被动微波遥感估算雪水当量研究进展与展望

doi:10.11867/j.issn.1001-8166.2004.02.0204

地球科学进展 ›› 2004, Vol. 19 ›› Issue (2): 204 -210. doi: 10.11867/j.issn.1001-8166.2004.02.0204

车涛;李新

中国科学院寒区旱区环境与工程研究所，甘肃兰州 730000

收稿日期:2003-02-09 修回日期:2003-08-04 出版日期:2004-12-20
通讯作者: 车涛(1976-), 男, 陕西周至县人, 博士研究生, 主要从事冰冻圈的被动微波遥感研究. E-mail:E-mail:chetao@ns.lzb.ac.cn
基金资助:
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：90202014）和“青藏高原积雪和冻土的被动微波遥感监测研究”(编号: 49971060)资助.

THE DEVELOPMENT AND PROSPECT OF ESTIMATING SNOW WATER EQUIVALENT USING PASSIVE MICROWAVE REMOTE SENSING DATA

CHE Tao, LI Xin

Cold and Arid Regions Environmental and Engineering Research Institute, CAS, Lanzhou 730000, China

Received:2003-02-09 Revised:2003-08-04 Online:2004-12-20 Published:2004-04-01

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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

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.

Key words: Passive microwave, Remote sensing, Snow water equivalent, SSM/, Qinghai-Tibetan plateau.

中图分类号:

TP721.1

［1］ England A W. Thermal microwave emission from a scattering layer［J］. Journal of Geophysical Research, 1975,80(32): 4 484-4 496.
［2］ Chang A T C, Gloersen P, Schmugge T,et al. Microwave emission from snow and glacier ice［J］. Journal of Glaciology, 1976,16(74): 23-39.
［3］ Chang A T C, Foster J L, Hall D K. Nimbus7 SMMR derived global snow cover parameters［J］. Annals of Glaciology, 1987, 9:39-44. 
［4］ Neale C M U, McFarland M J, Chang K. LandSurfaceType classification using microwave brightness temperature from the special sensor microwave/Imager ［J］. IEEE Transaction on Geoscience and Remote Sensing, 1990,28(5): 829-837.
［5］ Goodison B E, Walker A E. Canadian development and use of snow cover information from passive microwave satellite data［A］. In: Choudhury, B J, Kerr Y H, Njoku E G, et al, eds. ESA/NASA International Workshop［C］. Utrecht, The Netherlands：VSP, 1994.245-262. 
［6］ Chang A T C, Foster J L, Hall D K. Effects of forest on the snow parameters derived from microwave measurements during the boreal［J］. Hydrology Processing, 1996,10:1 565-1 574.
［7］ Hallikainen M T. Microwave radiometry on snow［J］. Advance in Space Research, 1989, 9 (1): 267-275.
［8］ Gan T Y. Passive microwave snow research in Canadian high arctic［J］. Canadian Journal of Remote Sensing, 1996, 22 (1): 36-44.
［9］ Foster J L, Chang A T C, Hall D K. Comparison snow mass estimates from a prototype passive microwave snow algorithm, a revised algorithm and snow depth climatology ［J］. Remote Sensing of Environment,1997,62:132-142.
［10］ Singh P R, Gan T Y. Retrieval of snow water equivalent using passive microwave brightness temperature data ［J］. Remote Sensing of Environment, 2000,74 (2): 275-286.
［11］ Balk B, Elder K. Combining binary decision tree and geostatistical methods to estimate snow distribution in a mountain watershed［J］. Water Resources Research, 2000,36:13-26.
［12］ Pulliainen J T, Grandell J, Hallikainen M T. HUT snow emission model and its applicability to snow water equivalent retrieval［J］.IEEE Transaction on Geoscience and Remote Sensing,1999,37(3): 1 378-1 390.
［13］ Goodison B E, Rubinstein I, Thirkettle F W, et al. Determination of snow water equivalent on the Canadian prairies using microwave radiometry［J］. IAHS Publish, 1986, 155: 163-173.
［14］ Tait A. Estimation of snow water equivalent using passive microwave radiation data［J］. Remote Sensing of Environment, 1998, 64:286-291.
［15］ Derksen C, Walker A E, LeDrew E, et al. Timeseries analysis of passivemicrowavederived central North American snow water equivalent imagery［J］. Annals of Glaciology,2002,34:1-7. 
［16］ Walker A E, Silis A. Snow-cover variations over the Mackenzie River basin, Canada, derived from SSM/I passivemicrowave satellite data［J］. Annals of Glaciology, 2002,34:8-14.
［17］ Goodison B E, Walker A E. Canadian development and use of snow cover information from passive microwave satellite data［A］. In: Choudhury B J, Kerr Y H, Njoku E G, eds. Passive Microwave Remote Sensing of Land-atmosphere Interactions［C］. Zeist, The Netherlands: VSP BV Publishers, 1995. 245-262.
［18］ Mognard N M, Josberger E G. Northern Great Plains 1996/97 seasonal evolution of snowpack parameters from satellite passivemicrowave measurements［J］. Annals of Glaciology, 2002,34:15-23.
［19］ Chang A T C, Foster J L, Hall D K. Nimbus7 SMMR derived global snow cover parameters ［J］. Annals of Glaciology, 1987,9:39-44.
［20］ Cao Meisheng(曹梅盛), Li Peiji(李培基), Robinson D A, et al. Evaluation and primary application of microwave remote sensing SMMR derived snow cover in Western China［J］. Remote Sensing of Environment(环境遥感), 1993, 8(3): 260-269(in Chinese). 
［21］ Cao Meisheng(曹梅盛), Li Peiji(李培基). Microwave remote sensing monitoring of snow in West China［J］. Journal of Mountain Research(山地研究), 1994,12(4): 231-233(in Chinese).
［22］ Bo Yanchen(柏延臣), Feng Xuezhi(冯学智), Li Xin(李新), et al. The retrieval of snow depth in QinghaiXizang (Tibet) plateau from passive microwave remote sensing data and its results assessment［J］. Journal of Remote Sensing(遥感学报), 2001,5(3): 161-165（in Chinese）
［23］ Armstong R L, Brodzik M J. Hemisphericscale comparison and evaluation of passivemicrowave snow algorithms ［J］. Annals of Glaciology, 2002,34:38-44.
［24］ Matzler C. Passive microwave signatures of landscapes in winter［J］.Meteorology Atmosphere Physical, 1994, 54:241-260.
［25］ Ulaby F T, Moore R K, Fung A K. Microwave Remote Sensing: Active and Passive (Vol. Ⅲ)［M］. London: Artech House Publishers Inc, 1984. 1612.
［26］ Zwally H J. Microwave emissivity and accumulation rate of polar firn［J］.Journal of Glaciology,1977, 18(79): 195-215.
［27］ Armstrong R, Chang A, Rango A, et al. Snow depths and grain size relationships with relevance for passive microwave studies［J］.Annual of Glaciology, 1993,17:171-176.
［28］ Matzler C, Standley A. Relief effects for passive microwave remote sensing［J］. International Journal of Remote Sensing, 2000, 21(12): 2 403-2 412.
［29］ Bellerby T, Taberner M, Wilmshurst A. Retrieval of land and sea brightness temperatures from mixed coastal pixels in passive microwave data ［J］.IEEE Transactions on Geoscience and Remote Sensing, 1998,36(6): 1 844-1 851.
［30］ Zuerndorfer B, England A W. Radiobrightness decision criteria for freeze/fraw boundaries［J］. IEEE Transaction on Geoscience and Remote Sensing, 1992,30(1): 89-102.

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