Integrating object-oriented image analysis and decision tree algorithm for land use and land cover classification using Radarsat-2 polarimetric SAR imagery

Zhixin Qi; Anthony Gar On Yeh; Xia Li; Zheng Lin

doi:10.1109/IGARSS.2010.5654051

Integrating object-oriented image analysis and decision tree algorithm for land use and land cover classification using Radarsat-2 polarimetric SAR imagery

Zhixin Qi^*
, Anthony Gar On Yeh
, Xia Li
, Zheng Lin

^*Corresponding author for this work

The University of Hong Kong
Sun Yat-Sen University

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

5 Scopus citations

Abstract

Traditional pixel-based classification methods yield poor results when applied to SAR imagery because of the presence of speckle and limited information in backscatter coefficients. A novel classification method, integrating polarimetric target decomposition, object-oriented image analysis, and decision tree algorithms, is proposed for the classification of polarimetric SAR data (PolSAR). The polarimetric target decomposition is aimed at extracting physical information related to the scattering mechanism of targets for the classification of scattering data. The main purposes of the object-oriented image analysis are delineating objects and extracting various spatial and textural features. The decision tree algorithm provides an efficient way to select features and create a decision tree for the classification. A comparison between the proposed method and the Wishart supervised classification was made. The overall accuracies of these two methods were 89.34% and 79.36%, respectively. The results show that the proposed method is an effective method for the classification of PolSAR data.

Original language	English
Title of host publication	2010 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	3098-3101
Number of pages	4
ISBN (Print)	9781424495658, 9781424495665
DOIs	https://doi.org/10.1109/IGARSS.2010.5654051
State	Published - 2010
Externally published	Yes
Event	2010 30th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010 - Honolulu, United States Duration: 25 Jul 2010 → 30 Jul 2010

Publication series

Name	International Geoscience and Remote Sensing Symposium (IGARSS)

Conference

Conference	2010 30th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010
Country/Territory	United States
City	Honolulu
Period	25/07/10 → 30/07/10

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 15 Life on Land

Keywords

Image classification
Object-oriented methods
Radar polarimetry
Synthetic aperture radar

Access to Document

10.1109/IGARSS.2010.5654051

Cite this

Qi, Z., Yeh, A. G. O., Li, X., & Lin, Z. (2010). Integrating object-oriented image analysis and decision tree algorithm for land use and land cover classification using Radarsat-2 polarimetric SAR imagery. In 2010 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010 (pp. 3098-3101). Article 5654051 (International Geoscience and Remote Sensing Symposium (IGARSS)). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IGARSS.2010.5654051

Qi, Zhixin ; Yeh, Anthony Gar On ; Li, Xia et al. / Integrating object-oriented image analysis and decision tree algorithm for land use and land cover classification using Radarsat-2 polarimetric SAR imagery. 2010 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010. Institute of Electrical and Electronics Engineers Inc., 2010. pp. 3098-3101 (International Geoscience and Remote Sensing Symposium (IGARSS)).

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title = "Integrating object-oriented image analysis and decision tree algorithm for land use and land cover classification using Radarsat-2 polarimetric SAR imagery",

abstract = "Traditional pixel-based classification methods yield poor results when applied to SAR imagery because of the presence of speckle and limited information in backscatter coefficients. A novel classification method, integrating polarimetric target decomposition, object-oriented image analysis, and decision tree algorithms, is proposed for the classification of polarimetric SAR data (PolSAR). The polarimetric target decomposition is aimed at extracting physical information related to the scattering mechanism of targets for the classification of scattering data. The main purposes of the object-oriented image analysis are delineating objects and extracting various spatial and textural features. The decision tree algorithm provides an efficient way to select features and create a decision tree for the classification. A comparison between the proposed method and the Wishart supervised classification was made. The overall accuracies of these two methods were 89.34\% and 79.36\%, respectively. The results show that the proposed method is an effective method for the classification of PolSAR data.",

keywords = "Image classification, Object-oriented methods, Radar polarimetry, Synthetic aperture radar",

author = "Zhixin Qi and Yeh, \{Anthony Gar On\} and Xia Li and Zheng Lin",

year = "2010",

doi = "10.1109/IGARSS.2010.5654051",

language = "英语",

isbn = "9781424495658",

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

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

pages = "3098--3101",

booktitle = "2010 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010",

address = "美国",

note = "2010 30th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010 ; Conference date: 25-07-2010 Through 30-07-2010",

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Qi, Z, Yeh, AGO, Li, X & Lin, Z 2010, Integrating object-oriented image analysis and decision tree algorithm for land use and land cover classification using Radarsat-2 polarimetric SAR imagery. in 2010 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010., 5654051, International Geoscience and Remote Sensing Symposium (IGARSS), Institute of Electrical and Electronics Engineers Inc., pp. 3098-3101, 2010 30th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010, Honolulu, United States, 25/07/10. https://doi.org/10.1109/IGARSS.2010.5654051

Integrating object-oriented image analysis and decision tree algorithm for land use and land cover classification using Radarsat-2 polarimetric SAR imagery. / Qi, Zhixin; Yeh, Anthony Gar On; Li, Xia et al.
2010 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010. Institute of Electrical and Electronics Engineers Inc., 2010. p. 3098-3101 5654051 (International Geoscience and Remote Sensing Symposium (IGARSS)).

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

TY - GEN

T1 - Integrating object-oriented image analysis and decision tree algorithm for land use and land cover classification using Radarsat-2 polarimetric SAR imagery

AU - Qi, Zhixin

AU - Yeh, Anthony Gar On

AU - Li, Xia

AU - Lin, Zheng

PY - 2010

Y1 - 2010

N2 - Traditional pixel-based classification methods yield poor results when applied to SAR imagery because of the presence of speckle and limited information in backscatter coefficients. A novel classification method, integrating polarimetric target decomposition, object-oriented image analysis, and decision tree algorithms, is proposed for the classification of polarimetric SAR data (PolSAR). The polarimetric target decomposition is aimed at extracting physical information related to the scattering mechanism of targets for the classification of scattering data. The main purposes of the object-oriented image analysis are delineating objects and extracting various spatial and textural features. The decision tree algorithm provides an efficient way to select features and create a decision tree for the classification. A comparison between the proposed method and the Wishart supervised classification was made. The overall accuracies of these two methods were 89.34% and 79.36%, respectively. The results show that the proposed method is an effective method for the classification of PolSAR data.

AB - Traditional pixel-based classification methods yield poor results when applied to SAR imagery because of the presence of speckle and limited information in backscatter coefficients. A novel classification method, integrating polarimetric target decomposition, object-oriented image analysis, and decision tree algorithms, is proposed for the classification of polarimetric SAR data (PolSAR). The polarimetric target decomposition is aimed at extracting physical information related to the scattering mechanism of targets for the classification of scattering data. The main purposes of the object-oriented image analysis are delineating objects and extracting various spatial and textural features. The decision tree algorithm provides an efficient way to select features and create a decision tree for the classification. A comparison between the proposed method and the Wishart supervised classification was made. The overall accuracies of these two methods were 89.34% and 79.36%, respectively. The results show that the proposed method is an effective method for the classification of PolSAR data.

KW - Image classification

KW - Object-oriented methods

KW - Radar polarimetry

KW - Synthetic aperture radar

UR - https://www.scopus.com/pages/publications/78650911018

U2 - 10.1109/IGARSS.2010.5654051

DO - 10.1109/IGARSS.2010.5654051

M3 - 会议稿件

AN - SCOPUS:78650911018

SN - 9781424495658

SN - 9781424495665

T3 - International Geoscience and Remote Sensing Symposium (IGARSS)

SP - 3098

EP - 3101

BT - 2010 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2010 30th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010

Y2 - 25 July 2010 through 30 July 2010

ER -

Qi Z, Yeh AGO, Li X, Lin Z. Integrating object-oriented image analysis and decision tree algorithm for land use and land cover classification using Radarsat-2 polarimetric SAR imagery. In 2010 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010. Institute of Electrical and Electronics Engineers Inc. 2010. p. 3098-3101. 5654051. (International Geoscience and Remote Sensing Symposium (IGARSS)). doi: 10.1109/IGARSS.2010.5654051

Integrating object-oriented image analysis and decision tree algorithm for land use and land cover classification using Radarsat-2 polarimetric SAR imagery

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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