Study on Remote Sensing Image Auto-Identify Classification by Used of Object-Oriented Technology

Si Wen Xia; Shu Gan; Peng Fei Ren; Xiao Lun Zhang

doi:10.4028/www.scientific.net/AMM.444-445.1244

Paper Titles

Numerical Simulation on the Temperature Field of Steel 1045 Quenched by Different Hardening Media
p.1222

A Case Study of Application of Modern Design of Experiment Methods in High Speed Wind Tunnel Test
p.1229

Numerical Simulation of Supersonic Aircraft Surface Aerodynamic Heating and Infrared Radiation Characteristics
p.1234

Remote Sensing Integration Survey of Typical Land Types and Analysis of its Spectral Properties in Southeast of Yunnan Province
p.1239

Study on Remote Sensing Image Auto-Identify Classification by Used of Object-Oriented Technology
p.1244

Mechanical Numerical Analysis for L-Shape Traffic Signs Bar with Variable Cross-Section
p.1250

The Urban Space Expansion Analysis in Mountain Areas Based on GIS and RS
p.1255

Research on Evaluation and Development Potential Analysis of Low-Slope Hilly Land Resources
p.1260

Seismic Response on the Mangjiedu Long-Span PC Continuous Rigid Frame Bridge with High Piers
p.1265

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 444-445Study on Remote Sensing Image Auto-Identify...

Study on Remote Sensing Image Auto-Identify Classification by Used of Object-Oriented Technology

Abstract:

In dealing with high-resolution remote sensing image auto-identify classification, the traditional pixel-based and spectral statistical characteristics classification technology or method has some insurmountable difficulties. In this paper, object-oriented image analysis method is by application, the auto-identify classification rules are set up based the different remote sensing image characteristics that included such as spectral, texture, scale and so on. As a case study, a petroleum reserve base auto-identify classification is selected as an example and the target is identified, in a better effective result by applications of the object-oriented method. The result appraising analysis indicates that object-oriented classification method to identify automatically high-resolution remote sensing images pattern object can get a high precision. The method of object-oriented has a widely potential application for remote sensing image automatic-identify classification in times to come.

You might also be interested in these eBooks

Advances in Computational Modeling and Simulation

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 444-445)

Pages:

1244-1249

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.444-445.1244

Citation:

Cite this paper

Online since:

October 2013

Authors:

Si Wen Xia, Shu Gan, Peng Fei Ren, Xiao Lun Zhang

Keywords:

Auto-Identify Classification Technology, High-Resolution, Object-Oriented Classification Method, Remote Sensing Image

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Huiping Hu. Using object-oriented technology to access information of landscape. [Master thesis]. Central South University. Hunan, (2007).

Google Scholar

[2] Yuanxiu Guan, Xiaoyang Cheng. Guidelines of high-resolution satellite image processing. [M]. Science Press. Beijing, (2008).

Google Scholar

[3] Ning Sun. Object recognition method of high spatial resolution remote sensing images for building. [Master thesis]. Zhejiang University. Hangzhou, (2010).

Google Scholar

[4] Qihao Chen. Research and implementation of object-oriented classification technology for multi-source remote sensing data. [Master thesis]. China University of Geosciences. Wuhan, (2007).

Google Scholar

[5] Chinese user manual of ECognition8 Developer. [G]. Panorama Space Technology Co., Ltd. Beijing, (2010).

Google Scholar