NDLI: Review of remotely sensed imagery classification patterns based on object-oriented image analysis

Content Provider	Springer Nature Link
Author	Liu, Yongxue Li, Manchun Mao, Liang Xu, Feifei Huang, Shuo
Copyright Year	2006
Abstract	With the wide use of high-resolution remotely sensed imagery, the object-oriented remotely sensed information 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 methodology 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 information 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.
Starting Page	282
Ending Page	288
Page Count	7
File Format	PDF
ISSN	10020063
Journal	Chinese Geographical Science
Volume Number	16
Issue Number	3
Language	English
Publisher	Science Press
Publisher Date	2006-01-01
Publisher Place	Beijing
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	object-oriented image analysis remote sensing classification pattern Geography (general)
Content Type	Text
Resource Type	Article
Subject	Earth and Planetary Sciences Geography, Planning and Development

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