Experimental Validation of Conifer and Broad-Leaf Tree Classification Using High Resolution PolSAR Data above X-Band

Yoshio YAMAGUCHI; Yuto MINETANI; Maito UMEMURA; Hiroyoshi YAMADA

doi:10.1587/transcom.2018EBP3288

Experimental Validation of Conifer and Broad-Leaf Tree Classification Using High Resolution PolSAR Data above X-Band

Yoshio YAMAGUCHI, Yuto MINETANI, Maito UMEMURA, Hiroyoshi YAMADA

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Summary :

This paper presents a conifer and broad-leaf tree classification scheme that processes high resolution polarimetric synthetic aperture data above X-band. To validate the proposal, fully polarimetric measurements are conducted in a precisely controlled environment to examine the difference between the scattering mechanisms of conifer and broad-leaf trees at 15GHz. With 3.75cm range resolution, scattering matrices of two tree types were measured by a vector network analyzer. Polarimetric analyses using the 4-component scattering power decomposition and alpha-bar angle of eigenvalue decomposition yielded clear distinction between the two tree types. This scheme was also applied to an X-band Pi-SAR2 data set. The results confirm that it is possible to distinguish between tree types using fully polarimetric and high-resolution data above X-band.

Publication: IEICE TRANSACTIONS on Communications Vol.E102-B No.7 pp.1345-1350

Publication Date: 2019/07/01

Publicized: 2019/01/09

Online ISSN: 1745-1345

DOI: 10.1587/transcom.2018EBP3288

Type of Manuscript: PAPER

Category: Antennas and Propagation

Authors

Yoshio YAMAGUCHI
  Niigata University
Yuto MINETANI
  Niigata University
Maito UMEMURA
  Niigata University
Hiroyoshi YAMADA
  Niigata University

Keyword

polarimetry, scattering power decomposition, eigenvalue decomposition, conifer, broad-leaf tree

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Yoshio YAMAGUCHI, Yuto MINETANI, Maito UMEMURA, Hiroyoshi YAMADA, "Experimental Validation of Conifer and Broad-Leaf Tree Classification Using High Resolution PolSAR Data above X-Band" in IEICE TRANSACTIONS on Communications, vol. E102-B, no. 7, pp. 1345-1350, July 2019, doi: 10.1587/transcom.2018EBP3288.
Abstract: This paper presents a conifer and broad-leaf tree classification scheme that processes high resolution polarimetric synthetic aperture data above X-band. To validate the proposal, fully polarimetric measurements are conducted in a precisely controlled environment to examine the difference between the scattering mechanisms of conifer and broad-leaf trees at 15GHz. With 3.75cm range resolution, scattering matrices of two tree types were measured by a vector network analyzer. Polarimetric analyses using the 4-component scattering power decomposition and alpha-bar angle of eigenvalue decomposition yielded clear distinction between the two tree types. This scheme was also applied to an X-band Pi-SAR2 data set. The results confirm that it is possible to distinguish between tree types using fully polarimetric and high-resolution data above X-band.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2018EBP3288/_p

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@ARTICLE{e102-b_7_1345,
author={Yoshio YAMAGUCHI, Yuto MINETANI, Maito UMEMURA, Hiroyoshi YAMADA, },
journal={IEICE TRANSACTIONS on Communications},
title={Experimental Validation of Conifer and Broad-Leaf Tree Classification Using High Resolution PolSAR Data above X-Band},
year={2019},
volume={E102-B},
number={7},
pages={1345-1350},
abstract={This paper presents a conifer and broad-leaf tree classification scheme that processes high resolution polarimetric synthetic aperture data above X-band. To validate the proposal, fully polarimetric measurements are conducted in a precisely controlled environment to examine the difference between the scattering mechanisms of conifer and broad-leaf trees at 15GHz. With 3.75cm range resolution, scattering matrices of two tree types were measured by a vector network analyzer. Polarimetric analyses using the 4-component scattering power decomposition and alpha-bar angle of eigenvalue decomposition yielded clear distinction between the two tree types. This scheme was also applied to an X-band Pi-SAR2 data set. The results confirm that it is possible to distinguish between tree types using fully polarimetric and high-resolution data above X-band.},
keywords={},
doi={10.1587/transcom.2018EBP3288},
ISSN={1745-1345},
month={July},}

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TY - JOUR
TI - Experimental Validation of Conifer and Broad-Leaf Tree Classification Using High Resolution PolSAR Data above X-Band
T2 - IEICE TRANSACTIONS on Communications
SP - 1345
EP - 1350
AU - Yoshio YAMAGUCHI
AU - Yuto MINETANI
AU - Maito UMEMURA
AU - Hiroyoshi YAMADA
PY - 2019
DO - 10.1587/transcom.2018EBP3288
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E102-B
IS - 7
JA - IEICE TRANSACTIONS on Communications
Y1 - July 2019
AB - This paper presents a conifer and broad-leaf tree classification scheme that processes high resolution polarimetric synthetic aperture data above X-band. To validate the proposal, fully polarimetric measurements are conducted in a precisely controlled environment to examine the difference between the scattering mechanisms of conifer and broad-leaf trees at 15GHz. With 3.75cm range resolution, scattering matrices of two tree types were measured by a vector network analyzer. Polarimetric analyses using the 4-component scattering power decomposition and alpha-bar angle of eigenvalue decomposition yielded clear distinction between the two tree types. This scheme was also applied to an X-band Pi-SAR2 data set. The results confirm that it is possible to distinguish between tree types using fully polarimetric and high-resolution data above X-band.
ER -