DocumentCode :
1892512
Title :
Moisture & roughness estimation algorithm over permafrost area
Author :
Watanabe, Manabu ; Kushida, Keiji ; Harada, Koichiro ; Fukuda, Masami ; Sato, Motoyuki
fYear :
2011
fDate :
24-29 July 2011
Firstpage :
2598
Lastpage :
2601
Abstract :
We propose an algorithm to estimate surface roughness and moisture level of active layer of permafrost over permafrost area. This algorithm is based on the Oh´s semi-empirical model, and PALSAR data observed both in winter and summer seasons with vh polarization. PALSAR vh polarization data observed in winter is used to estimate surface roughness of permafrost. Then, the estimated surface roughness and PALSAR vh polarization data observed in summer is used to estimate the moisture level of the active layer of the permafrost. The moisture levels estimated from PALSAR data moderately matched with those of validation data taken in the field, while the surface roughness value shows some difference. The possible cause of this difference is that the surface roughness derived from the field data collection represents the roughness of the top of the sphagnum moss layer covered on the active layer of the permafrost, while the one estimated from PALSAR represents the roughness of the underlying active layer of the permafrost.
Keywords :
hydrological techniques; hydrology; ice; moisture; remote sensing by radar; synthetic aperture radar; vegetation; Oh semiempirical model; PALSAR data; VH polarization; moisture level; permafrost area; roughness estimation algorithm; sphagnum moss layer; surface roughness; Educational institutions; Mathematical model; Moisture; Moisture measurement; Rough surfaces; Soil moisture; Surface roughness; PALSAR; full polarimetry; global warming;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2011 IEEE International
Conference_Location :
Vancouver, BC
ISSN :
2153-6996
Print_ISBN :
978-1-4577-1003-2
Type :
conf
DOI :
10.1109/IGARSS.2011.6049773
Filename :
6049773
Link To Document :
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