Articles

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

  • ZHANG Ting-Jun
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  • 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 date: 2009-05-27

  Revised date: 2009-08-10

  Online published: 2009-10-10

Abstract

       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.

Cite this article

ZHANG Ting-Jun . Overview of the Satellite Remote Sensing of Frozen Ground:Passive Microwave Sensors[J]. Advances in Earth Science, 2009 , 24(10) : 1073 -1083 . DOI: 10.11867/j.issn.1001-8166.2009.10.1073

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