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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.


Disregarded SMOS brightness temperature observations because of suspected RFI, averaged over the Maqu (top) and the Twente (bottom) region and expressed as a percentage of the total number of SMOS observations.
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f11-sensors-12-09965: Disregarded SMOS brightness temperature observations because of suspected RFI, averaged over the Maqu (top) and the Twente (bottom) region and expressed as a percentage of the total number of SMOS observations.

Mentions: Several SMOS observations were disregarded in the soil moisture retrieval process. However, in particular for those dates when a large number of SMOS data was suspected to have been affected by RFI, one cannot exclude that RFI might also have been present in the remaining data used for the retrieval. As the RFI caused a bias in the measured brightness temperature, consequently the retrieved soil moisture might be affected by a bias as well. Most of the time, when the brightness temperature bias due to RFI is positive, then the corresponding bias in the soil moisture is negative. This could be one of the reasons for the dry bias observed in the SMOS soil moisture products. Figure 11 shows the number of disregarded SMOS L1c data per node because of suspected RFI, averaged over the Maqu and the Twente region, and expressed as a percentage over the total number of brightness temperature observations (obtained as described in Section 3). Only the nodes where soil moisture was retrieved were considered for this plot.


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

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

Disregarded SMOS brightness temperature observations because of suspected RFI, averaged over the Maqu (top) and the Twente (bottom) region and expressed as a percentage of the total number of SMOS observations.
© Copyright Policy
Related In: Results  -  Collection

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

f11-sensors-12-09965: Disregarded SMOS brightness temperature observations because of suspected RFI, averaged over the Maqu (top) and the Twente (bottom) region and expressed as a percentage of the total number of SMOS observations.
Mentions: Several SMOS observations were disregarded in the soil moisture retrieval process. However, in particular for those dates when a large number of SMOS data was suspected to have been affected by RFI, one cannot exclude that RFI might also have been present in the remaining data used for the retrieval. As the RFI caused a bias in the measured brightness temperature, consequently the retrieved soil moisture might be affected by a bias as well. Most of the time, when the brightness temperature bias due to RFI is positive, then the corresponding bias in the soil moisture is negative. This could be one of the reasons for the dry bias observed in the SMOS soil moisture products. Figure 11 shows the number of disregarded SMOS L1c data per node because of suspected RFI, averaged over the Maqu and the Twente region, and expressed as a percentage over the total number of brightness temperature observations (obtained as described in Section 3). Only the nodes where soil moisture was retrieved were considered for this plot.

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.