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

被引：5

作者：

Shang, Fang ^{[1
]}

Saito, Taiga ^{[1
]}

Ohi, Saya ^{[1
]}

Kishi, Naoto ^{[1
]}

机构：

[1] Univ Electrocommun, Dept Comp & Network Engn, Tokyo 1828585, Japan

来源：

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING | 2021年 / 59卷 / 09期

关键词：

Sensitivity; Correlation; Distributed databases; Forestry; Vegetation; Surfaces; Feature extraction; polarimetric synthetic aperture radar (PolSAR); stokes parameters; CLASSIFICATION; RADAR;

D O I：

10.1109/TGRS.2020.3032468

中图分类号：

P3 [地球物理学]; P59 [地球化学];

学科分类号：

0708 ; 070902 ;

摘要：

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.

引用

页码：7487 / 7499

页数：13

共 32 条

[11] Aboveground Biomass Mapping Using ALOS-2/PALSAR-2 Time-Series Images for Borneo's Forest [J].

Hayashi, Masato ;

Motohka, Takeshi ;

Sawada, Yoshito .

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2019, 12 (12) :5167-5177

[12] Polarimetric SAR Interferometry based modeling for tree height and aboveground biomass retrieval in a tropical deciduous forest [J].

Kumar, Shashi ;

Khati, Unmesh G. ;

Chandola, Shreya ;

Agrawal, Shefali ;

Kushwaha, Satya P. S. .

ADVANCES IN SPACE RESEARCH, 2017, 60 (03) :571-586

[13] Comparison of Machine Learning Methods Applied to SAR Images for Forest Classification in Mediterranean Areas [J].

Lapini, Alessandro ;

Pettinato, Simone ;

Santi, Emanuele ;

Paloscia, Simonetta ;

Fontanelli, Giacomo ;

Garzelli, Andrea .

REMOTE SENSING, 2020, 12 (03)

[14]

Lee J.S., 2004, Journal of Photogrammetry and Remote Sensing, V9, P31

[15]

Lee JS, 2009, OPT SCI ENG-CRC, P1

[16] Forest Assessment Using High Resolution SAR Data in X-Band [J].

Perko, Roland ;

Raggam, Hannes ;

Deutscher, Janik ;

Gutjahr, Karlheinz ;

Schardt, Mathias .

REMOTE SENSING, 2011, 3 (04) :792-815

[17]

Saito T, 2019, INT GEOSCI REMOTE SE, P3285, DOI [10.1109/igarss.2019.8898698, 10.1109/IGARSS.2019.8898698]

[18] Complementarity of X-, C-, and L-band SAR Backscatter Observations to Retrieve Forest Stem Volume in Boreal Forest [J].

Santoro, Maurizio ;

Cartus, Oliver ;

Fransson, Johan E. S. ;

Wegmuller, Urs .

REMOTE SENSING, 2019, 11 (13)

[19] Aboveground Forest Biomass Estimation Combining L- and P-Band SAR Acquisitions [J].

Schlund, Michael ;

Davidson, Malcolm W. J. .

REMOTE SENSING, 2018, 10 (07)

[20]

Shang F., 2019, PROC INT S ANTENNAS, P1

← 1 2 3 4 →