Estimation of improved resolution soil moisture in vegetated areas using passive AMSR-E data
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Microwave remote sensing provides a unique capability for soil parameter retrievals. Therefore, various soil parameters estimation models have been developed using brightness temperature (BT) measured by passive microwave sensors. Due to the low resolution of satellite microwave radiometer data, the main goal of this study is to develop a downscaling approach to improve the spatial resolution of soil moisture estimates with the use of higher resolution visible/infrared sensor data. Accordingly, after the soil parameters have been obtained using Simultaneous Land Parameters Retrieval Model algorithm, the downscaling method has been applied to the soil moisture estimations that have been validated against in situ soil moisture data. Advance Microwave Scanning Radiometer-EOS BT data in Soil Moisture Experiment 2003 region in the south and north of Oklahoma have been used to this end. Results illustrated that the soil moisture variability is effectively captured at 5 km spatial scales without a significant degradation of the accuracy.
KeywordsSoil moisture land surface parameters SLPRM AMSR-E downscaling MODIS
The authors thank the three anonymous reviewers for their comments, which have helped to improve this manuscript.
- Allen P B and Naney J W 1991 Hydrology of the Little Washita RiverWatershed. Oklahoma: Data and Analyses; USDA, ARS-90, Washington, DC, 74p.Google Scholar
- Chanzy A and Wigneron J P 2000 Microwave emission from soil and vegetation; In: COST action 712 final report: Radiative transfer models for microwave radiometry (ed.) Mätzler C, Brussels, Belgium: European Commission (EUR 19543 EN), pp. 89–103.Google Scholar
- Moradizadeh M and Saradjian M R 2016 The effect of roughness in simultaneously retrieval of land surface parameters. Phys. Chem. Earth. https://doi.org/10.1016/j.pce.2016.03.006.
- Moradizadeh M, Momeni M and Saradjian M 2017 Assessment of the relationship between land surface temperature (LST) and near surface water vapor in central part of Iran; J. Geogr. Environ. Plan. 28(3) Ser No. 67.Google Scholar
- Njoku E G 1995 Surface temperature estimation over land using satellite microwave radiometry; In: Passive microwave remote sensing of land-atmosphere interactions (eds) Choudhury B J, Kerr Y H, Njoku E G and Pampaloni P, VSP Publishing, Utrecht.Google Scholar
- Owe M, Van de Griend A A and Chang A T C 1992 Surface moisture and satellite microwave observations in semiarid southern Africa; Water Resour. Res. 28 829–839.Google Scholar
- Piles M, Camps A, Vall-llossera M, Sánchez N, Martínez-Fernández J, Monerris A, Baroncini-Turricchia G, Pérez-Gutiérrez C, Aguasca A, Acevo R and Bosch-Lluís X 2010 Soil moisture downscaling activities at the REMEDHUS Cal/Val site and its application to SMOS; Proc. 11th Spec. Meeting Microwave Radiometry Remote Sensing Environment 17–21.Google Scholar
- Schmugge T J 1985 Remote sensing of soil moisture; In: Hydrological forecasting (eds) Anderson M G and Burt T P, Wiley, New York.Google Scholar
- Singh G, Srivastava H S, Mesapam S and Patel P 2015b Analysis of monthly soil moisture variations derived from AMSR-E for the year 2010 over Indian subcontinent; Proc. Int. Conf. Sustainable Energy and Build Environment, pp. 539–545.Google Scholar
- Wigneron J P, Kerr Y H, Waldteufel P, Saleh K, Escorihuela M J, Richaume M J, Ferrazzoli P, de Rosnay P, Gurney R, Calvet J C, Grant J P, Guglielmetti M, Hornbuckle B, Mätzler C, Pellarin T and Schwank M 2007 L-band Microwave Emission of the Biosphere (L-MEB) Model: Description and calibration against experimental data sets over crop fields; Remote Sens. Environ. 107 639–655.CrossRefGoogle Scholar