The Method of Decomposing the Passive Microwave Soil Moisture Using Optical Information

  • 1. Capital Normal University, Base of the State Laboratory of Urban Environmental Processes and Digital Modeling, Beijing 100048;
    2. Institute of Remote Sensing Application, CAS, Beijing 100101;
    3. Southwest University, School of Geographical Sciences, Chongqing 400715

Received date: 2011-10-21

  Revised date: 2012-09-13

  Online published: 2012-10-25


The water held in the top few centimeters of the soil is a key variable in many hydrological, climatological and ecological processes. These data are difficult and costly to acquire through in situ measurements, especially at high temporal frequencies. Different types of remote sensing systems are currently used to infer soil moisture at different spatial and temporal scales, each with its specific characteristics and limitations. The soil moisture retrieval from passive microwave is not affected by the weather, and the algorithm is mature and reliable. But the spatial resolution of spaceborne passive microwave data is too low for many local applications, and the data are suitable for large scale studies. Optical sensors complemented with thermal infrared channels have, in spite of the strong atmospheric attenuation and the limited penetration depth of the used signal, received much attention as a source of information on soil moisture content and surface evaporation. The way the high spatial resolution surface evaporation information contained in optical/thermal sensors can be combined with relatively low resolution soil moisture. Selecting 1km resolution the Moderate Resolution Imaging Spectroradiometer (MODIS) optical data and 25km resolution the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) passive microwave data 2 level of soil moisture product, the authors used NDVI-Ts feature space to remove the vegetation effect, and decompose the passive microwave soil moisture through a soil evaporation model. At last the authors got the 1km resolution soil moisture. Through building scatter diagram, it could be found that the relevance between the inversion result and 1km Temperature Vegetation Drought Index (TVDI) reached 0.569. The quantitative results of the study still need further validation and improvement.

Cite this article

WANG An-Qi, SHI Jian-Cheng, A Che, GONG Hui-Li-* . The Method of Decomposing the Passive Microwave Soil Moisture Using Optical Information[J]. Journal of Geo-information Science, 2012 , 14(5) : 652 -657 . DOI: 10.3724/SP.J.1047.2012.00652


[1] Crow W T & Zhan X. Continental-scale evaluation of remotely sensed soil moisture products[J]. IEEE Geoscience and Remote Sensing Letters, 2007,4(3):451-455.

[2] Prigent C, Aires F, Rossow W B, et al. Sensitivity of satellite microwave and infrared observations to soil moisture at a global scale: Relationship of satellite observations to in situ soil moisture measurements[J]. Journal of Geophysical Research, 2005,110:D07110.

[3] Wagner W, Bloschl G, Pampaloni P, et al. Operational readiness of microwave remote sensing of soil moisture for hydrologic applications[J]. Nordic Hydrology, 2007,38(1):1-20.

[4] Pellenq J, Kalma J, Boulet G, et al. A disaggregation scheme for soil moisture based on topography and soil depth[J]. Journal of Hydrology, 2003, 276(1-4):112-127.

[5] Kim G, Barros A P. Downscaling of remotely sensed soil moisture with a modified fractal interpolation method using contraction mapping and ancillary data[J]. Remote Sensing of Environment, 2002,83(3):400-413.

[6] Zhan X, Houser P R, Walker J P, et al. A method for retrieving high-resolution surface soil moisture from hydros L-band radiometer and Radar observations[J]. Geoscience and Remote Sensing, IEEE Transactions, 2006, 44(6):1534-1544.

[7] Chauhan N S, Miller S, Ardanuy P. Spaceborne soil moisture estimation at high resolution: a microwave-optical /IR synergistic approach[J]. International Journal of Remote Sensing, 2003,24(22):4599-4622.

[8] Merlin O, Chehbouni A, Kerr Y, et al. A downscaling method for distributing surface soil moisture within a microwave pixel: Application to the Monsoon'90 data[J]. Remote Sensing of Environment, 2006,101:379-389.

[9] Merlin O, Chehbouni A, Kerr Y. A combined modeling and multi-spectral/multi-resolution remote sensing approach for disaggregation of surface soil moisture: Application to SMOS configuration[J]. IEEE Transactions on Geoscience and Remote Sensing, 2005,43(9):2036-2050.

[10] Merlin O, Walker J P, Chehbouni A, et al. Towards deterministic downscaling of SMOS soil moisture using MODIS derived soil evaporative efficiency[J]. Remote Sensing of Environment, 2008,112:3935-3946.

[11] Merlin O, Bitar A, Walker J, et al. An improved algorithm for disaggregating microwave-derived soil moisture based on red, near-infrared and thermal-infrared data[J]. Remote Sensing of Environment, 2010,114:2305-2316.

[12] Yang K, Koike T, Kaihotsu I, et al. Validation of a dual-pass microwave land data assimilation system for estimating surface soil moisture in semiarid regions[J]. Journal of Hydrometeorology, 2009,10:780-793.

[13] 王颖,宫辉力,赵文吉,等. 北京野鸭湖湿地资源变化特征[J]. 地理学报,2005,60(4):656-664.

[14] Carlson T, Gillies R, Perry E. A method to make use of thermal infrared temperature and NDVI measurements to infer surface soil water content and fractional vegetation cover[J]. Remote Sensing Reviews, 1994,9:161-173.

[15] Anderson M C, Norman J M, Mecikalski J R, et al. A climatological study of evapotranspiration and moisture stress across the continental united states based on thermal remote sensing: 2. surface moisture climatology[J]. Journal of Geophysical Research, 2007,112:D11112.

[16] Nishida K, Nemani R R, Glassy J M, et al. Development of an evapotranspiration index from Aqua/MODIS for monitoring surface moisture status[J]. IEEE Transactions on Geoscience and Remote Sensing, 2003,41(2): 493-501.

[17] Carlson T N, Gillies R R, Schmugge T J. An interpretation of methodologies for indirect measurement of soil water content[J]. Agricultural and Forest Meteorology, 1995,77:191-205.

[18] Price J C. The potential of remotely sensed thermal infrared data to infer surface soil moisture and evaporation[J]. Water Resources Research, 1980,16:787-795.

[19] Gentine P, Entekhabi D, Chehbouni A, et al. Analysis of evaporative fraction diurnal behavior[J]. Agricultural and Forest Meteorology, 2007,143:13-29.

[20] Komatsu T S. Towards a robust phenomenological expression of evaporation efficiency for unsaturated soil surfaces[J]. Journal of Applied Meteorology, 2003,42:1330-1334.

[21] Thom A S and Oliver H R. On Penman's equation for estimating regional evaporation[J]. Journal of the Royal Meteorological Society,1977,103:345-357.

[22] Sarwar A and Bill R. Mapping evapotranspiration in the Indus Basin using ASTER data[J]. International Journal of Remote Sensing, 2007,28:5037-5046.

[23] Liu S, Mao D, Jia L. Evaluating parameterizations of aerodynamic resistance to heat transfer using field measurements[J]. Hydrology and Earth System Sciences, 2007,11:769-783.

[24] Shangguan W, Dai Y, Liu B, et al. A soil particle-size distribution dataset for regional land and climate modeling in China[J]. Geoderma, 2012,171:85-92.

[25] Sandholt I, Rasmussen K, Andersen J. A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status[J]. Remote Sensing of Environment, 2001,79:213-224.