Soil Moisture Retrieval From SMAP: A Validation and Error Analysis Study Using Ground-Based Observations Over the Little Washita Watershed
The newest soil moisture-dedicated satellite, the Soil Moisture Active Passive (SMAP) mission, provides global maps of soil moisture using concurrent L-band radar and radiometer acquisitions. To support the ongoing validation activities of SMAP soil moisture products, in this paper, we examined the...
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| Published in: | IEEE transactions on geoscience and remote sensing Vol. 56; no. 3; pp. 1394 - 1408 |
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01.03.2018
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| ISSN: | 0196-2892, 1558-0644 |
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| Abstract | The newest soil moisture-dedicated satellite, the Soil Moisture Active Passive (SMAP) mission, provides global maps of soil moisture using concurrent L-band radar and radiometer acquisitions. To support the ongoing validation activities of SMAP soil moisture products, in this paper, we examined the retrieval accuracy of four SMAP soil moisture products by using well-calibrated and dense in situ measurements from the Little Washita Watershed network, one of the SMAP core validation sites with intensive ground sampling. The four SMAP products include the active (3 km), passive (36 km), active-passive (9 km), and the enhanced passive product which is a newly released soil moisture data set with a grid resolution of 9 km. Efforts on identifying the possible error sources of these products were also made for the purpose of improving the SMAP soil moisture algorithms. The results show that the passive and active-passive products can well capture the temporal dynamic of ground soil moisture with overall unbiased root-mean-square error (ubRMSE) values of 0.032 and <inline-formula> <tex-math notation="LaTeX">0.041~\text {m}^{3}\cdot ~\text {m}^{-3} </tex-math></inline-formula>, respectively, which generally meet their mission requirement of <inline-formula> <tex-math notation="LaTeX">0.04~\text {m}^{3}\cdot ~\text {m}^{-3} </tex-math></inline-formula>. In contrast, some irregular fluctuations exist in the active product, leading to an overall wet bias, which makes its accuracy a little poorer than its expected retrieval accuracy of <inline-formula> <tex-math notation="LaTeX">0.06~\text {m}^{3}\cdot ~\text {m}^{-3} </tex-math></inline-formula>. The new enhanced passive product shows the lowest ubRMSE value of <inline-formula> <tex-math notation="LaTeX">0.026 ~\text {m}^{3}\cdot ~\text {m}^{-3} </tex-math></inline-formula> though it underestimates in situ measurements with a bias of <inline-formula> <tex-math notation="LaTeX">0.059 ~\text {m}^{3}\cdot ~\text {m}^{-3} </tex-math></inline-formula>, revealing its great potential to substitute the active-passive product to provide global soil moisture measurements at a medium resolution of 9 km. The underestimation of SMAP surface temperature data may be one of the reasons that contribute to the dry bias of SMAP passive, active-passive, and enhanced passive products. The microwave polarization difference index and HV-polarized backscatter show good response to in situ soil moisture and may be considered in SMAP algorithms to further improve the accuracy of soil moisture retrievals. We expect that our findings can be fed back to improve the SMAP soil moisture algorithms and thus promote the application of SMAP soil moisture products in terrestrial water, energy, and carbon cycles. |
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| AbstractList | The newest soil moisture-dedicated satellite, the Soil Moisture Active Passive (SMAP) mission, provides global maps of soil moisture using concurrent L-band radar and radiometer acquisitions. To support the ongoing validation activities of SMAP soil moisture products, in this paper, we examined the retrieval accuracy of four SMAP soil moisture products by using well-calibrated and dense in situ measurements from the Little Washita Watershed network, one of the SMAP core validation sites with intensive ground sampling. The four SMAP products include the active (3 km), passive (36 km), active-passive (9 km), and the enhanced passive product which is a newly released soil moisture data set with a grid resolution of 9 km. Efforts on identifying the possible error sources of these products were also made for the purpose of improving the SMAP soil moisture algorithms. The results show that the passive and active-passive products can well capture the temporal dynamic of ground soil moisture with overall unbiased root-mean-square error (ubRMSE) values of 0.032 and <inline-formula> <tex-math notation="LaTeX">0.041~\text {m}^{3}\cdot ~\text {m}^{-3} </tex-math></inline-formula>, respectively, which generally meet their mission requirement of <inline-formula> <tex-math notation="LaTeX">0.04~\text {m}^{3}\cdot ~\text {m}^{-3} </tex-math></inline-formula>. In contrast, some irregular fluctuations exist in the active product, leading to an overall wet bias, which makes its accuracy a little poorer than its expected retrieval accuracy of <inline-formula> <tex-math notation="LaTeX">0.06~\text {m}^{3}\cdot ~\text {m}^{-3} </tex-math></inline-formula>. The new enhanced passive product shows the lowest ubRMSE value of <inline-formula> <tex-math notation="LaTeX">0.026 ~\text {m}^{3}\cdot ~\text {m}^{-3} </tex-math></inline-formula> though it underestimates in situ measurements with a bias of <inline-formula> <tex-math notation="LaTeX">0.059 ~\text {m}^{3}\cdot ~\text {m}^{-3} </tex-math></inline-formula>, revealing its great potential to substitute the active-passive product to provide global soil moisture measurements at a medium resolution of 9 km. The underestimation of SMAP surface temperature data may be one of the reasons that contribute to the dry bias of SMAP passive, active-passive, and enhanced passive products. The microwave polarization difference index and HV-polarized backscatter show good response to in situ soil moisture and may be considered in SMAP algorithms to further improve the accuracy of soil moisture retrievals. We expect that our findings can be fed back to improve the SMAP soil moisture algorithms and thus promote the application of SMAP soil moisture products in terrestrial water, energy, and carbon cycles. The newest soil moisture-dedicated satellite, the Soil Moisture Active Passive (SMAP) mission, provides global maps of soil moisture using concurrent L-band radar and radiometer acquisitions. To support the ongoing validation activities of SMAP soil moisture products, in this paper, we examined the retrieval accuracy of four SMAP soil moisture products by using well-calibrated and dense in situ measurements from the Little Washita Watershed network, one of the SMAP core validation sites with intensive ground sampling. The four SMAP products include the active (3 km), passive (36 km), active-passive (9 km), and the enhanced passive product which is a newly released soil moisture data set with a grid resolution of 9 km. Efforts on identifying the possible error sources of these products were also made for the purpose of improving the SMAP soil moisture algorithms. The results show that the passive and active-passive products can well capture the temporal dynamic of ground soil moisture with overall unbiased root-mean-square error (ubRMSE) values of 0.032 and 0.041 m3· m-3, respectively, which generally meet their mission requirement of 0.04 m3· m-3. In contrast, some irregular fluctuations exist in the active product, leading to an overall wet bias, which makes its accuracy a little poorer than its expected retrieval accuracy of 0.06 m3· m-3. The new enhanced passive product shows the lowest ubRMSE value of 0.026 m3 · m-3 though it underestimates in situ measurements with a bias of 0.059 m3 · m-3, revealing its great potential to substitute the active-passive product to provide global soil moisture measurements at a medium resolution of 9 km. The underestimation of SMAP surface temperature data may be one of the reasons that contribute to the dry bias of SMAP passive, active-passive, and enhanced passive products. The microwave polarization difference index and HV-polarized backscatter show good response to in situ soil moisture and may be considered in SMAP algorithms to further improve the accuracy of soil moisture retrievals. We expect that our findings can be fed back to improve the SMAP soil moisture algorithms and thus promote the application of SMAP soil moisture products in terrestrial water, energy, and carbon cycles. |
| Author | Li, Zhen Cui, Chenyang Xu, Jia Chen, Quan Chen, Kun-Shan Zeng, Jiangyuan Bai, Xiaojing |
| Author_xml | – sequence: 1 givenname: Quan orcidid: 0000-0002-6691-2235 surname: Chen fullname: Chen, Quan organization: Airborne Remote Sensing Center, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China – sequence: 2 givenname: Jiangyuan orcidid: 0000-0002-5039-6774 surname: Zeng fullname: Zeng, Jiangyuan email: zengjy@radi.ac.cn organization: State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences and Beijing Normal University, Beijing, China – sequence: 3 givenname: Chenyang surname: Cui fullname: Cui, Chenyang organization: School of Earth Sciences and Engineering, Hohai University, Nanjing, China – sequence: 4 givenname: Zhen orcidid: 0000-0003-3491-0697 surname: Li fullname: Li, Zhen organization: Airborne Remote Sensing Center, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China – sequence: 5 givenname: Kun-Shan orcidid: 0000-0001-7698-9861 surname: Chen fullname: Chen, Kun-Shan organization: State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences and Beijing Normal University, Beijing, China – sequence: 6 givenname: Xiaojing surname: Bai fullname: Bai, Xiaojing organization: College of Hydrometeorology, Nanjing University of Information Science and Technology, Nanjing, China – sequence: 7 givenname: Jia surname: Xu fullname: Xu, Jia organization: School of Earth Sciences and Engineering, Hohai University, Nanjing, China |
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| SubjectTerms | Accuracy Active microwave Algorithms Backscattering Bias Carbon cycle Data processing Error analysis Ground-based observation In situ measurement Microwave radiometry Moisture measurement passive microwave Products Radar Radiometers Resolution Retrieval Satellites Soil Soil dynamics Soil improvement Soil measurements Soil moisture Soil Moisture Active Passive (SMAP) Surface temperature Temperature data Temperature measurement validation Watersheds |
| Title | Soil Moisture Retrieval From SMAP: A Validation and Error Analysis Study Using Ground-Based Observations Over the Little Washita Watershed |
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