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Validation of SMOS soil moisture products over the Maqu and Twente regions.

Dente L, Su Z, Wen J - Sensors (Basel) (2012)

Bottom Line: However, the validation analysis resulted in determination coefficients of 0.55 and 0.51 over the Maqu and Twente region, respectively, for the ascending pass data, and of 0.24 and 0.41, respectively, for the descending pass data.Moreover, a systematic dry bias of the SMOS soil moisture was found of approximately 0.13 m(3)/m(3) for the Maqu region and 0.17 m(3)/m(3) for the Twente region for ascending pass data.Several factors might have affected the retrieval accuracy, such as the presence of Radio Frequency Interference (RFI), the use of inaccurate land cover information and the presence of frozen soils not correctly detected in winter.

View Article: PubMed Central - PubMed

Affiliation: Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Hengelosestraat 99, 7514AE Enschede, The Netherlands. dente@itc.nl

ABSTRACT
The validation of Soil Moisture and Ocean Salinity (SMOS) soil moisture products is a crucial step in the investigation of their inaccuracies and limitations, before planning further refinements of the retrieval algorithm. Therefore, this study intended to contribute to the validation of the SMOS soil moisture products, by comparing them with the data collected in situ in the Maqu (China) and Twente (The Netherlands) regions in 2010. The seasonal behavior of the SMOS soil moisture products is generally in agreement with the in situ measurements for both regions. However, the validation analysis resulted in determination coefficients of 0.55 and 0.51 over the Maqu and Twente region, respectively, for the ascending pass data, and of 0.24 and 0.41, respectively, for the descending pass data. Moreover, a systematic dry bias of the SMOS soil moisture was found of approximately 0.13 m(3)/m(3) for the Maqu region and 0.17 m(3)/m(3) for the Twente region for ascending pass data. Several factors might have affected the retrieval accuracy, such as the presence of Radio Frequency Interference (RFI), the use of inaccurate land cover information and the presence of frozen soils not correctly detected in winter. Improving the RFI filtering method and the quality of the retrieval algorithm inputs, such as land surface temperature and land cover, would certainly improve the accuracy of the retrieved soil moisture.

No MeSH data available.


SMOS soil moisture averaged over the Maqu (top) and the Twente (bottom) region as a function of in situ average soil moisture at the satellite acquisition time, for ascending passes (left) and for descending passes (right). Empty symbols indicate that for more than half of the area no SMOS products were generated, whereas filled symbols refer to a good coverage.
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f12-sensors-12-09965: SMOS soil moisture averaged over the Maqu (top) and the Twente (bottom) region as a function of in situ average soil moisture at the satellite acquisition time, for ascending passes (left) and for descending passes (right). Empty symbols indicate that for more than half of the area no SMOS products were generated, whereas filled symbols refer to a good coverage.

Mentions: In order to have a clearer view of the match between retrieved and measured soil moisture, the SMOS soil moisture spatial average was compared with the in situ measurements collected at the time of the satellite acquisitions, as shown in the scatter plots in Figure 12. Moreover, Table 1 reports the determination coefficient, R2, and the root mean square error, rmse, between the two time series. The analysis was done separately for ascending and descending data.


Validation of SMOS soil moisture products over the Maqu and Twente regions.

Dente L, Su Z, Wen J - Sensors (Basel) (2012)

SMOS soil moisture averaged over the Maqu (top) and the Twente (bottom) region as a function of in situ average soil moisture at the satellite acquisition time, for ascending passes (left) and for descending passes (right). Empty symbols indicate that for more than half of the area no SMOS products were generated, whereas filled symbols refer to a good coverage.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3472810&req=5

f12-sensors-12-09965: SMOS soil moisture averaged over the Maqu (top) and the Twente (bottom) region as a function of in situ average soil moisture at the satellite acquisition time, for ascending passes (left) and for descending passes (right). Empty symbols indicate that for more than half of the area no SMOS products were generated, whereas filled symbols refer to a good coverage.
Mentions: In order to have a clearer view of the match between retrieved and measured soil moisture, the SMOS soil moisture spatial average was compared with the in situ measurements collected at the time of the satellite acquisitions, as shown in the scatter plots in Figure 12. Moreover, Table 1 reports the determination coefficient, R2, and the root mean square error, rmse, between the two time series. The analysis was done separately for ascending and descending data.

Bottom Line: However, the validation analysis resulted in determination coefficients of 0.55 and 0.51 over the Maqu and Twente region, respectively, for the ascending pass data, and of 0.24 and 0.41, respectively, for the descending pass data.Moreover, a systematic dry bias of the SMOS soil moisture was found of approximately 0.13 m(3)/m(3) for the Maqu region and 0.17 m(3)/m(3) for the Twente region for ascending pass data.Several factors might have affected the retrieval accuracy, such as the presence of Radio Frequency Interference (RFI), the use of inaccurate land cover information and the presence of frozen soils not correctly detected in winter.

View Article: PubMed Central - PubMed

Affiliation: Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Hengelosestraat 99, 7514AE Enschede, The Netherlands. dente@itc.nl

ABSTRACT
The validation of Soil Moisture and Ocean Salinity (SMOS) soil moisture products is a crucial step in the investigation of their inaccuracies and limitations, before planning further refinements of the retrieval algorithm. Therefore, this study intended to contribute to the validation of the SMOS soil moisture products, by comparing them with the data collected in situ in the Maqu (China) and Twente (The Netherlands) regions in 2010. The seasonal behavior of the SMOS soil moisture products is generally in agreement with the in situ measurements for both regions. However, the validation analysis resulted in determination coefficients of 0.55 and 0.51 over the Maqu and Twente region, respectively, for the ascending pass data, and of 0.24 and 0.41, respectively, for the descending pass data. Moreover, a systematic dry bias of the SMOS soil moisture was found of approximately 0.13 m(3)/m(3) for the Maqu region and 0.17 m(3)/m(3) for the Twente region for ascending pass data. Several factors might have affected the retrieval accuracy, such as the presence of Radio Frequency Interference (RFI), the use of inaccurate land cover information and the presence of frozen soils not correctly detected in winter. Improving the RFI filtering method and the quality of the retrieval algorithm inputs, such as land surface temperature and land cover, would certainly improve the accuracy of the retrieved soil moisture.

No MeSH data available.