Improving SMOS soil moisture algorithm performance in forested areas with multisensor SAR data

Jaakko Seppänen; Jaan Praks; Oleg Antropov

doi:10.1109/IGARSS.2016.7729428

Improving SMOS soil moisture algorithm performance in forested areas with multisensor SAR data

Jaakko Seppänen, Jaan Praks, Oleg Antropov

Not published at VTT

Aalto University

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

Abstract

In this paper, we propose a new approach for improving boreal forest soil moisture estimation using L-band microwave radiometer. The effect is achieved by introducing improved description of forest canopy contribution from multisensor SAR measurements. Spaceborne L-band radiometer is a valuable tool for providing soil moisture estimates globally. Unfortunately, complex vegetation layer, such as forest, can hamper the accuracy of soil moisture retrieval leading to rather poor results particularly over boreal forest areas. Currently, the L-band Microwave Emission of the Biosphere (L-MEB) model adopted in the Soil Moisture and Ocean Salinity (SMOS) Level 2 Soil Moisture algorithm, uses Leaf Area Index (LAI) in order to to account for forest canopy contribution to total emission. However, it can argued that LAI presents poorly the actual structure of the coniferous forest. The LAI is calibrated to represent only the leaves, but at L-band, the main contribution to emission and attenuation is due to branches, while trunks and leaves have smaller effects. Here, we tested several combinations of spaceborne SAR data as a substitute of LA! in temperature brightness models for soil moisture retrieval. Particularly when L-band ALOS PALSAR stripmap data were used, the agreement between modelled and measured TB has improved from 0.46 to 0.55 in the L-MEB model.

Original language	English
Title of host publication	2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016
Publisher	IEEE Institute of Electrical and Electronic Engineers
Pages	1675-1678
ISBN (Electronic)	978-1-5090-3332-4, 978-1-5090-3331-7
ISBN (Print)	978-1-5090-3333-1
DOIs	https://doi.org/10.1109/IGARSS.2016.7729428
Publication status	Published - 1 Nov 2016
MoE publication type	A4 Article in a conference publication
Event	36th IEEE International Geoscience and Remote Sensing Symposium: Advancing the understanding of our living planet - Beijing, China Duration: 10 Jul 2016 → 15 Jul 2016 Conference number: 36

Publication series

Series	IEEE International Geoscience and Remote Sensing Symposium Proceedings
Volume	36
ISSN	2153-6996

Conference

Conference	36th IEEE International Geoscience and Remote Sensing Symposium
Abbreviated title	IGARSS
Country/Territory	China
City	Beijing
Period	10/07/16 → 15/07/16

Keywords

L-band radiometer
L-MEB
SMOS
Soil moisture

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10.1109/IGARSS.2016.7729428

Cite this

Seppänen, Jaakko ; Praks, Jaan ; Antropov, Oleg. / Improving SMOS soil moisture algorithm performance in forested areas with multisensor SAR data. 2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016. IEEE Institute of Electrical and Electronic Engineers, 2016. pp. 1675-1678 (IEEE International Geoscience and Remote Sensing Symposium Proceedings, Vol. 36).

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title = "Improving SMOS soil moisture algorithm performance in forested areas with multisensor SAR data",

abstract = "In this paper, we propose a new approach for improving boreal forest soil moisture estimation using L-band microwave radiometer. The effect is achieved by introducing improved description of forest canopy contribution from multisensor SAR measurements. Spaceborne L-band radiometer is a valuable tool for providing soil moisture estimates globally. Unfortunately, complex vegetation layer, such as forest, can hamper the accuracy of soil moisture retrieval leading to rather poor results particularly over boreal forest areas. Currently, the L-band Microwave Emission of the Biosphere (L-MEB) model adopted in the Soil Moisture and Ocean Salinity (SMOS) Level 2 Soil Moisture algorithm, uses Leaf Area Index (LAI) in order to to account for forest canopy contribution to total emission. However, it can argued that LAI presents poorly the actual structure of the coniferous forest. The LAI is calibrated to represent only the leaves, but at L-band, the main contribution to emission and attenuation is due to branches, while trunks and leaves have smaller effects. Here, we tested several combinations of spaceborne SAR data as a substitute of LA! in temperature brightness models for soil moisture retrieval. Particularly when L-band ALOS PALSAR stripmap data were used, the agreement between modelled and measured TB has improved from 0.46 to 0.55 in the L-MEB model.",

keywords = "L-band radiometer, L-MEB, SMOS, Soil moisture",

author = "Jaakko Sepp{\"a}nen and Jaan Praks and Oleg Antropov",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE. Copyright: Copyright 2017 Elsevier B.V., All rights reserved.; 36th IEEE International Geoscience and Remote Sensing Symposium : Advancing the understanding of our living planet, IGARSS ; Conference date: 10-07-2016 Through 15-07-2016",

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doi = "10.1109/IGARSS.2016.7729428",

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Seppänen, J, Praks, J & Antropov, O 2016, Improving SMOS soil moisture algorithm performance in forested areas with multisensor SAR data. in 2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016., 7729428, IEEE Institute of Electrical and Electronic Engineers, IEEE International Geoscience and Remote Sensing Symposium Proceedings, vol. 36, pp. 1675-1678, 36th IEEE International Geoscience and Remote Sensing Symposium, Beijing, China, 10/07/16. https://doi.org/10.1109/IGARSS.2016.7729428

Improving SMOS soil moisture algorithm performance in forested areas with multisensor SAR data. / Seppänen, Jaakko; Praks, Jaan; Antropov, Oleg.
2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016. IEEE Institute of Electrical and Electronic Engineers, 2016. p. 1675-1678 7729428 (IEEE International Geoscience and Remote Sensing Symposium Proceedings, Vol. 36).

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

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AU - Antropov, Oleg

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PY - 2016/11/1

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N2 - In this paper, we propose a new approach for improving boreal forest soil moisture estimation using L-band microwave radiometer. The effect is achieved by introducing improved description of forest canopy contribution from multisensor SAR measurements. Spaceborne L-band radiometer is a valuable tool for providing soil moisture estimates globally. Unfortunately, complex vegetation layer, such as forest, can hamper the accuracy of soil moisture retrieval leading to rather poor results particularly over boreal forest areas. Currently, the L-band Microwave Emission of the Biosphere (L-MEB) model adopted in the Soil Moisture and Ocean Salinity (SMOS) Level 2 Soil Moisture algorithm, uses Leaf Area Index (LAI) in order to to account for forest canopy contribution to total emission. However, it can argued that LAI presents poorly the actual structure of the coniferous forest. The LAI is calibrated to represent only the leaves, but at L-band, the main contribution to emission and attenuation is due to branches, while trunks and leaves have smaller effects. Here, we tested several combinations of spaceborne SAR data as a substitute of LA! in temperature brightness models for soil moisture retrieval. Particularly when L-band ALOS PALSAR stripmap data were used, the agreement between modelled and measured TB has improved from 0.46 to 0.55 in the L-MEB model.

AB - In this paper, we propose a new approach for improving boreal forest soil moisture estimation using L-band microwave radiometer. The effect is achieved by introducing improved description of forest canopy contribution from multisensor SAR measurements. Spaceborne L-band radiometer is a valuable tool for providing soil moisture estimates globally. Unfortunately, complex vegetation layer, such as forest, can hamper the accuracy of soil moisture retrieval leading to rather poor results particularly over boreal forest areas. Currently, the L-band Microwave Emission of the Biosphere (L-MEB) model adopted in the Soil Moisture and Ocean Salinity (SMOS) Level 2 Soil Moisture algorithm, uses Leaf Area Index (LAI) in order to to account for forest canopy contribution to total emission. However, it can argued that LAI presents poorly the actual structure of the coniferous forest. The LAI is calibrated to represent only the leaves, but at L-band, the main contribution to emission and attenuation is due to branches, while trunks and leaves have smaller effects. Here, we tested several combinations of spaceborne SAR data as a substitute of LA! in temperature brightness models for soil moisture retrieval. Particularly when L-band ALOS PALSAR stripmap data were used, the agreement between modelled and measured TB has improved from 0.46 to 0.55 in the L-MEB model.

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M3 - Conference article in proceedings

AN - SCOPUS:85007453772

SN - 978-1-5090-3333-1

T3 - IEEE International Geoscience and Remote Sensing Symposium Proceedings

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Seppänen J, Praks J, Antropov O. Improving SMOS soil moisture algorithm performance in forested areas with multisensor SAR data. In 2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016. IEEE Institute of Electrical and Electronic Engineers. 2016. p. 1675-1678. 7729428. (IEEE International Geoscience and Remote Sensing Symposium Proceedings, Vol. 36). doi: 10.1109/IGARSS.2016.7729428

Improving SMOS soil moisture algorithm performance in forested areas with multisensor SAR data

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