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Spatial Downscaling of AMSR2 Soil Moisture Content using Soil Texture and Field Measurements
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 Title & Authors
Spatial Downscaling of AMSR2 Soil Moisture Content using Soil Texture and Field Measurements
Na, Sangil; Lee, Kyoungdo; Baek, Shinchul; Hong, Sukyoung;
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Soil moisture content is generally accepted as an important factor to understand the process of crop growth and is the basis of earth system models for analysis and prediction of the crop condition. To continuously monitor soil moisture changes at kilometer scale, it is demanded to create high resolution data from the current, several tens of kilometers. In this paper we described a downscaling method for Advanced Microwave Scanning Radiometer 2 (AMSR2) Soil Moisture Content (SMC) from 10 km to 30 m resolution using a soil texture and field measurements that have a high correlation with the SMC. As a result, the soil moisture variations of both data (before and after downscaling) were identical, and the Root Mean Square Error (RMSE) of SMC exhibited the low values. Also, time series analyses showed that three kinds of SMC data (field measurement, original AMSR2, and downscaled AMSR2) had very similar temporal variations. Our method can be applied to downscaling of other soil variables and can contribute to monitoring small-scale changes of soil moisture by providing high resolution data.
Soil moisture content;AMSR2;Downscaling;Soil texture;
 Cited by
Chauhan, N.S., S. Miller, and P. Ardanuy. 2003. Spaceborne soil moisture estimation at high resolution: a Microwaveoptical/IR synergistic approach, Int. J. Remote Sens. 24(22):4599-4622. crossref(new window)

Choi, M.H. and Y.M. Hur. 2012. A microwaveoptical/infrared disaggregation for improving spatial representation of soil moisture using AMSR-E and MODIS products, Remote Sens. Environ. 124:259-269. crossref(new window)

GCOM Data Providing Service Homepage :

Hur, Y.M. and M.H. Choi. 2011. Advanced Microwave Scanning Radiometer E soil moisture evaluation for Haenam flux monitoring network site, Korean J. Remote Sens. 27(2):131-140 (in Korean). crossref(new window)

Imaoka, K., M. Kachi, H. Fujii, H. Murakami, M. Hori, A. Ono, T. Igarashi, K. Nakagawa, T. Oki, Y. Honda, and H. Shimoda. 2010. Global Change Observation Mission (GCOM) for monitoring carbon, water cycles, and climate change, Proc. IEEE, 98(5):717-734. crossref(new window)

Jackson, T.J., M.H. Cosh, R. Bindlish, P.J. Starks, D.D. Bosch, M. Seyfried, D.C. Goodrich, M.S. Moran, and J. Du. 2010. Validation of Advanced Microwave Scanning Radiometer soil moisture products, IEEE Trans. Geosci. Remote Sens. 48(12):4256-4272. crossref(new window)

Kim, G.S. and J.P. Kim. 2011. Correlation analysis between soil moisture retrieved from satellite images and ground network measurements, J. Korean Associ. Geog. Information Studies, 14(2):69-81 (in Korean). crossref(new window)

Kim, M.J., G.S. Kim, and J.E. Yi. 2015. Bias correction of AMSR2 soil moisture data using ground observations, J. Korean Soc. Agric. Eng. 57(4):61-71 (in Korean).

Korean Soil Information System Homepage :

Oh, M.R., T.Y., Gu, Y.M. Kim, G.H. Ryu, M.J. Kim, H.J. Lee, S.M. Kim, H.J. Han, S.J. Park, A.R. Kim, J.S. Jo, and S.J. Shin. 2013. Research for the meteorological and earthquake observation technology and its application (II) - Development of satellite technologies to monitor global environment changes and to apply global precipitation measurement, National Institute of Meteorological Research, Korea Meteorological Administration, 29-42

Srivastava, P.K., D. Han, M.R. Ramirez, and T. Islam. 2013. Machine learning techniques for downscaling SMOS satellite soil moisture using MODIS land surface temperature for hydrological application, Water Resour. Manage. 27(8):3127-3144. crossref(new window)

Wagner, W., C. Pathe, M. Doubkova, D. Sabel, A. Bartsch, S. Hasenauer, G. Blöschl, K. Scipal, J. Martinez-Fernandez, and A. Low. 2008. Temporal stability of soil moisture and radar backscatter observed by the Advanced Synthetic Aperture Radar (ASAR), Sensors, 8(2):1174-1197. crossref(new window)

Wang, L., J. Wen, T. Zhang, Y. Tian, X. Shi, X. Wang, R. Liu, J. Zhang, and S. Lu. 2009. Surface soil moisture estimates from AMSR-E observations over an Arid area, Northwest China, Hydrol. Earth Syst. Sci. Discuss. 6:1055-1087. crossref(new window)

Ye, Q., L. Chai, L. Jiang, and S. Zhao. 2014. A Downscaling approach of phase transition water content using AMSR2 and MODIS products, In Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International:3323-3326.

You, C.S. 2007. Application of remote sensing to soil moisture research, Mag. Korea Water Resour. Assoc. 30(1):64-68 (in Korean).