Spatial Evaluation of Soil Moisture (SM), Land Surface Temperature (LST), and LST-Derived SM Indexes Dynamics during SMAPVEX12

Downscaling microwave soil moisture (SM) with optical/thermal remote sensing data has considerable application potential. Spatial correlations between SM and land surface temperature (LST) or LST-derived SM indexes (SMIs) are vital to the current optical/thermal and microwave fusion downscaling methods. In this study, the spatial correlations were evaluated at the same spatial scale using SMAPVEX12 SM data and MODIS day/night LST products. LST-derived SMIs was calculated using NLDAS-2 gridded meteorological data with conventional trapezoid and two-stage trapezoid models. Results indicated that (1) SM agrees better with daytime LST than the nighttime or the day-night differential LST; (2) the daytime LSTs on Aqua and Terra present very similar spatial agreement with SM and they have very similar performances as downscaling factors in simulating SM; (3) decoupling effect among SM, LST, and LST-derived SMIs occurs not only in very wet but also in very dry condition; and (4) the decoupling effect degrades the performance of LST as a downscaling factor. The future downscaling algorithms should consider net surface radiation and soil type to tackle the decoupling effect.

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

[2]  Yann Kerr,et al.  Soil moisture retrieval from space: the Soil Moisture and Ocean Salinity (SMOS) mission , 2001, IEEE Trans. Geosci. Remote. Sens..

[3]  Dawei Han,et al.  Machine Learning Techniques for Downscaling SMOS Satellite Soil Moisture Using MODIS Land Surface Temperature for Hydrological Application , 2013, Water Resources Management.

[4]  Yann Kerr,et al.  The SMOS Mission: New Tool for Monitoring Key Elements ofthe Global Water Cycle , 2010, Proceedings of the IEEE.

[5]  Simon Yueh,et al.  Passive active L- and S-band (PALS) microwave sensor for ocean salinity and soil moisture measurements , 2001, IEEE Trans. Geosci. Remote. Sens..

[6]  I. Sandholt,et al.  A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status , 2002 .

[7]  A. Colliandera,et al.  Development and assessment of the SMAP enhanced passive soil moisture product , 2017 .

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

[9]  G. Petropoulos,et al.  A review of Ts/VI remote sensing based methods for the retrieval of land surface energy fluxes and soil surface moisture , 2009 .

[10]  Terri S. Hogue,et al.  Improving Spatial Soil Moisture Representation Through Integration of AMSR-E and MODIS Products , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[11]  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 .

[12]  T. Jackson,et al.  Retrieving soil moisture for non-forested areas using PALS radiometer measurements in SMAPVEX12 field campaign , 2016 .

[13]  Hao Sun,et al.  Comparison of Three Theoretical Methods for Determining Dry and Wet Edges of the LST/FVC Space: Revisit of Method Physics , 2017, Remote. Sens..

[14]  J. Lhomme,et al.  A THEORETICAL BASIS FOR THE PRIESTLEY-TAYLOR COEFFICIENT , 1997 .

[15]  A. Al Bitar,et al.  An improved algorithm for disaggregating microwave-derived soil moisture based on red, near-infrared and thermal-infrared data , 2010 .

[16]  L. Jiang,et al.  An intercomparison of regional latent heat flux estimation using remote sensing data , 2003 .

[17]  J. D. Tarpley,et al.  Real‐time and retrospective forcing in the North American Land Data Assimilation System (NLDAS) project , 2003 .

[18]  Hao Sun,et al.  A Two-Source Model for Estimating Evaporative Fraction (TMEF) Coupling Priestley-Taylor Formula and Two-Stage Trapezoid , 2016, Remote. Sens..

[19]  Adriano Camps,et al.  A Spatially Consistent Downscaling Approach for SMOS Using an Adaptive Moving Window , 2018, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[20]  T. Carlson An Overview of the “Triangle Method” for Estimating Surface Evapotranspiration and Soil Moisture from Satellite Imagery , 2007, Sensors (Basel, Switzerland).

[21]  Jeffrey P. Walker,et al.  Upscaling sparse ground‐based soil moisture observations for the validation of coarse‐resolution satellite soil moisture products , 2012 .

[22]  V. Singh,et al.  A Two-source Trapezoid Model for Evapotranspiration (TTME) from satellite imagery , 2012 .

[23]  Ahmad Al Bitar,et al.  SMOS disaggregated soil moisture product at 1 km resolution: Processor overview and first validation results , 2016, Remote Sensing of Environment.

[24]  Peter R. J. North,et al.  New Vegetation Albedo Parameters and Global Fields of Soil Background Albedo Derived from MODIS for Use in a Climate Model , 2009 .

[25]  Alexander Loew,et al.  Evaluation of soil moisture downscaling using a simple thermal-based proxy – the REMEDHUS network (Spain) example , 2015 .

[26]  S. Seneviratne,et al.  Investigating soil moisture-climate interactions in a changing climate: A review , 2010 .

[27]  Jiancheng Shi,et al.  The Soil Moisture Active Passive (SMAP) Mission , 2010, Proceedings of the IEEE.

[28]  V. Caselles,et al.  Influence of soil water content on the thermal infrared emissivity of bare soils: Implication for land surface temperature determination , 2007 .

[29]  Marc B. Parlange,et al.  On the concept of equilibrium evaporation and the value of the Priestley-Taylor coefficient. , 1996 .

[30]  Zhanqing Li,et al.  Estimation of evaporative fraction from a combination of day and night land surface temperatures and NDVI: A new method to determine the Priestley-Taylor parameter , 2006 .

[31]  Eva Rubio,et al.  Thermal–infrared emissivities of natural surfaces: improvements on the experimental set-up and new measurements , 2003 .

[32]  Jie Wang,et al.  Spatial Downscaling of Satellite Soil Moisture Data Using a Vegetation Temperature Condition Index , 2016, IEEE Transactions on Geoscience and Remote Sensing.

[33]  Sun Xiaomin,et al.  An operational two-layer remote sensing model to estimate surface flux in regional scale: Physical background , 2005 .

[34]  Philippe Richaume,et al.  Disaggregation of SMOS Soil Moisture in Southeastern Australia , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[35]  S. Miller,et al.  Spaceborne soil moisture estimation at high resolution: a microwave-optical/IR synergistic approach , 2003 .

[36]  Sidharth Misra,et al.  Spatial Downscaling of SMAP Soil Moisture Using MODIS Land Surface Temperature and NDVI During SMAPVEX15 , 2017, IEEE Geoscience and Remote Sensing Letters.

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

[38]  Maosheng Zhao,et al.  Improvements to a MODIS global terrestrial evapotranspiration algorithm , 2011 .

[39]  George P. Petropoulos,et al.  Surface soil moisture retrievals from remote sensing: Current status, products & future trends , 2015 .

[40]  Kalifa Goita,et al.  The Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12): Prelaunch Calibration and Validation of the SMAP Soil Moisture Algorithms , 2015, IEEE Transactions on Geoscience and Remote Sensing.

[41]  T. Jackson,et al.  Long term analysis of PALS soil moisture campaign measurements for global soil moisture algorithm development , 2012 .

[42]  Hao Sun,et al.  Two-Stage Trapezoid: A New Interpretation of the Land Surface Temperature and Fractional Vegetation Coverage Space , 2016, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[43]  R. Knight,et al.  Soil Moisture Measurement for Ecological and Hydrological Watershed‐Scale Observatories: A Review , 2008 .

[44]  Xiang Zhao,et al.  A new agricultural drought monitoring index combining MODIS NDWI and day–night land surface temperatures: a case study in China , 2013 .

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

[46]  Kyle Knipper,et al.  Downscaling SMAP and SMOS soil moisture with moderate-resolution imaging spectroradiometer visible and infrared products over southern Arizona , 2017 .