地球科学进展 ›› 2009, Vol. 24 ›› Issue (10): 1073 -1083. doi: 10.11867/j.issn.1001-8166.2009.10.1073

综述与评述 上一篇    下一篇

冻土遥感研究进展:被动微波遥感
张廷军 1,2,晋锐 3,高  峰 4   
  1. 1. 中国科学院寒区旱区环境与工程研究所冻土工程国家重点实验室,甘肃  兰州  730000;
    2.美国雪冰数据中心,科罗拉多大学环境科学合作研究所,博尔德市,80309-0449,美国;
    3.中国科学院寒区旱区环境与工程研究所,甘肃 兰州 730000;4.中国科学院国家科学图书馆兰州分馆,甘肃 兰州 730000
  • 收稿日期:2009-05-27 修回日期:2009-08-10 出版日期:2009-10-10
  • 通讯作者: 张廷军 E-mail:tzhang@nsidc.org
  • 基金资助:

    公益性行业(气象)科研专项经费项目“中国冰冻圈卫星监测关键技术研究及系统开发”(编号:GYHY(QX)2007-6-18),美国航空航天局(U.S. NASA项目NAG5-13721及NNXØ6AE65G);美国阿拉斯加大学极地研究中心(U.S. NSF项目OPP-0328664)联合资助.

Overview of the Satellite Remote Sensing of Frozen Ground:Passive Microwave Sensors

Zhang Tingjun 1,2, Jin Rui 3, Gao Feng 4   

  1. 1.State Key Laboratory of Frozen Soil Engineering, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou  730000, China;
    2. National Snow and Ice Data Center, Cooperative Institute for Research in Environmental Sciences,University of Colorado, Boulder  80303-0449, USA;
    3. Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Science, Lanzhou  730000, China;4.Lanzhou Branch of the National Science Library, Chinese Academy of Science, Lanzhou  730000,China
  • Received:2009-05-27 Revised:2009-08-10 Online:2009-10-10 Published:2009-10-10

多年冻土和季节冻土分别占北半球裸露地表的24%和55%。近地表土壤冻融的范围、冻结起始日期、持续时间及冻融深度对寒季/寒区植物生长、大气与土壤间能量、水分及温室气体交换都具有极其重要的影响。自20世纪70年代以来,应用卫星遥感结合地面观测资料研究局地到区域尺度的季节冻土和多年冻土已取得诸多成果,而遥感在冻土研究中的最直接应用是利用微波探测近地表土壤冻融状态。相对于主动SAR,星载被动微波传感器具有多通道观测且重访周期较高,空间分辨率很低的特点。重点评述了近几十年来被动微波辐射计在冻土研究中的算法发展及其应用前景,主要包括双指标算法、时间序列变化检测算法及判别树算法3类,其核心均是基于冻土的低温特征和“体散射变暗”效应。发展可靠实用的微波遥感土壤冻融状态判别算法,提供区域和全球尺度上的土壤冻融状态信息,对水文学、气象学以及农业科学、工程地质研究与应用都具有重要意义。

       Permafrost and seasonally frozen ground regions occupy approximately 24% and 55%, respectively, of the exposed land surface in the Northern Hemisphere. The areal extent, timing, duration, and depth of the near-surface soil freeze and thaw have a significant impact on plant growth, energy, water and greehouse gas exchanges between the atmosphere and the soils in cold seasons/cold regions. Satellite remote sensing combined with ground “truth” measurements have been used to investigate seasonally frozen ground and permafrost at local to regional scales with some successes. However, the direct application of remote sensing in the frozen ground research is to us the passive microwave brightness temperature to detect the soil freeze/thaw cycle. Compared to the active SAR, the spaceborne radiometers has the ability of multi-channels observation with frequent revisiting period, but with coarser spatial resolution. As the succession of the review, this paper focuses on the algorithm development and potential application of passive microwave radiometers in detecting near surface soil freeze/thaw cycle. The three widely used algorithms include dual-index algorithm, change detection algorithm based on the time series of brightness temperature and the decision tree algorithm. All three algorithms are based on low-temperature characteristics and volume scattering darkening effect of frozen soil. These algorithms are highly promising in detecting surface soil freeze/thaw status. However, further algorithm refinement, calibration and validation are needed.

中图分类号: 

[1] Kimball J S, McDonald K C, Keyser A R,et al.Application of NASA Scatterometer (NSCAT) for determining the daily frozen and nonfrozen landscape of Alasks[J].Remote Sensing of Environment,2001, 75: 113-126.
[2] Goodison B E, Brown R D, Grane R G. EOS Science Plan: Chapter 6 Cryospheric System[R].NASA,1998.
[3] Zhang T, Armstrong R L. Soil freeze/thaw cycles over snow-free land detected by passive microwave remote sensing[J]. Geophysical Research Letters,2001, 28(5): 763-766.
[4] Zhang T, Armstrong R L, Smith J. Investigation of the near-surface soil freeze-thaw cycle in the contiguous United States: Algorithm development and validation[J].Journal of Geophysical Research,2003, 108(D22), doi: 10.1029/2003JD003530.
[5] Jin Rui,Li Xin.A review on the algorithms of frozen/thaw boundary detection by using passive microwave remote sensing[J]. Remote Sensing Technology and Application,2002,17(6):370-375.[晋锐, 李新. 被动微波遥感监测土壤冻融界限的研究综述[J].遥感技术与应用,2002,17(6): 370-375.]
[6] England A W.Radiobrightness of diurnally heated, freezing soil[J].IEEE Transactions on Geosciences and Remote Sensing, 1990,28(4): 464-476.
[7] Ulaby F T, Moore R K, Fung A K.Microwave Remote Sensing, Active and Passive, III: From Theory to Applications[M]. Artech House Publishers, Appendix E, 1986:2 020-2 028.
[8] McDonald K C, Kimball J S, Njoku E,et al.Variability in springtime thaw in the terrestrial high latitudes: Monitoring a major control on the biospheric assimilation of atmospheric CO2 with spaceborne microwave remote sensing[J].Earth Interactions,2004, 8(20):1-23.
[9] Zuerndorfer B, England A W. Radiobrightness decision criteria for freeze/thaw boundaries[J].IEEE Transaction on Geoscience and Remote Sensing,1992, 30(1): 89-102.
[10] Wegmuller U. The effect of freezing and thawing on the microwave signatures of bare soil[J].Remote Sensing of Environments, 1990, 33: 123-135.
[11] Wegmuller U, Matzler C, Schanda E. Microwave signatures of bare soil[J].Advance in Space Research,1989, 9(1): 307-316.
[12] England A W. The effect upon microwave emissivity of volume scattering in snow, in ice and in frozen soil[C]//Proceedings of the URSI Common II on Microwave Scattering and Emission from the Earth, 1974:273-287.
[13] Dobson C, Ulaby F T, Zuerndorfer B,et al. Mesoscale Monitoring of the Soil Freeze/thaw Boundary from Orbital Microwave Radiometry[R].Final Report to Orbiting Satellite Project, NASA/Goddard Space Flight Center,1990:30.
[14] England A W. Galantowicz J F, Zuerndorfer B W. A volume scattering explanation for the negative spectral gradient of frozen soil[C]//Proceeding of IGARSS′91,1991:1 175-1 177.
[15] England A W. Thermal microwave Emission from a Scattering Layer[J].Journal of Geophysical Research Soild Earth, 1975,80(32):4 484-4 496.
[16] Zuerndorfer B, England A W, Ulaby F T. An optimized approach to mapping freezing terrain with SMMR data[C]//Proceeding of IEEE International Geoscience and Remote Sensing Symposium,1990:1 153-1 156.
[17] Zuerndorfer B W, England A W, Dobson M C, et al. Mapping freeze/thaw boundaries with SMMR data[J].Agricultural and Forest Meteorology,1990, 52:199-225.
[18] Hoekstra P, Delaney A. Dielectric properties of soils at UHF and microwave frequencies[J].Journal of Geophysical Research, 1974, 79(11):1 699-1 708.
[19] Cao Meisheng, Chang Tiejun. Monitoring terrain soil freeze/thaw condition on Qinghai Plateau in spring and autumn using microwave remote sensing[J].Journal of Remote Sensing,1997,1(2):139-144.[曹梅盛, 张铁军. 青海高原春秋季地表土冻融的微波遥感监测[J]. 遥感学报,1997,1(2):139-144.]
[20] Toll D L, Owe M, Foster J, et al. Monitoring seasonally frozen soils using passive microwave satellite data and simulation modeling[C]//Proceeding of International Geoscience and Remote Sensing Symposium, 1999: 1 149-1 151.
[21] Hollinger J. DMSP Special Sensor Microwave/Imager Calibration/Validation[R]. Final Report volume I, Naval Research Laboratory,1989.
[22] Judge J, Galantowicz J F, England A W,et al.Freeze/thaw classification for prairie soils using SSM/I radiobrightness[C]//Proceeding of International Geoscience and Remote Sensing Symposium.1996: 2 270-2 272.
[23] Chang A T C, Cao M S. Monitoring soil condition in the northern Tibetan Plateau using SSM/I data[J].Nordic Hydrology,1996, 27(3): 175-184.
[24] Zhang T, Armstrong R L, Smith J. Detecting seasonally frozen soils over snow-free land surface using satellite microwave remote sensing data[C]//Proceedings of the Fifth Conference on Polar Meteorology and Oceanography.1999:355-357.
[25] Kim E J, England A W. Passive microwave freeze/thaw classification for wet tundra regions[C]//Proceeding of International Geoscience and Remote Sensing Symposium, 1996, 4: 2 267-2 269.
[26] Yershov E D. General Geocryology[M].Cambridge: Cambridge University Press, 1998.
[27] Zhang T. Influence of the seasonal snow cover on the ground thermal regime: An overview[J].Reviews of Geophysics,2005, 43, RG4002, doi:10.1029/2004RG000157.
[28] Goodrich L E. The influence of snow cover on the ground thermal regime[J].Canadian Geotechnical Journal,1982, 19: 421-432.
[29] Zhang T, Osterkamp T E, Stamnes K. Influence of the depth hoar layer of the seasonal snow cover on the ground thermal regime[J].Water Resources Research,1996, 32(7):2 075-2 086.
[30] Zhang T, Stamnes K. Impact of climatic factors on the active layer and permafrost at Barrow, Alaska[J].Permafrost and Periglacial Processes,1998,9:229-246.
[31] Smith N V, Saatchi S S, Randerson J T. Trends in high northern latitudes soil freeze and thaw cycles from 1988 to 2002[J]. Journal of Geophysical Research,2004, 109, D12101, doi:10.1029/2003JD004472.
[32] Basist A, Grody N C, Peterson T C, et al. Using the special sensor microwave/imager to monitor land surface temperatures, wetness and snow cover[J].Journal of Applied Meteorology,1998, 37: 888-911.
[33] McGuire A D, Apps M, Chapin F S III,et al.Land cover and land use change in Alaska and Canada[C]//Land Change Science: Observing, Monitoring, and Understanding Trajectories of Change on the Earth's Surface, 2005.
[34] Canny J F. A computational approach to edge detection[J].IEEE Transactions on Pattern Analysis and Machine intelligence, 1986, 8(6): 679-698.
[35] Stone R S, Dutton E G, Harris J M,et al.Earlier spring snowmelt in northern Alaska as an indicator of climate change[J].Journal of Geophysical Research,2002, 107(D10), doi: 10.1029/2000JD000286.
[36] Jin Rui, Li Xin, Che Tao.A decision tree algorithm for surface freeze/thaw classification using SSM/I[J].Journal of Remote Sensing,2008,12(6):1 017-1 027.[晋锐, 李新, 车涛.SSM/I监测地表冻融状态的决策树算法[J].遥感学报, 2008,12(6):1 017-1 027.]
[37] Zhou Youwu, Guo Dongxin, Qiu Guoqing,et al.Geocryology in China[M]. Beijing: Science Press,2000.[周幼吾,郭东信,邱国庆,等.中国冻土[M].北京:科学出版社, 2000.]
[38] Cao Meisheng, Li Xin, Chen Xianzhang,et al. Remote Sensing of Cryosphere[M]. Beijing: Science Press,2006.[曹梅盛,李新,陈贤章,等.冰冻圈遥感[M].北京:科学出版社,2006.]

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