Multi-Sensor Sar Data for Improved Modeling of Microwave Brightness Temperature over Boreal Forest

Oleg Antropov; Jaakko Seppänen; Thomas Jagdhuber; Hallikainen Martti; Jaan Praks

doi:10.1109/IGARSS.2018.8517626

Multi-Sensor Sar Data for Improved Modeling of Microwave Brightness Temperature over Boreal Forest

Oleg Antropov^*, Jaakko Seppänen, Thomas Jagdhuber, Hallikainen Martti, Jaan Praks

^*Corresponding author for this work

German Aerospace Center

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

Abstract

Here, we investigate multiple ways of assimilating synthetic aperture radar (SAR) data to L-band Microwave Emission of the Biosphere (L-MEB) model to enhance the model performance over forested areas in the boreal zone. Land C-band satellite SAR backscatter data, X-band interferometric SAR coherence, as well as auxiliary data layers from forest authorities are used as a proxy in calculating the forest transmissivity, instead of traditionally used leaf area index (LAI) parameter.

Our earlier experiments have shown, that when particularly ALOS PALSAR (L-band) and multitemporal composite Sentinel-1 (C-band) data were applied, an improved agreement was achieved between the measured and simulated brightness temperatures (TBs) over forests. Here, we extend our analysis and examine data acquired by ALOS PALSAR, ESA Sentinel-1, and TanDEM-X mission of DLR, as well as several other auxiliary datasets on forest parameters. Our proposed model based approach indicates the potential of an SAR-based estimation of forest volume transmissivity and represents a viable way of active-passive microwave satellite data fusion and incorporating readily available reference data.

Original language	English
Title of host publication	IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium
Publisher	IEEE
Pages	361-364
Number of pages	4
ISBN (Electronic)	978-1-5386-7150-4
DOIs	https://doi.org/10.1109/IGARSS.2018.8517626
Publication status	Published - 2018
MoE publication type	A4 Conference publication
Event	IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain Duration: 22 Jul 2018 → 27 Jul 2018 Conference number: 38 https://www.igarss2018.org/

Publication series

Name	IEEE International Symposium on Geoscience and Remote Sensing IGARSS
Publisher	IEEE
ISSN (Print)	2153-6996
ISSN (Electronic)	2153-7003

Conference

Conference	IEEE International Geoscience and Remote Sensing Symposium
Abbreviated title	IGARSS
Country/Territory	Spain
City	Valencia
Period	22/07/2018 → 27/07/2018
Internet address	https://www.igarss2018.org/

Keywords

microwave radiometry
remote sensing
soil moisture
synthetic aperture radar (SAR)
interferometric SAR coherence
forest stem volume
ALOS PALSAR
Sentinel-1
TanDEM-X
RADAR BACKSCATTER
STEM VOLUME
SOIL
RETRIEVAL

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/IGARSS.2018.8517626

Cite this

Antropov, O., Seppänen, J., Jagdhuber, T., Martti, H., & Praks, J. (2018). Multi-Sensor Sar Data for Improved Modeling of Microwave Brightness Temperature over Boreal Forest. In IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium (pp. 361-364). (IEEE International Symposium on Geoscience and Remote Sensing IGARSS). IEEE. https://doi.org/10.1109/IGARSS.2018.8517626

@inproceedings{e44968139dc24607a310efb8658a2b83,

title = "Multi-Sensor Sar Data for Improved Modeling of Microwave Brightness Temperature over Boreal Forest",

abstract = "Here, we investigate multiple ways of assimilating synthetic aperture radar (SAR) data to L-band Microwave Emission of the Biosphere (L-MEB) model to enhance the model performance over forested areas in the boreal zone. Land C-band satellite SAR backscatter data, X-band interferometric SAR coherence, as well as auxiliary data layers from forest authorities are used as a proxy in calculating the forest transmissivity, instead of traditionally used leaf area index (LAI) parameter.Our earlier experiments have shown, that when particularly ALOS PALSAR (L-band) and multitemporal composite Sentinel-1 (C-band) data were applied, an improved agreement was achieved between the measured and simulated brightness temperatures (TBs) over forests. Here, we extend our analysis and examine data acquired by ALOS PALSAR, ESA Sentinel-1, and TanDEM-X mission of DLR, as well as several other auxiliary datasets on forest parameters. Our proposed model based approach indicates the potential of an SAR-based estimation of forest volume transmissivity and represents a viable way of active-passive microwave satellite data fusion and incorporating readily available reference data.",

keywords = "microwave radiometry, remote sensing, soil moisture, synthetic aperture radar (SAR), interferometric SAR coherence, forest stem volume, ALOS PALSAR, Sentinel-1, TanDEM-X, RADAR BACKSCATTER, STEM VOLUME, SOIL, RETRIEVAL",

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

year = "2018",

doi = "10.1109/IGARSS.2018.8517626",

language = "English",

series = "IEEE International Symposium on Geoscience and Remote Sensing IGARSS",

publisher = "IEEE",

pages = "361--364",

booktitle = "IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium",

address = "United States",

note = "IEEE International Geoscience and Remote Sensing Symposium , IGARSS ; Conference date: 22-07-2018 Through 27-07-2018",

url = "https://www.igarss2018.org/",

}

Antropov, O, Seppänen, J, Jagdhuber, T, Martti, H & Praks, J 2018, Multi-Sensor Sar Data for Improved Modeling of Microwave Brightness Temperature over Boreal Forest. in IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium. IEEE International Symposium on Geoscience and Remote Sensing IGARSS, IEEE, pp. 361-364, IEEE International Geoscience and Remote Sensing Symposium , Valencia, Spain, 22/07/2018. https://doi.org/10.1109/IGARSS.2018.8517626

Multi-Sensor Sar Data for Improved Modeling of Microwave Brightness Temperature over Boreal Forest. / Antropov, Oleg; Seppänen, Jaakko; Jagdhuber, Thomas et al.
IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2018. p. 361-364 (IEEE International Symposium on Geoscience and Remote Sensing IGARSS).

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

TY - GEN

T1 - Multi-Sensor Sar Data for Improved Modeling of Microwave Brightness Temperature over Boreal Forest

AU - Antropov, Oleg

AU - Seppänen, Jaakko

AU - Jagdhuber, Thomas

AU - Martti, Hallikainen

AU - Praks, Jaan

N1 - Conference code: 38

PY - 2018

Y1 - 2018

N2 - Here, we investigate multiple ways of assimilating synthetic aperture radar (SAR) data to L-band Microwave Emission of the Biosphere (L-MEB) model to enhance the model performance over forested areas in the boreal zone. Land C-band satellite SAR backscatter data, X-band interferometric SAR coherence, as well as auxiliary data layers from forest authorities are used as a proxy in calculating the forest transmissivity, instead of traditionally used leaf area index (LAI) parameter.Our earlier experiments have shown, that when particularly ALOS PALSAR (L-band) and multitemporal composite Sentinel-1 (C-band) data were applied, an improved agreement was achieved between the measured and simulated brightness temperatures (TBs) over forests. Here, we extend our analysis and examine data acquired by ALOS PALSAR, ESA Sentinel-1, and TanDEM-X mission of DLR, as well as several other auxiliary datasets on forest parameters. Our proposed model based approach indicates the potential of an SAR-based estimation of forest volume transmissivity and represents a viable way of active-passive microwave satellite data fusion and incorporating readily available reference data.

AB - Here, we investigate multiple ways of assimilating synthetic aperture radar (SAR) data to L-band Microwave Emission of the Biosphere (L-MEB) model to enhance the model performance over forested areas in the boreal zone. Land C-band satellite SAR backscatter data, X-band interferometric SAR coherence, as well as auxiliary data layers from forest authorities are used as a proxy in calculating the forest transmissivity, instead of traditionally used leaf area index (LAI) parameter.Our earlier experiments have shown, that when particularly ALOS PALSAR (L-band) and multitemporal composite Sentinel-1 (C-band) data were applied, an improved agreement was achieved between the measured and simulated brightness temperatures (TBs) over forests. Here, we extend our analysis and examine data acquired by ALOS PALSAR, ESA Sentinel-1, and TanDEM-X mission of DLR, as well as several other auxiliary datasets on forest parameters. Our proposed model based approach indicates the potential of an SAR-based estimation of forest volume transmissivity and represents a viable way of active-passive microwave satellite data fusion and incorporating readily available reference data.

KW - microwave radiometry

KW - remote sensing

KW - soil moisture

KW - synthetic aperture radar (SAR)

KW - interferometric SAR coherence

KW - forest stem volume

KW - ALOS PALSAR

KW - Sentinel-1

KW - TanDEM-X

KW - RADAR BACKSCATTER

KW - STEM VOLUME

KW - SOIL

KW - RETRIEVAL

U2 - 10.1109/IGARSS.2018.8517626

DO - 10.1109/IGARSS.2018.8517626

M3 - Conference article in proceedings

T3 - IEEE International Symposium on Geoscience and Remote Sensing IGARSS

SP - 361

EP - 364

BT - IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium

PB - IEEE

T2 - IEEE International Geoscience and Remote Sensing Symposium

Y2 - 22 July 2018 through 27 July 2018

ER -

Multi-Sensor Sar Data for Improved Modeling of Microwave Brightness Temperature over Boreal Forest

Abstract

Publication series

Conference

Keywords

UN SDGs

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Cite this