DocumentCode
1535432
Title
Forest Modeling For Height Inversion Using Single-Baseline InSAR/Pol-InSAR Data
Author
Garestier, Franck ; Le Toan, Thuy
Volume
48
Issue
3
fYear
2010
fDate
3/1/2010 12:00:00 AM
Firstpage
1528
Lastpage
1539
Abstract
The Random Volume over Ground (RVoG) model has been extensively applied to polarimetric synthetic aperture radar interferometry (Pol-InSAR) data for forest height inversion. The model assumes forest as a homogeneous volume of randomly oriented particles characterized by a constant extinction but does not take into account the forest vertical heterogeneity, to which interferometric coherence is sensitive. In order to integrate vertical heterogeneity in forest models, two complementary models, which take into consideration the forest natural structure, are investigated through analysis of volume interferometric coherence. The first model assumes a vertically varying extinction in the volume layer, and the second model considers predominant contributions localized in a finite height interval, modeled as a Gaussian-distributed backscatter. The two forest models are compared with constant extinction RVoG in the coherence and interferometric phase aspects. Finally, the contribution of these new models for forest height inversion using the Pol-InSAR technique is discussed in the context of a two-layer ground + canopy medium.
Keywords
forestry; geophysical signal processing; height measurement; inverse problems; radar interferometry; radar polarimetry; radar signal processing; remote sensing by radar; synthetic aperture radar; Gaussian distributed backscatter; Pol-InSAR data; RVoG model; canopy medium; forest height inversion; forest modeling; forest natural structure; forest vertical heterogeneity; height interval; interferometric coherence volume analysis; polarimetric synthetic aperture radar interferometry; random volume over ground model; single baseline InSAR data; two layer ground medium; Forestry; interferometry; polarimetry; synthetic aperture radar (SAR);
fLanguage
English
Journal_Title
Geoscience and Remote Sensing, IEEE Transactions on
Publisher
ieee
ISSN
0196-2892
Type
jour
DOI
10.1109/TGRS.2009.2032538
Filename
5308279
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