A Method for Downscaling FengYun-3B Soil Moisture Based on Apparent Thermal Inertia

FengYun-3B (FY-3B) soil moisture product, retrieved from passive microwave brightness temperature data based on the Qp model, has rarely been applied at the catchment and region scale. One of the reasons for this is its coarse spatial resolution (25-km). The study in this paper presented a new method to obtain a high spatial resolution soil moisture product by downscaling FY-3B soil moisture product from 25-km to 1-km spatial resolution using the theory of Apparent Thermal Inertia (ATI) under bare surface or sparse vegetation covered land surface. The relationship between soil moisture and ATI was first constructed, and the coefficients were obtained directly from 25-km FY-3B soil moisture product and ATI derived from MODIS data, which is different from previous studies often assuming the same set of coefficients applicable at different spatial resolutions. The method was applied to Naqu area on the Tibetan Plateau to obtain the downscaled 1-km resolution soil moisture product, the latter was validated using ground measurements collected from Soil Moisture/Temperature Monitoring Network on the central Tibetan Plateau (TP-STMNS) in 2012. The downscaled soil moisture showed promising results with a coefficient of determination R2 higher than 0.45 and a root mean-square error (RMSE) less than 0.11 m3/m3 when comparing with the ground measurements at 5 sites out of the 9 selected sites. It was found that the accuracy of downscaled soil moisture was largely influenced by the accuracy of the FY-3B soil moisture product. The proposed method could be applied for both bare soil surface and sparsely vegetated surface.

[1]  M. Minacapilli,et al.  High resolution remote estimation of soil surface water content by a thermal inertia approach , 2009 .

[2]  Wade T. Crow,et al.  Potential for downscaling soil moisture maps derived from spaceborne imaging radar data , 2000 .

[3]  Wout Verhoef,et al.  Mapping agroecological zones and time lag in vegetation growth by means of Fourier analysis of time series of NDVI images , 1993 .

[4]  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.

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

[6]  Li Fang,et al.  Enhancing Model Skill by Assimilating SMOPS Blended Soil Moisture Product into Noah Land Surface Model , 2015 .

[7]  K. Moffett,et al.  Remote Sens , 2015 .

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

[9]  Lazhu,et al.  A MULTISCALE SOIL MOISTURE AND FREEZE-THAW MONITORING NETWORK ON THE THIRD POLE , 2013 .

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

[11]  Bernard De Baets,et al.  The potential of multitemporal Aqua and Terra MODIS apparent thermal inertia as a soil moisture indicator , 2011, Int. J. Appl. Earth Obs. Geoinformation.

[12]  Thomas J. Jackson,et al.  Soil moisture retrieval from AMSR-E , 2003, IEEE Trans. Geosci. Remote. Sens..

[13]  W. Verstraeten,et al.  Soil moisture content retrieval based on apparent thermal inertia for Xinjiang province in China , 2012 .

[14]  Klaus Scipal,et al.  Temporal Stability of Soil Moisture and Radar Backscatter Observed by the Advanced Synthetic Aperture Radar (ASAR) , 2008, Sensors.

[15]  Yann Kerr,et al.  SMOS: analysis of perturbing effects over land surfaces , 2003, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477).

[16]  T. Schmugge,et al.  Remote sensing in hydrology , 2002 .

[17]  J. C. Price On the analysis of thermal infrared imagery: The limited utility of apparent thermal inertia , 1985 .

[18]  Matthew P. McAllister,et al.  MODIS Data and Services at the National Snow and Ice Data Center (NSIDC) , 2010 .

[19]  N. Lu,et al.  Spatial upscaling of in-situ soil moisture measurements based on MODIS-derived apparent thermal inertia , 2013 .

[20]  Claudia Notarnicola,et al.  Application of the Apparent Thermal Inertia Concept for Soil Moisture Estimation in Agricultural Areas , 2013 .

[21]  Yong Xue,et al.  Soil moisture retrieval from MODIS data in Northern China Plain using thermal inertia model , 2007 .

[22]  W. Verhoef,et al.  Reconstructing cloudfree NDVI composites using Fourier analysis of time series , 2000 .

[23]  Jean-Pierre Wigneron,et al.  Physically Based Estimation of Bare-Surface Soil Moisture With the Passive Radiometers , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[24]  Wade T. Crow,et al.  Evaluating the Utility of Remotely Sensed Soil Moisture Retrievals for Operational Agricultural Drought Monitoring , 2010, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[25]  Li Jia,et al.  Retrieving High-Resolution Surface Soil Moisture by Downscaling AMSR-E Brightness Temperature Using MODIS LST and NDVI Data , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[26]  Yi Y. Liu,et al.  Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals , 2011 .

[27]  Jeffrey P. Walker,et al.  Towards deterministic downscaling of SMOS soil moisture using MODIS derived soil evaporative efficiency , 2008 .

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

[29]  W. Verstraeten,et al.  Soil moisture retrieval using thermal inertia, determined with visible and thermal spaceborne data, validated for European forests , 2006 .

[30]  Yong Xue,et al.  Advanced thermal inertia modelling , 1995 .

[31]  E. Njoku,et al.  Passive microwave remote sensing of soil moisture , 1996 .

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