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

Jaakko Seppänen, Jaan Praks, Oleg Antropov

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference contributionScientificvertaisarvioitu

Abstrakti

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 (LA!) in order to to account for forest canopy contribution to total emission. However, it can argued that LA! presents poorly the actual structure of the coniferous forest. The LA! 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.

AlkuperäiskieliEnglanti
OtsikkoProceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016
KustantajaIEEE
Sivut1675-1678
Sivumäärä4
Vuosikerta2016-November
ISBN (elektroninen)9781509033324
DOI - pysyväislinkit
TilaJulkaistu - 1 marraskuuta 2016
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaInternational Geoscience and Remote Sensing Symposium - Beijing, Kiina
Kesto: 10 heinäkuuta 201615 heinäkuuta 2016
Konferenssinumero: 36

Julkaisusarja

NimiIEEE International Geoscience and Remote Sensing Symposium proceedings
KustantajaIEEE
ISSN (painettu)2153-6996
ISSN (elektroninen)2153-7003

Conference

ConferenceInternational Geoscience and Remote Sensing Symposium
LyhennettäIGARSS
MaaKiina
KaupunkiBeijing
Ajanjakso10/07/201615/07/2016

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