Coniferous and Broad-Leaved Forest Distinguishing Using L-Band Polarimetric SAR Data

This article proposes a coniferous and broad-leaved forest distinguishing method using L-band polarimetric SAR data based on the structure-orientation parameter. The structure-orientation parameter is one of the averaged Stokes vector-based discriminators which is sensitive to the composition of equ...

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Bibliographic Details
Published in:IEEE transactions on geoscience and remote sensing 2021-09, Vol.59 (9), p.7487-7499
Main Authors: Shang, Fang, Saito, Taiga, Ohi, Saya, Kishi, Naoto
Format: Article
Language:English
Subjects:
Coniferous forests
Correlation
Discriminators
Distributed databases
Feature extraction
Forestry
Orientation
Parameter sensitivity
Parameters
polarimetric synthetic aperture radar (PolSAR)
Polarimetry
Sensitivity
stokes parameters
Surfaces
Vegetation
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Summary:This article proposes a coniferous and broad-leaved forest distinguishing method using L-band polarimetric SAR data based on the structure-orientation parameter. The structure-orientation parameter is one of the averaged Stokes vector-based discriminators which is sensitive to the composition of equivalent horizontal and vertical structures. In the proposed method, the structure-orientation parameters is compensated by employing the scattered power information to remove the influence of the topography. The final distinguishing result is generated based on the statistical feature of the compensated parameters. The experiments using several sets of ALOS2-PALSAR2 level 1.1 data prove that the proposed method has high performance for forest-type distinguishing.
ISSN:0196-2892
1558-0644
DOI:10.1109/TGRS.2020.3032468