Soil Moisture Retrieval Quantitatively with Remotely Sensed Data and Its Crucial Factors Analysis

DOI: 10.4236/jwarp.2009.16053   PDF   HTML   XML   5,380 Downloads   9,305 Views   Citations


The Ts/NDVI method was adopted to retrieve soil moisture with multi-temporal and multi-sensor remotely sensed data f ETM+ and ASTER in study area. The retrieved soil moisture maps were consistent with the soil type and vegetation, which were also the two main factors determining the distribution of soil moisture.

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J. JIAN, P. PAN, Y. CHEN and W. YANG, "Soil Moisture Retrieval Quantitatively with Remotely Sensed Data and Its Crucial Factors Analysis," Journal of Water Resource and Protection, Vol. 1 No. 6, 2009, pp. 439-447. doi: 10.4236/jwarp.2009.16053.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] R. W. A. Hutjes, P. Kabat, et al., “Biospheric aspects of the hydrological cycle,” Journal of Hydrology, Vol. 212–213, pp. 1–21, 1998.
[2] Y. Gao and C. Wang, “Biospheric aspects of hydrological cycle: BAHC plan and its research progress,” Progress in Geography, Vol. 19, pp. 97–103, 2000.
[3] D. Entekhabi, H. Nakamurai, and E. G. Njoku, “Solving the inverse problem for soil moisture and temperature profiles by sequential assimilation of multifrequeney re-motely sensed observations,” IEEE Transactions on Geoscience and Remote Sensing, Vol. 32, pp. 438–448, 1994.
[4] IGPB, WCRD and IHDP, “Abstract volume of challenge of a changing earth,” in Proceedings Global Change Opening Science Conference, Amsterdam, Netherland, pp. 10 13, July, 2001.
[5] D. Gerten, S. Schaphoff, U. Haberlandt, W. Lucht, and S. Sitch, “Terrestrial vegetation and water balance-hydrological evaluation of a dynamic global vegetation mode,” Journal of Hydrology, Vol. 286, pp. 249–270, 2004.
[6] N. A. Brunsell, “Characterization of land-surface precipita-tion feedback regimes with remote sensing,” Remote Sensing of Environment, Vol. 112, pp. 200–211, 2006.
[7] R. H. French, J. J. Miller, C. Dettling, and J. R. Carr, “Use of remotely sensed data to estimate the flow of wa-ter to a playa lake,” Journal of Hydrology, Vol. 325, pp. 67–81, 2006.
[8] M. S. Feldman, T. Howard, E. McDonald-Buller, G. Mullins, D. T. Allen, A. Webb, and Y. Kimura, “Appli-cations of satellite remote sensing data for estimating dry deposition in eastern Texas,” Atmospheric Environment, Vol. 44, pp. 7562–7576, 2007.
[9] E. García-Cuesta, I. M. Galván, and A. J. de Castro, “Multilayer perceptron as inverse model in a ground- based remote sensing temperature retrieval problem,” Engineering Applications of Artificial Intelligence, Vol. 21, pp. 26–34, 2008.
[10] A. Holsten, T. Vetter, K. Vohland, V. Krysanova, “Im-pact of climate change on soil moisture dynamics in Brandenburg with a focus on nature conservation areas,” Ecological Modelling, Vol. 220, pp. 2076–2087, 2009.
[11] K. Y. Li, M. T. Coe, N. Ramankutty, and R. D. Jong, “Modeling the hydrological impact of land-use change in West Africa,” Journal of Hydrology, Vol. 337, pp. 258– 268, 2007.
[12] J. Liu, E. Pattey, M. C. Nolin, J. R. Miller, and O. Ka, “Mapping within-field soil drainage using remote sens-ing,” DEM and apparent soil electrical conductivity. Ge-oderma, Vol. 143, pp.261–272, 2008.
[13] Y. Liu, W. Yang, and X. X. Wang, “Development of a SWAT extension module to simulate riparian wetland hydrologic processes at a watershed scale,” Hydrological Processes, Vol. 22, pp. 2901–2915, 2008.
[14] A. Loew, “Impact of surface heterogeneity on surface soil moisture retrievals from passive microwave data at the regional scale: The Upper Danube case,” Remote Sensing of Environment, Vol. 112, pp. 231–248, 2008.
[15] M. F. McCabe, E. F. Wood, R. Wójcik, M. Pan, J. Shef-field, H. Gao, and H. Su, “Hydrological consistency using multi-sensor remote sensing data for water and energy cycle studies,” Remote Sensing of Environment, Vol. 112, pp. 430–444, 2008.
[16] W. N. Yang, J. Jian, Y. X. Li, X. N. Wan, L. Peng, H. H. Liu, H. Y. Shao, X. A. Dai, T. Zeng, and X. M. Wu, “Remote sensing inversion of eco-water resource quantity in international workshop on earth observation and re-mote sensing applications,” 29 June-2 July 2008, Beijing, China(IEEE), pp. 1–6, 2008.
[17] J. Jian, “Quantitative investigation of eco-water with remote sensing in the upper of Minjiang river,” Doctoral thesis, Chengdu University of Technology, China, 2006.

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