Title :
Study on highway geological disasters knowledge base for remote sensing images interpretation
Author :
Liu, Yanbing ; Ren, Yi ; Leiqiua Hu ; Zhumeia Liu
Abstract :
Knowledge can help to find a problem-solution quickly, and knowledge base is a practical tool for managing knowledge systematically. Due to highway geological disasters, cognition from remote sensing images is a complex technology; it´s relevant for disaster mitigation to establish a knowledge base. But most of the frameworks of knowledge base are incomplete due to lack of experts´ knowledge and insufficient quantitative knowledge from images. The purpose of this paper is to construct a highway geological disasters knowledge base (HGDKB) by making full use of multi-features knowledge of images, the visual recognition knowledge of experts, and the object-oriented approach to enabling knowledge being shared for highway geological disasters cognition. Firstly, the knowledge base framework is built, and the object-oriented method is used to represent knowledge by extensible markup language (XML) programming. Then, with the completion of HGDKB, the knowledge base is used to discern and recognize the debris movements with state highway corridor from Wenchuan to Dujiangyan of Sichuan of China as the pilot study.
Keywords :
XML; disasters; geophysical image processing; geophysical techniques; knowledge management; object-oriented methods; remote sensing; roads; China; Dujiangyan; Sichuan; Wenchuan; XML; disaster mitigation; extensible markup language programming; highway geological disaster cognition; highway geological disaster knowledge base; image quantitative knowledge; knowledge base framework; knowledge management; multifeature image knowledge; object-oriented method; remote sensing image interpretation; Databases; Geology; Knowledge acquisition; Knowledge based systems; Remote sensing; Road transportation; Visualization; Geological disaster; Highway; Interpretation; Knowledge base; Object-oriented method;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location :
Munich
Print_ISBN :
978-1-4673-1160-1
Electronic_ISBN :
2153-6996
DOI :
10.1109/IGARSS.2012.6352208