DocumentCode :
2191754
Title :
Relating envisat ASAR and ALOS PALSAR backscattering coefficient to spot NDVI for monitoring seasonal change of pasture biomass in Western Australia
Author :
Wang, Xin ; Li, Xiaojing ; Ge, Linlin
Author_Institution :
Sch. of Surveying & Spatial Inf. Syst., Univ. of New South Wales, Sydney, NSW, Australia
fYear :
2012
fDate :
22-27 July 2012
Firstpage :
3744
Lastpage :
3747
Abstract :
Regular estimates of pasture biomass are invaluable for managing the supply of annual pasture in Western Australia (WA). NDVI has been used for estimation of biomass in Australia, with some shortcomings which could be overcome by SAR. The regression model between pasture biomass and SAR backscatter could be obtained if sufficient ground measurements of biomass are available. However, biomass measurements over a large area are not easy to be obtained. Therefore, we are trying to relate ENVISAT ASAR/ALOS PALSAR backscatter to NDVI, and then to biomass. It was found that time series of NDVI is significantly correlated to ASAR HH, HV+HH, VV+VH (dB) with R2 of 0.71, 0.67, and 0.63, respectively. NDVI is also significantly related to ALOS PALSAR HH (R2=0.82). In conclusion, the investigation confirmed the potential of ASAR and PALSAR data monitoring biomass and its seasonal change in the temperate Southwestern Australia, and provided a solid foundation for further research concerning quantitative estimation of biomass.
Keywords :
remote sensing by radar; vegetation; ASAR data biomass monitoring; ENVISAT ALOS PALSAR backscattering coefficient; ENVISAT ASAR backscattering coefficient; NDVI; PALSAR data biomass monitoring; Southwestern Australia; Western Australia; biomass estimation; biomass measurements; biomass quantitative estimation; pasture biomass seasonal change monitoring; regression model; Australia; Backscatter; Biomass; Mathematical model; Monitoring; Synthetic aperture radar; Vegetation mapping; Biomass; Correlation; Fourier Fitting; NDVI; SAR Backscatter;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location :
Munich
ISSN :
2153-6996
Print_ISBN :
978-1-4673-1160-1
Electronic_ISBN :
2153-6996
Type :
conf
DOI :
10.1109/IGARSS.2012.6350503
Filename :
6350503
Link To Document :
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