Global retrieval of surface soil moisture using L-band SMAP SAR data and its validation

S. Kim; J. Johnson; Majid Moghaddam; Leung Tsang; J. Van Zyl; A. Colliander; S. Dunbar; T. Jackson; Sermsak Jaruwatanadilok; R. West; Aaron A Berg; T. Caldwell; M. Cosh; E. Lopez-Baeza; M. Thibeault; J. Walker; Dara Entekhabi; S. Yueh

Global retrieval of surface soil moisture using L-band SMAP SAR data and its validation

S. Kim, J. Johnson, Majid Moghaddam, Leung Tsang, J. Van Zyl, A. Colliander, S. Dunbar, T. Jackson, Sermsak Jaruwatanadilok, R. West, Aaron A Berg, T. Caldwell, M. Cosh, E. Lopez-Baeza, M. Thibeault, J. Walker, Dara Entekhabi, S. Yueh

Civil Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

1 Citation (Scopus)

Abstract

Surface soil moisture retrievals using radar observations have been challenging due to the strong effects by surfac roughness and vegetation scattering. Physically-based forward models for radar scattering are inverted using time-serie retrieval algorithm to systematically correct for the effect of the roughness and vegetation. The retrievals are performed for top 5-cm layer soil moisture at 3-km spatial resolution using the L-band radar data acquired by the Soil Moisture Activ Passive (SMAP) satellite globally every three days from mid-April to early July, 2015. These were assessed over 1 rigorously-chosen core validation sites covering a wide range of biomass types and amounts and soil conditions. The soi moisture retrieval performance had an accuracy of approaching the goal of 0.063 m3/m3 unbiased-RMSE (root mean squar error), a near zero bias, and a correlation of 0.56. The successful retrieval demonstrates that the physically-based retrieva method is capable of characterizing soil moisture over diverse conditions of soil moisture, surface roughness, and vegetatio on a global scale.

Original language	English
Title of host publication	Proceedings of the 11th European Conference on Synthetic Aperture Radar, EUSAR 2016
Subtitle of host publication	Hamburg, Germany; 6-9 June 2016
Place of Publication	Piscataway NJ USA
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	1118-1121
Number of pages	4
ISBN (Electronic)	9783800742288
Publication status	Published - 2016
Event	European Conference on Synthetic Aperture Radar (EUSAR) 2016 - Hamburg, Germany Duration: 6 Jun 2016 → 9 Jun 2016 Conference number: 11th https://ieeexplore.ieee.org/xpl/conhome/7559229/proceeding (Proceedings)

Conference

Conference	European Conference on Synthetic Aperture Radar (EUSAR) 2016
Abbreviated title	EUSAR 2016
Country/Territory	Germany
City	Hamburg
Period	6/06/16 → 9/06/16
Internet address	https://ieeexplore.ieee.org/xpl/conhome/7559229/proceeding (Proceedings)

Cite this

Kim, S., Johnson, J., Moghaddam, M., Tsang, L., Van Zyl, J., Colliander, A., Dunbar, S., Jackson, T., Jaruwatanadilok, S., West, R., Berg, A. A., Caldwell, T., Cosh, M., Lopez-Baeza, E., Thibeault, M., Walker, J., Entekhabi, D., & Yueh, S. (2016). Global retrieval of surface soil moisture using L-band SMAP SAR data and its validation. In Proceedings of the 11th European Conference on Synthetic Aperture Radar, EUSAR 2016: Hamburg, Germany; 6-9 June 2016 (pp. 1118-1121 ). Article 7559490 IEEE, Institute of Electrical and Electronics Engineers.

@inproceedings{b41f4ca6f0a54efd8bb258f14a5c3a28,

title = "Global retrieval of surface soil moisture using L-band SMAP SAR data and its validation",

abstract = "Surface soil moisture retrievals using radar observations have been challenging due to the strong effects by surfac roughness and vegetation scattering. Physically-based forward models for radar scattering are inverted using time-serie retrieval algorithm to systematically correct for the effect of the roughness and vegetation. The retrievals are performed for top 5-cm layer soil moisture at 3-km spatial resolution using the L-band radar data acquired by the Soil Moisture Activ Passive (SMAP) satellite globally every three days from mid-April to early July, 2015. These were assessed over 1 rigorously-chosen core validation sites covering a wide range of biomass types and amounts and soil conditions. The soi moisture retrieval performance had an accuracy of approaching the goal of 0.063 m3/m3 unbiased-RMSE (root mean squar error), a near zero bias, and a correlation of 0.56. The successful retrieval demonstrates that the physically-based retrieva method is capable of characterizing soil moisture over diverse conditions of soil moisture, surface roughness, and vegetatio on a global scale.",

author = "S. Kim and J. Johnson and Majid Moghaddam and Leung Tsang and {Van Zyl}, J. and A. Colliander and S. Dunbar and T. Jackson and Sermsak Jaruwatanadilok and R. West and Berg, {Aaron A} and T. Caldwell and M. Cosh and E. Lopez-Baeza and M. Thibeault and J. Walker and Dara Entekhabi and S. Yueh",

year = "2016",

language = "English",

pages = "1118--1121 ",

booktitle = "Proceedings of the 11th European Conference on Synthetic Aperture Radar, EUSAR 2016",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States of America",

note = "European Conference on Synthetic Aperture Radar (EUSAR) 2016, EUSAR 2016 ; Conference date: 06-06-2016 Through 09-06-2016",

url = "https://ieeexplore.ieee.org/xpl/conhome/7559229/proceeding",

}

Kim, S, Johnson, J, Moghaddam, M, Tsang, L, Van Zyl, J, Colliander, A, Dunbar, S, Jackson, T, Jaruwatanadilok, S, West, R, Berg, AA, Caldwell, T, Cosh, M, Lopez-Baeza, E, Thibeault, M, Walker, J, Entekhabi, D & Yueh, S 2016, Global retrieval of surface soil moisture using L-band SMAP SAR data and its validation. in Proceedings of the 11th European Conference on Synthetic Aperture Radar, EUSAR 2016: Hamburg, Germany; 6-9 June 2016., 7559490, IEEE, Institute of Electrical and Electronics Engineers, Piscataway NJ USA, pp. 1118-1121 , European Conference on Synthetic Aperture Radar (EUSAR) 2016, Hamburg, Hamburg, Germany, 6/06/16.

Global retrieval of surface soil moisture using L-band SMAP SAR data and its validation. / Kim, S.; Johnson, J.; Moghaddam, Majid et al.
Proceedings of the 11th European Conference on Synthetic Aperture Radar, EUSAR 2016: Hamburg, Germany; 6-9 June 2016. Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, 2016. p. 1118-1121 7559490.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

TY - GEN

T1 - Global retrieval of surface soil moisture using L-band SMAP SAR data and its validation

AU - Kim, S.

AU - Johnson, J.

AU - Moghaddam, Majid

AU - Tsang, Leung

AU - Van Zyl, J.

AU - Colliander, A.

AU - Dunbar, S.

AU - Jackson, T.

AU - Jaruwatanadilok, Sermsak

AU - West, R.

AU - Berg, Aaron A

AU - Caldwell, T.

AU - Cosh, M.

AU - Lopez-Baeza, E.

AU - Thibeault, M.

AU - Walker, J.

AU - Entekhabi, Dara

AU - Yueh, S.

N1 - Conference code: 11th

PY - 2016

Y1 - 2016

N2 - Surface soil moisture retrievals using radar observations have been challenging due to the strong effects by surfac roughness and vegetation scattering. Physically-based forward models for radar scattering are inverted using time-serie retrieval algorithm to systematically correct for the effect of the roughness and vegetation. The retrievals are performed for top 5-cm layer soil moisture at 3-km spatial resolution using the L-band radar data acquired by the Soil Moisture Activ Passive (SMAP) satellite globally every three days from mid-April to early July, 2015. These were assessed over 1 rigorously-chosen core validation sites covering a wide range of biomass types and amounts and soil conditions. The soi moisture retrieval performance had an accuracy of approaching the goal of 0.063 m3/m3 unbiased-RMSE (root mean squar error), a near zero bias, and a correlation of 0.56. The successful retrieval demonstrates that the physically-based retrieva method is capable of characterizing soil moisture over diverse conditions of soil moisture, surface roughness, and vegetatio on a global scale.

AB - Surface soil moisture retrievals using radar observations have been challenging due to the strong effects by surfac roughness and vegetation scattering. Physically-based forward models for radar scattering are inverted using time-serie retrieval algorithm to systematically correct for the effect of the roughness and vegetation. The retrievals are performed for top 5-cm layer soil moisture at 3-km spatial resolution using the L-band radar data acquired by the Soil Moisture Activ Passive (SMAP) satellite globally every three days from mid-April to early July, 2015. These were assessed over 1 rigorously-chosen core validation sites covering a wide range of biomass types and amounts and soil conditions. The soi moisture retrieval performance had an accuracy of approaching the goal of 0.063 m3/m3 unbiased-RMSE (root mean squar error), a near zero bias, and a correlation of 0.56. The successful retrieval demonstrates that the physically-based retrieva method is capable of characterizing soil moisture over diverse conditions of soil moisture, surface roughness, and vegetatio on a global scale.

UR - http://www.scopus.com/inward/record.url?scp=85000885292&partnerID=8YFLogxK

M3 - Conference Paper

AN - SCOPUS:85000885292

SP - 1118

EP - 1121

BT - Proceedings of the 11th European Conference on Synthetic Aperture Radar, EUSAR 2016

PB - IEEE, Institute of Electrical and Electronics Engineers

CY - Piscataway NJ USA

T2 - European Conference on Synthetic Aperture Radar (EUSAR) 2016

Y2 - 6 June 2016 through 9 June 2016

ER -

Kim S, Johnson J, Moghaddam M, Tsang L, Van Zyl J, Colliander A et al. Global retrieval of surface soil moisture using L-band SMAP SAR data and its validation. In Proceedings of the 11th European Conference on Synthetic Aperture Radar, EUSAR 2016: Hamburg, Germany; 6-9 June 2016. Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers. 2016. p. 1118-1121 . 7559490

Global retrieval of surface soil moisture using L-band SMAP SAR data and its validation

Abstract

Conference

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Surface soil moisture retrieval using L-band SMAP SAR data and its validation

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