DocumentCode :
2207362
Title :
Observation of vegetation vertical structure and disturbance using L-band InSAR over the Injune region in Australia
Author :
Lei, Yang ; Siqueira, Paul ; Clewley, Daniel ; Lucas, Richard
Author_Institution :
Univ. of Massachusetts, Amherst, MA, USA
fYear :
2012
fDate :
22-27 July 2012
Firstpage :
1637
Lastpage :
1640
Abstract :
Knowledge of the global biomass distribution is essential in monitoring the carbon cycle budget and the climate change. In addition to limited field inventory data, researchers have been developing remote sensing techniques (e.g., LiDAR, SAR backscatter, InSAR phase and/or correlation magnitude) to derive biomass maps. Most of the techniques seek for empirical relationships between biomass and remote sensing measures; however, lack of a direct physical interpretation of the measurement constrains the utility and understanding of remote sensing data sensitivity to the forest characteristics of interest. In this paper, we explore the use of InSAR correlation magnitude to invert for the tree height through use of a physical scattering model [1]. The inversion algorithm, along with the estimates of the tree heights, will be cross-compared with itself over our test area: the Injune region (ILCP) in Australia.
Keywords :
geophysical image processing; optical radar; radar interferometry; remote sensing by radar; synthetic aperture radar; vegetation; vegetation mapping; Australia; InSAR correlation magnitude; InSAR phase magnitude; Injune region; LiDAR; SAR backscatter; biomass maps; carbon cycle budget; climate change; direct physical interpretation; forest characteristics; global biomass distribution; inversion algorithm; limited field inventory data; measurement constrains; physical scattering model; remote sensing data sensitivity; remote sensing measures; remote sensing techniques; test area; tree height; vegetation vertical structure; Backscatter; Biomass; Correlation; Decorrelation; Noise; Thermal noise; Vegetation; InSAR; correlation; tree heights;
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.2012.6351214
Filename :
6351214
Link To Document :
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