Review of Remotely Sensed Imagery Classification Patterns Based on Object-oriented Image Analysis

LIU Yongxue; LI Manchun; MAO Liang; XU Feifei; HUANG Shuo

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Review of Remotely Sensed Imagery Classification Patterns Based on Object-oriented Image Analysis

LIU Yongxue, LI Manchun, MAO Liang, XU Feifei, HUANG Shuo

文章导航 > Chinese Geographical Science > 2006 > 16(3): 282-288

LIU Yongxue, LI Manchun, MAO Liang, XU Feifei, HUANG Shuo. Review of Remotely Sensed Imagery Classification Patterns Based on Object-oriented Image Analysis[J]. 中国地理科学, 2006, 16(3): 282-288.

引用本文:

LIU Yongxue, LI Manchun, MAO Liang, XU Feifei, HUANG Shuo. Review of Remotely Sensed Imagery Classification Patterns Based on Object-oriented Image Analysis[J]. Chinese Geographical Science, 2006, 16(3): 282-288.

Citation:

LIU Yongxue, LI Manchun, MAO Liang, XU Feifei, HUANG Shuo. Review of Remotely Sensed Imagery Classification Patterns Based on Object-oriented Image Analysis[J]. Chinese Geographical Science, 2006, 16(3): 282-288.

Review of Remotely Sensed Imagery Classification Patterns Based on Object-oriented Image Analysis

1.
School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210093, China;
2.
Department of Geography, State University of New York at Buffalo, Buffalo, NY 14261, USA

基金项目: Under the auspices of the National Natural Science Foundation of China(No.40301038);Talents Recruitment Foun-dation of Nanjing University

详细信息

作者简介:
LIU Yongxue(1976- ),male,a native of Yangzhou of Jiangsu Province,Ph.D.,associate professor,specialized in application of remote sensing & GIS.E-mail:yongxue@nju.edu.cn.

Review of Remotely Sensed Imagery Classification Patterns Based on Object-oriented Image Analysis

1.
School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210093, China;
2.
Department of Geography, State University of New York at Buffalo, Buffalo, NY 14261, USA

摘要: With the wide use of high-resolution remotely sensed imagery, the object-oriented remotely sensed informa- tion classification pattern has been intensively studied. Starting with the definition of object-oriented remotely sensed information classification pattern and a literature review of related research progress, this paper sums up 4 developing phases of object-oriented classification pattern during the past 20 years. Then, we discuss the three aspects of method- ology in detail, namely remotely sensed imagery segmentation, feature analysis and feature selection, and classification rule generation, through comparing them with remotely sensed information classification method based on per-pixel. At last, this paper presents several points that need to be paid attention to in the future studies on object-oriented RS in- formation classification pattern: 1) developing robust and highly effective image segmentation algorithm for multi-spectral RS imagery; 2) improving the feature-set including edge, spatial-adjacent and temporal characteristics; 3) discussing the classification rule generation classifier based on the decision tree; 4) presenting evaluation methods for classification result by object-oriented classification pattern.
- object-oriented image analysis /
- remote sensing /
- classification pattern
Abstract: With the wide use of high-resolution remotely sensed imagery, the object-oriented remotely sensed informa- tion classification pattern has been intensively studied. Starting with the definition of object-oriented remotely sensed information classification pattern and a literature review of related research progress, this paper sums up 4 developing phases of object-oriented classification pattern during the past 20 years. Then, we discuss the three aspects of method- ology in detail, namely remotely sensed imagery segmentation, feature analysis and feature selection, and classification rule generation, through comparing them with remotely sensed information classification method based on per-pixel. At last, this paper presents several points that need to be paid attention to in the future studies on object-oriented RS in- formation classification pattern: 1) developing robust and highly effective image segmentation algorithm for multi-spectral RS imagery; 2) improving the feature-set including edge, spatial-adjacent and temporal characteristics; 3) discussing the classification rule generation classifier based on the decision tree; 4) presenting evaluation methods for classification result by object-oriented classification pattern.
- object-oriented image analysis /
- remote sensing /
- classification pattern

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Review of Remotely Sensed Imagery Classification Patterns Based on Object-oriented Image Analysis

1. School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210093, China;

2. Department of Geography, State University of New York at Buffalo, Buffalo, NY 14261, USA

基金项目: Under the auspices of the National Natural Science Foundation of China(No.40301038);Talents Recruitment Foun-dation of Nanjing University

作者简介:
LIU Yongxue(1976- ),male,a native of Yangzhou of Jiangsu Province,Ph.D.,associate professor,specialized in application of remote sensing & GIS.E-mail:yongxue@nju.edu.cn.

收稿日期: 2006-05-30
修回日期: 2006-07-19
刊出日期: 2006-09-20

关键词:

object-oriented image analysis /

remote sensing /

classification pattern

摘要: With the wide use of high-resolution remotely sensed imagery, the object-oriented remotely sensed informa- tion classification pattern has been intensively studied. Starting with the definition of object-oriented remotely sensed information classification pattern and a literature review of related research progress, this paper sums up 4 developing phases of object-oriented classification pattern during the past 20 years. Then, we discuss the three aspects of method- ology in detail, namely remotely sensed imagery segmentation, feature analysis and feature selection, and classification rule generation, through comparing them with remotely sensed information classification method based on per-pixel. At last, this paper presents several points that need to be paid attention to in the future studies on object-oriented RS in- formation classification pattern: 1) developing robust and highly effective image segmentation algorithm for multi-spectral RS imagery; 2) improving the feature-set including edge, spatial-adjacent and temporal characteristics; 3) discussing the classification rule generation classifier based on the decision tree; 4) presenting evaluation methods for classification result by object-oriented classification pattern.

English Abstract

Review of Remotely Sensed Imagery Classification Patterns Based on Object-oriented Image Analysis

1. School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210093, China;

2. Department of Geography, State University of New York at Buffalo, Buffalo, NY 14261, USA

Received Date: 2006-05-30
Rev Recd Date: 2006-07-19
Publish Date: 2006-09-20

Keywords:

Abstract: With the wide use of high-resolution remotely sensed imagery, the object-oriented remotely sensed informa- tion classification pattern has been intensively studied. Starting with the definition of object-oriented remotely sensed information classification pattern and a literature review of related research progress, this paper sums up 4 developing phases of object-oriented classification pattern during the past 20 years. Then, we discuss the three aspects of method- ology in detail, namely remotely sensed imagery segmentation, feature analysis and feature selection, and classification rule generation, through comparing them with remotely sensed information classification method based on per-pixel. At last, this paper presents several points that need to be paid attention to in the future studies on object-oriented RS in- formation classification pattern: 1) developing robust and highly effective image segmentation algorithm for multi-spectral RS imagery; 2) improving the feature-set including edge, spatial-adjacent and temporal characteristics; 3) discussing the classification rule generation classifier based on the decision tree; 4) presenting evaluation methods for classification result by object-oriented classification pattern.

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Review of Remotely Sensed Imagery Classification Patterns Based on Object-oriented Image Analysis

作者简介: LIU Yongxue(1976- ),male,a native of Yangzhou of Jiangsu Province,Ph.D.,associate professor,specialized in application of remote sensing & GIS.E-mail:yongxue@nju.edu.cn.

Review of Remotely Sensed Imagery Classification Patterns Based on Object-oriented Image Analysis

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出版历程

Review of Remotely Sensed Imagery Classification Patterns Based on Object-oriented Image Analysis

1. School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210093, China; 2. Department of Geography, State University of New York at Buffalo, Buffalo, NY 14261, USA

作者简介: LIU Yongxue(1976- ),male,a native of Yangzhou of Jiangsu Province,Ph.D.,associate professor,specialized in application of remote sensing & GIS.E-mail:yongxue@nju.edu.cn.

English Abstract

Review of Remotely Sensed Imagery Classification Patterns Based on Object-oriented Image Analysis

1. School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210093, China; 2. Department of Geography, State University of New York at Buffalo, Buffalo, NY 14261, USA

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目录

作者简介:
LIU Yongxue(1976- ),male,a native of Yangzhou of Jiangsu Province,Ph.D.,associate professor,specialized in application of remote sensing & GIS.E-mail:yongxue@nju.edu.cn.

1. School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210093, China;

2. Department of Geography, State University of New York at Buffalo, Buffalo, NY 14261, USA

作者简介:
LIU Yongxue(1976- ),male,a native of Yangzhou of Jiangsu Province,Ph.D.,associate professor,specialized in application of remote sensing & GIS.E-mail:yongxue@nju.edu.cn.

1. School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210093, China;

2. Department of Geography, State University of New York at Buffalo, Buffalo, NY 14261, USA