, passive microwave remote sensing has played a key role in cryosphere research field in past three decades. This paper reviews the researches of monitoring snow using passive microwave remote sensing data at home and abroad. The applicability of existing algorithms (and models) to estimate snow water equivalent is assessed. Then, the retrieval of SWE in the Qinghai Tibetan plateau is discussed in detail, to illustrate the complexity of the estimating SWE using SSM/I data in the special region, and to clarify the reasons that lead to the complexity. Finally, a series of methods and solutions are offered, which provide the theory basis for the further dynamic monitoring on snow in the Qinghai Tibetan plateau regions. For improving the retrieval accuracy, several aspects should be taken into account, such as detecting wet snow and dry snow, distinguishing the snow cover and frozen soil in the SSM/I sub pixel, and comparison of retrieval results and observation data.
Keywords:Passive microwave  Remote sensing  Snow water equivalent  SSM/I  Qinghai  Tibetan plateau  
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