A Spatially Consistent Downscaling Approach for SMOS Using an Adaptive Moving Window

The ESA's Soil Moisture and Ocean Salinity (SMOS, 2009–2017) is the first mission using L-band radiometry to monitor the Earth's global surface soil moisture (SM). After more than 7 years in orbit, many studies have contributed to improving the quality and applicability of SMOS-derived SM maps. In this research, a novel downscaling algorithm is proposed for retrieving high resolution (1 km) SM. This model is an extension of the “universal triangle” technique, and also introduces the concept of adaptive moving window. Its inputs are the low resolution SMOS BEC L3 SM and the brightness temperatures at vertical and horizontal polarizations (SMOS L1C), and the high resolution NDVI and LST from optically-based sensors. The proposed method allows obtaining high resolution SM maps worldwide, with no limitation in extension.

[1]  Dara Entekhabi,et al.  An Algorithm for Merging SMAP Radiometer and Radar Data for High-Resolution Soil-Moisture Retrieval , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[2]  Thomas J. Schmugge,et al.  An interpretation of methodologies for indirect measurement of soil water content , 1995 .

[3]  Manuel Martín-Neira,et al.  MIRAS Calibration and Performance: Results From the SMOS In-Orbit Commissioning Phase , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[4]  Adriano Camps,et al.  Improved Image Reconstruction Algorithms for Aperture Synthesis Radiometers , 2008, IEEE Trans. Geosci. Remote. Sens..

[5]  George P. Petropoulos,et al.  Satellite Soil Moisture Retrieval: Techniques and Applications , 2016 .

[6]  T. Schmugge,et al.  Vegetation effects on the microwave emission of soils , 1991 .

[7]  Adriano Camps,et al.  Multi-Temporal Evaluation of Soil Moisture and Land Surface Temperature Dynamics Using in Situ and Satellite Observations , 2016, Remote. Sens..

[8]  Yann Kerr,et al.  A combined modeling and multispectral/multiresolution remote sensing approach for disaggregation of surface soil moisture: application to SMOS configuration , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[9]  Ahmad Al Bitar,et al.  Self-calibrated evaporation-based disaggregation of SMOS soil moisture: An evaluation study at 3 km and 100 m resolution in Catalunya, Spain , 2013 .

[10]  José Martínez-Fernández,et al.  Validation of the SMOS L2 Soil Moisture Data in the REMEDHUS Network (Spain) , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[11]  Niko E. C. Verhoest,et al.  A review of spatial downscaling of satellite remotely sensed soil moisture , 2017 .

[12]  A. Al Bitar,et al.  Overview of SMOS performance in terms of global soil moisture monitoring after six years in operation , 2016 .

[13]  Adriano Camps,et al.  A Downscaling Approach for SMOS Land Observations: Evaluation of High-Resolution Soil Moisture Maps Over the Iberian Peninsula , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[14]  T. Schmugge,et al.  Passive microwave remote sensing system for soil moisture: some supporting research , 1989 .

[15]  Gregory Duveiller,et al.  Spatially downscaling sun-induced chlorophyll fluorescence leads to an improved temporal correlation with gross primary productivity , 2016 .

[16]  Kelly K. Caylor,et al.  Validation of SMAP surface soil moisture products with core validation sites , 2017, Remote Sensing of Environment.

[17]  T. Carlson,et al.  Thermal remote sensing of surface soil water content with partial vegetation cover for incorporation into climate models , 1995 .

[18]  Jiancheng Shi,et al.  Tests of the SMAP Combined Radar and Radiometer Algorithm Using Airborne Field Campaign Observations and Simulated Data , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[19]  Adriano Camps,et al.  A Change Detection Algorithm for Retrieving High-Resolution Soil Moisture From SMAP Radar and Radiometer Observations , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[20]  George P. Petropoulos,et al.  Towards improved spatio-temporal resolution soil moisture retrievals from the synergy of SMOS and MSG SEVIRI spaceborne observations , 2016 .

[21]  Yann Kerr,et al.  A disaggregation scheme for soil moisture based on topography and soil depth , 2003 .

[22]  Adriano Camps,et al.  Impact of day/night time land surface temperature in soil moisture disaggregation algorithms , 2016 .

[23]  Wade T. Crow,et al.  Performance Metrics for Soil Moisture Retrievals and Application Requirements , 2009 .

[24]  Yann Kerr,et al.  Downscaling SMOS-Derived Soil Moisture Using MODIS Visible/Infrared Data , 2011, IEEE Transactions on Geoscience and Remote Sensing.