Fast extracting of change area from remote sensing image by Fuzzy theory and case base reasoning

Ting Shiuan Wang, Teng To Yu

研究成果: Conference contribution

摘要

This study presents the technology to combine the remote sensing image of SPOT and FORMOSAT-2 satellite image by Fuzzy theory and case base reasoning. This method adopt three experience identify factors of NDVI, shape, and color to establish the membership function. The Fuzzy theory was applied to estimate the process of thinking as the human brain; while the Case Base Reasoning method was used to increase the capability of self-loop learning and support its consistency with the real nature. The results show that the successful rate of identification was between 90 percent. The Case Base Reasoning results show that the two data similarity was between 46 percent. The Fuzzy and Case Base Reasoning difference factor was (satellite sensors, inclination, date, shadowing, etc.). The rate can be increase if there is enough experienced data. It reveal that fuzzy theory with case base reasoning indeed can rapid screen the change area from remote sensing image in before and after the disaster event.

原文English
主出版物標題FUZZ 2011 - 2011 IEEE International Conference on Fuzzy Systems - Proceedings
頁面340-345
頁數6
DOIs
出版狀態Published - 2011 九月 27
事件2011 IEEE International Conference on Fuzzy Systems, FUZZ 2011 - Taipei, Taiwan
持續時間: 2011 六月 272011 六月 30

出版系列

名字IEEE International Conference on Fuzzy Systems
ISSN(列印)1098-7584

Other

Other2011 IEEE International Conference on Fuzzy Systems, FUZZ 2011
國家/地區Taiwan
城市Taipei
期間11-06-2711-06-30

All Science Journal Classification (ASJC) codes

  • 軟體
  • 理論電腦科學
  • 人工智慧
  • 應用數學

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