Classification of Tree Types by Polarimetric Pi-SAR

Motoyuki Sato; Takafumi Koike

Classification of Tree Types by Polarimetric Pi-SAR

Research output: Contribution to conference › Paper › peer-review

Abstract

In order to classify tree types, we introduce a new technique, which detects the change of Polarimetric Entropy parameters. We define the difference of the two-dimensional polarimetric entropy parameters, and applied the proposed technique to Pi-SAR airborne polarimetric SAR data. The result in an urban area shows that the seasonal change is very random and we could not find significant changes between two scenes. Then, we applied the technique to a forested region. The change in coniferous trees and broad leafed trees is statistically different. Using the change in polarimetric entropy properties, we find this technique can be used for tree type classification.

Original language	English
Pages	431-433
Number of pages	3
Publication status	Published - 2003
Externally published	Yes
Event	2003 IEEE IGARSS: Learning From Earth's Shapes and Colours - Toulouse, France Duration: 2003 Jul 21 → 2003 Jul 25

Other

Other	2003 IEEE IGARSS: Learning From Earth's Shapes and Colours
Country/Territory	France
City	Toulouse
Period	03/7/21 → 03/7/25

Keywords

Pi-SAR
Polarimetri Entropy
Radar Polrainmtry
Tree Classification

ASJC Scopus subject areas

Computer Science Applications
Earth and Planetary Sciences(all)

Cite this

@conference{7505e79129554f57812241d6045655e7,

title = "Classification of Tree Types by Polarimetric Pi-SAR",

abstract = "In order to classify tree types, we introduce a new technique, which detects the change of Polarimetric Entropy parameters. We define the difference of the two-dimensional polarimetric entropy parameters, and applied the proposed technique to Pi-SAR airborne polarimetric SAR data. The result in an urban area shows that the seasonal change is very random and we could not find significant changes between two scenes. Then, we applied the technique to a forested region. The change in coniferous trees and broad leafed trees is statistically different. Using the change in polarimetric entropy properties, we find this technique can be used for tree type classification.",

keywords = "Pi-SAR, Polarimetri Entropy, Radar Polrainmtry, Tree Classification",

author = "Motoyuki Sato and Takafumi Koike",

note = "Funding Information: This work was supported by a JSPS grant-in-aid for scientific research (S) 4102024); 2003 IEEE IGARSS: Learning From Earth's Shapes and Colours ; Conference date: 21-07-2003 Through 25-07-2003",

year = "2003",

language = "English",

pages = "431--433",

}

TY - CONF

T1 - Classification of Tree Types by Polarimetric Pi-SAR

AU - Sato, Motoyuki

AU - Koike, Takafumi

N1 - Funding Information: This work was supported by a JSPS grant-in-aid for scientific research (S) 4102024)

PY - 2003

Y1 - 2003

N2 - In order to classify tree types, we introduce a new technique, which detects the change of Polarimetric Entropy parameters. We define the difference of the two-dimensional polarimetric entropy parameters, and applied the proposed technique to Pi-SAR airborne polarimetric SAR data. The result in an urban area shows that the seasonal change is very random and we could not find significant changes between two scenes. Then, we applied the technique to a forested region. The change in coniferous trees and broad leafed trees is statistically different. Using the change in polarimetric entropy properties, we find this technique can be used for tree type classification.

AB - In order to classify tree types, we introduce a new technique, which detects the change of Polarimetric Entropy parameters. We define the difference of the two-dimensional polarimetric entropy parameters, and applied the proposed technique to Pi-SAR airborne polarimetric SAR data. The result in an urban area shows that the seasonal change is very random and we could not find significant changes between two scenes. Then, we applied the technique to a forested region. The change in coniferous trees and broad leafed trees is statistically different. Using the change in polarimetric entropy properties, we find this technique can be used for tree type classification.

KW - Pi-SAR

KW - Polarimetri Entropy

KW - Radar Polrainmtry

KW - Tree Classification

UR - http://www.scopus.com/inward/record.url?scp=0242543211&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0242543211&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:0242543211

SP - 431

EP - 433

T2 - 2003 IEEE IGARSS: Learning From Earth's Shapes and Colours

Y2 - 21 July 2003 through 25 July 2003

ER -

Classification of Tree Types by Polarimetric Pi-SAR

Abstract

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Keywords

ASJC Scopus subject areas

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