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

Jaakko Seppänen, Jaan Praks, Oleg Antropov

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-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 languageEnglish
Title of host publication2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016
PublisherIEEE Institute of Electrical and Electronic Engineers
Pages1675-1678
ISBN (Electronic)978-1-5090-3332-4, 978-1-5090-3331-7
ISBN (Print)978-1-5090-3333-1
DOIs
Publication statusPublished - 1 Nov 2016
MoE publication typeA4 Article in a conference publication
Event36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Beijing, China
Duration: 10 Jul 201615 Jul 2016

Publication series

SeriesIEEE International Geoscience and Remote Sensing Symposium Proceedings
Volume36
ISSN2153-6996

Conference

Conference36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016
Country/TerritoryChina
CityBeijing
Period10/07/1615/07/16

Keywords

  • L-band radiometer
  • L-MEB
  • SMOS
  • Soil moisture

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