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http://dx.doi.org/10.7745/KJSSF.2012.45.2.127

Estimation of Soil Moisture Content from Backscattering Coefficients Using a Radar Scatterometer  

Kim, Yi-Hyun (Soil and Fertilizer Management Division, National Academy of Agricultural Science, Rural Development Administration)
Hong, Suk-Young (Soil and Fertilizer Management Division, National Academy of Agricultural Science, Rural Development Administration)
Lee, Jae-Eun (Upland Crop Research Division, National Institute of Crop Science, Rural Development Administration)
Publication Information
Korean Journal of Soil Science and Fertilizer / v.45, no.2, 2012 , pp. 127-134 More about this Journal
Abstract
Microwave remote sensing can help monitor the land surface water cycle, crop growth and soil moisture. A ground-based polarimetric scatterometer has an advantage for continuous crop using multi-polarization and multi-frequencies and various incident angles have been used extensively in a frequency range expanding from L-band to Ka-band. In this study, we analyzed the relationships between L-, C- and X-band signatures and soil moisture content over the whole soybean growth period. Polarimetric backscatter data at L-, C- and X-bands were acquired every 10 minutes. L-band backscattering coefficients were higher than those observed using C- or X-band over the period. Backscattering coefficients for all frequencies and polarizations increased until Day Of Year (DOY) 271 and then decreased until harvesting stage (DOY 294). Time serious of soil moisture content was not a corresponding with backscattering over the whole growth stage, although it increased relatively until early August (R2, DOY 224). We conducted the relationship between the backscattering coefficients of each band and soil moisture content. Backscattering coefficients for all frequencies were not correlated with soil moisture content when considered over the entire stage ($r{\leq}0.50$). However, we found that L-band HH polarization was correlated with soil moisture content (r=0.90) when Leaf Area Index (LAI)<2. Retrieval equations were developed for estimating soil moisture content using L-band HH polarization. Relation between L-HH and soil moisture shows exponential pattern and highly related with soil moisture content ($R^2=0.92$). Results from this study show that backscattering coefficients of radar scatterometer appear effective to estimate soil moisture content.
Keywords
Microwave remote sensing; Scatterometer; Backscattering coefficients; Soil moisture content; Retrieval equations;
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1 Bahari, S.A., H. Tali., T. Chuah, and H.T. Ewe. 1997. A preliminary study of phenological growth stages of wetland rice using ERS1/2 SAR data. in proc. IEEE International Geoscience Remote Sensing Symposium. pp. 1069-1071.
2 Bartsch, A., C. Pathe, and W. Wagner. 2007. Relative soil moisture from C- and L-band SAR time series, The 1st Joint PI Symposium of ALOS Data Nodes for ALOS Science Program, Kyoto, Japan. 19-23 Nov. 2007.
3 Bindlish, R. and A.P. Barros. 2001. Parameterization of vegetation backscatter in radar-based soil moisture estimation. Remote Sens. Environ. 76:130-137.   DOI   ScienceOn
4 Bouvet, A. and T. Le Toan. 2011. Use of ENVISAT/ASAR wide-swath data for timely rice fields mapping in the Mekong River Delta. Remote Sens. Environ. 115:1090-1101.   DOI
5 Chen, C. and H. Mcnairn. 2006. A neural network integrated approach for rice crop monitoring. Int. J. Remote Sens. 27:1367-1393.   DOI
6 Dobson, M.C. and F.T. Ulaby. 1986. Active microwave soil moisture research. IEEE Trans. Geosci. Remote Sens. 24:23-36.   DOI
7 Fehr, W.R. and C.E. Caviness. 1977. Stages of soybean development. Iowa Agric. Home Econ. Exp. Stn, IA, USA.
8 Fung, A.K. 1994. Microwave scattering and emission models and their applications. Artech House Inc., Norwood, MA, USA.
9 Hallikainen, T., F.T. Ulaby., M.C. Dobson., M.A. El-Rayes, and L. Wu. 1985. Microwave dielectric behavior of wet soil. Part-I: Empirical models and experimental observation. IEEE Trans. Geosci. Remote Sens. 23:25-34.   DOI
10 Jackson, T.J., A. Chang, and T.J. Schmugge. 1981. Aircraft active microwave measurements for estimating soil moisture. Photogramm. Eng. Rem. Sens. 47:801-805.
11 Kim, Y.H., S.Y. Hong., H.Y. Lee, and J.E. Lee. 2011. Monitoring soybean growth using L, C, and X-bands automatic radar scatterometer measurement. Korean J. Remote Sens. 27(2):191-201.   과학기술학회마을   DOI
12 Kurosu, T., M. Fujita, and K. Chiba. 1995. Monitoring of rice crop growth from space using the ERS-1 C-band SAR. IEEE Trans. Geosci. Remote Sens. 33(4):1092-1096.   DOI
13 Le Toan, T., H. Laur., E. Mougin, and A. Lopes. 1989. Multi-temporal and dual-polarization observations of agricultural vegetation covers by X-band SAR images. IEEE Trans. Geosci. Remote Sens. 27(6):709-718.   DOI
14 Macelloni, G., S. Paloscia., P. Pampaloni., F. Mariliani, and M. Gai. 2001. The relationship between the backscattering coefficient and the biomass of narrow and broad leaf crops. IEEE Trans. Geosci. Remote Sens. 39:873-884.   DOI   ScienceOn
15 Prasad, R. 2009. Retrieval of crop variables with field-based X-band microwave remote sensing of ladyfinger. Advanced in space research. 43:1356-1363.   DOI
16 Maity, S., C. Patnaik, and S. Panigraphy. 2004. Analysis of temporal backscattering of cotton crops using a semiempirical model. IEEE Trans. Geosci. Remote Sens. 42: 577-587.   DOI
17 Moran, M.S., C.D. Peters-Lidard., J.M Watts, and S. McElroy. 2004. Estimating soil moisture at the watershed scale with satellite-based. Can. J. Rem. Sens. 30:805-826.   DOI
18 Paris, J.F. 1986. The effect of leaf size on the microwave backscattering by corn. Remote Sens. Environ. 19:81-95.   DOI   ScienceOn
19 Prevot, L., I. Champion, and G. Guyot. 1993. Estimation surface soil moisture and leaf area index of a wheat canopy using a dual-frequency (C and X bands) scatterometer. Remote Sens. Environ. 46:331-339.   DOI   ScienceOn
20 Ram, V., M, Ali., M, Daily, J. Gabrynowicz, S. Narumalani, K. Nygard, W. Perrizo., S. Reichenbach., G.A. Seielstad, and W. White. 1995. Accessing Earth system science data and applications through high-bandwidth networks. IEEE Sel. Areas Commun. 13:793-805.   DOI
21 Ribbes, F. and T. Le Toan. 1999. Rice field mapping and monitoring with RADARSAT data. Int. J. Remote Sens. 20:745-765.   DOI
22 Schmugge, T. 1978. Remote sensing of surface soil moisture. J. Appl. Meteorol. Clim. 17:1549-1557.   DOI
23 Singh, D. 2006. Scatterometer performance with polarization discrimination ratio approach to retrieve crop soybean parameter at X-band. Int. J. Remote Sens. 27(19):4101- 4115.   DOI
24 Ulaby, F.T. and C. Elachi. 1990. Radar polarimetry for geoscience applications. Artech House Inc., Norwood, MA, USA.
25 Ulaby, F.T. 1974. Radar measurement of soil moisture content. IEEE Trans. Antennas Propag. 22:257-265.   DOI
26 Ulaby, F.T. M.K, Moore, and A.K. Fung. 1982, Microwave remote sensing. Active and Passive. Artech House Inc., Norwood, MA, USA.
27 Ulaby, F.T., C.T. Allen., G. Eger, and E.T. Kanemasu. 1984. Relating the microwave backscattering coefficient to leaf area index. Remote Sens. Environ. 14:113-133.   DOI   ScienceOn
28 Wagner, W., G. Lemoine., M. Borgeaud, and H. Rott. 1999. A study of vegetation cover effects on ERS scatterometer data. IEEE Trans. Geosci. Remote Sens. 37:938-948.   DOI
29 Xiao, X., S. Boles., S. Frolking., C. Li., J.Y. Babu, and W. Salas. 2005. Mapping paddy rice agriculture in south and southeast asia using multi-temporal MODIS images. Remote Sens. Environ. 100:95-113.