TY - GEN
T1 - Improving SMOS soil moisture algorithm performance in forested areas with multisensor SAR data
AU - Seppänen, Jaakko
AU - Praks, Jaan
AU - Antropov, Oleg
N1 - Publisher Copyright:
© 2016 IEEE.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2016/11/1
Y1 - 2016/11/1
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.
KW - L-band radiometer
KW - L-MEB
KW - SMOS
KW - Soil moisture
UR - http://www.scopus.com/inward/record.url?scp=85007453772&partnerID=8YFLogxK
U2 - 10.1109/IGARSS.2016.7729428
DO - 10.1109/IGARSS.2016.7729428
M3 - Conference article in proceedings
AN - SCOPUS:85007453772
SN - 978-1-5090-3333-1
T3 - IEEE International Geoscience and Remote Sensing Symposium Proceedings
SP - 1675
EP - 1678
BT - 2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016
PB - IEEE Institute of Electrical and Electronic Engineers
T2 - 36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016
Y2 - 10 July 2016 through 15 July 2016
ER -