Fine Classification of PolSAR Land Cover Types Based on Multi-Band

Fangzhou Han; Tianci Liu; Lamei Zhang; Shang Fang

doi:10.1109/IGARSS52108.2023.10282348

Fine Classification of PolSAR Land Cover Types Based on Multi-Band

Fangzhou Han^*
, Tianci Liu
, Lamei Zhang
, Shang Fang

^*Corresponding author for this work

School of Electronics and Information Engineering

Harbin Institute of Technology
The University of Electro-Communications

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Considering the distinct scattering characteristics observed in diverse frequency bands for terrain surfaces, the utilization of complementary information from multi-band PolSAR data proves advantageous in effectively distinguishing targets that may present challenges when assessed in isolation within a single band. In this study, we employ the polarimetric target decomposition methods to investigate the scattering characteristics of representative targets within the C and L bands. Based on these findings, we construct a random forest fine classification model specifically tailored for different types of urban vegetation. Notably, experimental results demonstrate a noteworthy enhancement in classification accuracy following the integration of multi-band data.

Original language	English
Title of host publication	IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	8030-8033
Number of pages	4
ISBN (Electronic)	9798350320107
DOIs	https://doi.org/10.1109/IGARSS52108.2023.10282348
State	Published - 2023
Event	2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023 - Pasadena, United States Duration: 16 Jul 2023 → 21 Jul 2023

Publication series

Name	International Geoscience and Remote Sensing Symposium (IGARSS)
Volume	2023-July
ISSN (Electronic)	2153-6996

Conference

Conference	2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023
Country/Territory	United States
City	Pasadena
Period	16/07/23 → 21/07/23

Keywords

PolSAR terrain surface classification
multi-band PolSAR
polarimetric target decomposition method
scattering characteristic

Access to Document

10.1109/IGARSS52108.2023.10282348

Cite this

Han, F., Liu, T., Zhang, L., & Fang, S. (2023). Fine Classification of PolSAR Land Cover Types Based on Multi-Band. In IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings (pp. 8030-8033). (International Geoscience and Remote Sensing Symposium (IGARSS) ; Vol. 2023-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IGARSS52108.2023.10282348

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title = "Fine Classification of PolSAR Land Cover Types Based on Multi-Band",

abstract = "Considering the distinct scattering characteristics observed in diverse frequency bands for terrain surfaces, the utilization of complementary information from multi-band PolSAR data proves advantageous in effectively distinguishing targets that may present challenges when assessed in isolation within a single band. In this study, we employ the polarimetric target decomposition methods to investigate the scattering characteristics of representative targets within the C and L bands. Based on these findings, we construct a random forest fine classification model specifically tailored for different types of urban vegetation. Notably, experimental results demonstrate a noteworthy enhancement in classification accuracy following the integration of multi-band data.",

keywords = "PolSAR terrain surface classification, multi-band PolSAR, polarimetric target decomposition method, scattering characteristic",

author = "Fangzhou Han and Tianci Liu and Lamei Zhang and Shang Fang",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023 ; Conference date: 16-07-2023 Through 21-07-2023",

year = "2023",

doi = "10.1109/IGARSS52108.2023.10282348",

language = "英语",

series = "International Geoscience and Remote Sensing Symposium (IGARSS) ",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "8030--8033",

booktitle = "IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings",

address = "美国",

}

Han, F, Liu, T, Zhang, L & Fang, S 2023, Fine Classification of PolSAR Land Cover Types Based on Multi-Band. in IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings. International Geoscience and Remote Sensing Symposium (IGARSS) , vol. 2023-July, Institute of Electrical and Electronics Engineers Inc., pp. 8030-8033, 2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023, Pasadena, United States, 16/07/23. https://doi.org/10.1109/IGARSS52108.2023.10282348

Fine Classification of PolSAR Land Cover Types Based on Multi-Band. / Han, Fangzhou; Liu, Tianci; Zhang, Lamei et al.
IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2023. p. 8030-8033 (International Geoscience and Remote Sensing Symposium (IGARSS) ; Vol. 2023-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Fine Classification of PolSAR Land Cover Types Based on Multi-Band

AU - Han, Fangzhou

AU - Liu, Tianci

AU - Zhang, Lamei

AU - Fang, Shang

PY - 2023

Y1 - 2023

N2 - Considering the distinct scattering characteristics observed in diverse frequency bands for terrain surfaces, the utilization of complementary information from multi-band PolSAR data proves advantageous in effectively distinguishing targets that may present challenges when assessed in isolation within a single band. In this study, we employ the polarimetric target decomposition methods to investigate the scattering characteristics of representative targets within the C and L bands. Based on these findings, we construct a random forest fine classification model specifically tailored for different types of urban vegetation. Notably, experimental results demonstrate a noteworthy enhancement in classification accuracy following the integration of multi-band data.

AB - Considering the distinct scattering characteristics observed in diverse frequency bands for terrain surfaces, the utilization of complementary information from multi-band PolSAR data proves advantageous in effectively distinguishing targets that may present challenges when assessed in isolation within a single band. In this study, we employ the polarimetric target decomposition methods to investigate the scattering characteristics of representative targets within the C and L bands. Based on these findings, we construct a random forest fine classification model specifically tailored for different types of urban vegetation. Notably, experimental results demonstrate a noteworthy enhancement in classification accuracy following the integration of multi-band data.

KW - PolSAR terrain surface classification

KW - multi-band PolSAR

KW - polarimetric target decomposition method

KW - scattering characteristic

UR - https://www.scopus.com/pages/publications/85178355007

U2 - 10.1109/IGARSS52108.2023.10282348

DO - 10.1109/IGARSS52108.2023.10282348

M3 - 会议稿件

AN - SCOPUS:85178355007

T3 - International Geoscience and Remote Sensing Symposium (IGARSS)

SP - 8030

EP - 8033

BT - IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023

Y2 - 16 July 2023 through 21 July 2023

ER -

Han F, Liu T, Zhang L, Fang S. Fine Classification of PolSAR Land Cover Types Based on Multi-Band. In IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings. Institute of Electrical and Electronics Engineers Inc. 2023. p. 8030-8033. (International Geoscience and Remote Sensing Symposium (IGARSS) ). doi: 10.1109/IGARSS52108.2023.10282348

Fine Classification of PolSAR Land Cover Types Based on Multi-Band

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