Development of a soil moisture retrieval algorithm for spaceborne passive microwave radiometers and its application to AMSR-E and SSM/I

Lu, Hui; Koike, Takao; Ohta, Toshiro; Kuria, David Ndegwa; Tsutsui, Hiroyuki; Graf, Thomas; Fuji, Hideki; Tamagawa, Katsunori

doi:10.1109/igarss.2007.4423014

Cited by 20 publications

(22 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In the past two decades, various studies have demonstrated that soil moisture can be retrieved by passive satellite missions, such as the Soil Moisture and Ocean Salinity (SMOS) mission [1,2], the Soil Moisture Active/Passive (SMAP) mission [3], the Special Sensor Microwave/Imager (SSM/I) mission, the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E)and Advanced Microwave Scanning Radiometer 2 (AMSR2) mission [4][5][6][7][8]. Soil moisture data sets acquired from all of these passive missions are widely used.…”

Section: Introductionmentioning

confidence: 99%

Validation Analysis of SMAP and AMSR2 Soil Moisture Products over the United States Using Ground-Based Measurements

Zhang

Ping

et al. 2017

Remote Sensing

View full text Add to dashboard Cite

Soil moisture products acquired from passive satellite missions have been widely applied in environmental processes. A primary challenge for the use of soil moisture products from passive sensors is their reliability. It is crucial to evaluate the reliability of those products before they can be routinely used at a global scale. In this paper, we evaluated the Soil Moisture Active/Passive (SMAP) and the Advanced Microwave Scanning Radiometer (AMSR2) radiometer soil moisture products against in situ measurements collected from American networks with four statistics, including the mean difference (MD), the root mean squared difference (RMSD), the unbiased root mean square error (ubRMSE) and the correlation coefficient (R). The evaluation results of SMAP and AMSR2 soil moisture products were compared. Moreover, the triple collocation (TC) error model was used to assess the error among AMSR2, SMAP and in situ data. The monthly average and daily AMSR2 and SMAP soil moisture data were analyzed. Different spatial series, temporal series and combined spatial-temporal analysis were carried out. The results reveal that SMAP soil moisture retrievals are generally better than AMSR2 soil moisture data. The remotely sensed retrievals show the best agreement with in situ measurements over the central Great Plains and cultivated crops throughout the year. In particular, SMAP soil moisture data shows a stable pattern for capturing the spatial distribution of surface soil moisture. Further studies are required for better understanding the SMAP soil moisture product.

show abstract

Section: Introductionmentioning

confidence: 99%

Validation Analysis of SMAP and AMSR2 Soil Moisture Products over the United States Using Ground-Based Measurements

Zhang

Ping

et al. 2017

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…Considering soil as a volume scattering medium or accounting for inhomogeneous temperatures or wetness can be treated within DMRT and layered radiative transfer (Lu et al, 2009). Though promising, this approach has still been hardly explored.…”

Section: Limitations and Perspectivesmentioning

confidence: 99%

SMRT: an active–passive microwave radiative transfer model for snow with multiple microstructure and scattering formulations (v1.0)

Picard

Sandells²,

Löwe³

2018

Geosci. Model Dev.

View full text Add to dashboard Cite

Abstract. The Snow Microwave Radiative Transfer (SMRT) thermal emission and backscatter model was developed to determine uncertainties in forward modeling through intercomparison of different model ingredients. The model differs from established models by the high degree of flexibility in switching between different electromagnetic theories, representations of snow microstructure, and other modules involved in various calculation steps. SMRT v1.0 includes the dense media radiative transfer theory (DMRT), the improved Born approximation (IBA), and independent Rayleigh scatterers to compute the intrinsic electromagnetic properties of a snow layer. In the case of IBA, five different formulations of the autocorrelation function to describe the snow microstructure characteristics are available, including the sticky hard sphere model, for which close equivalence between the IBA and DMRT theories has been shown here. Validation is demonstrated against established theories and models. SMRT was used to identify that several former studies conducting simulations with in situ measured snow properties are now comparable and moreover appear to be quantitatively nearly equivalent. This study also proves that a third parameter is needed in addition to density and specific surface area to characterize the microstructure. The paper provides a comprehensive description of the mathematical basis of SMRT and its numerical implementation in Python. Modularity supports model extensions foreseen in future versions comprising other media (e.g., sea ice, frozen lakes), different scattering theories, rough surface models, or new microstructure models.

show abstract

“…Considering soil as a volume scattering medium or accounting for inhomogeneous temperatures or wetness can be treated 30 within DMRT and layered radiative transfer (Lu et al, 2009). Though promising, this approach is still hardly explored yet.…”

Section: Limitations and Perspectivesmentioning

confidence: 99%

SMRT: An active / passive microwave radiative transfer model for snow with multiple microstructure and scattering formulations (v1.0)

Picard

Sandells²,

Löwe³

2018

Preprint

View full text Add to dashboard Cite

Transfer theory (DMRT), the Improved Born Approximation (IBA) and independent Rayleigh scatterers to compute the intrin-5 sic electromagnetic properties of a snow layer. In the case of IBA, five different formulations of the autocorrelation function to describe the snow microstructure characteristics are available, including the sticky hard sphere model, for which close equivalence between IBA and DMRT theories has been shown here. Validation is demonstrated against established theories and models. SMRT was used to identify that several former studies conducting simulations with in-situ measured snow properties are now comparable and moreover appear to be quantitatively nearly equivalent. This study also proves that a third parameter 10 is needed in addition to density and specific surface area to characterize the microstructure. The paper provides a comprehensive description of the mathematical basis of SMRT and its numerical implementation in Python. Modularity supports model extensions foreseen in future versions comprising other media (e.g. sea-ice, frozen lakes), different scattering theories, rough surface models, or new microstructure models.

show abstract

Development of a soil moisture retrieval algorithm for spaceborne passive microwave radiometers and its application to AMSR-E and SSM/I

Cited by 20 publications

References 17 publications

Validation Analysis of SMAP and AMSR2 Soil Moisture Products over the United States Using Ground-Based Measurements

Validation Analysis of SMAP and AMSR2 Soil Moisture Products over the United States Using Ground-Based Measurements

SMRT: an active–passive microwave radiative transfer model for snow with multiple microstructure and scattering formulations (v1.0)

SMRT: An active / passive microwave radiative transfer model for snow with multiple microstructure and scattering formulations (v1.0)

Contact Info

Product

Resources

About