Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-2/W1, 121-126, 2013
https://doi.org/10.5194/isprsarchives-XL-2-W1-121-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
13 May 2013
UNCERTAINTY MANAGEMENT IN SEISMIC VULNERABILITY ASSESSMENT USING GRANULAR COMPUTING BASED ON COVERING OF UNIVERSE
F. Khamespanah1, M. R. Delavar2, and M. Zare2,3 1Dept. of Surveying and Geomatics Eng., College of Eng., University of Tehran, Tehran, Iran
2Center of Excellence in Geomatics Eng. in Disaster Management, Dept. of Surveying and Geomatic Eng., College of Eng., University of Tehran, Tehran, Iran
3Seismology Research Center, International Institute of Earthquake Engineering and Seismology (IIEES), Tehran, Iran
Keywords: Seismic Vulnerability Assessment, Granular Computing Model, Multi Criteria Decision Making Abstract. Earthquake is an abrupt displacement of the earth's crust caused by the discharge of strain collected along faults or by volcanic eruptions. Earthquake as a recurring natural cataclysm has always been a matter of concern in Tehran, capital of Iran, as a laying city on a number of known and unknown faults. Earthquakes can cause severe physical, psychological and financial damages. Consequently, some procedures should be developed to assist modelling the potential casualties and its spatial uncertainty. One of these procedures is production of seismic vulnerability maps to take preventive measures to mitigate corporeal and financial losses of future earthquakes. Since vulnerability assessment is a multi-criteria decision making problem depending on some parameters and expert’s judgments, it undoubtedly is characterized by intrinsic uncertainties.

In this study, it is attempted to use Granular computing (GrC) model based on covering of universe to handle the spatial uncertainty. Granular computing model concentrates on a general theory and methodology for problem solving as well as information processing by assuming multiple levels of granularity. Basic elements in granular computing are subsets, classes, and clusters of a universe called elements. In this research GrC is used for extracting classification rules based on seismic vulnerability with minimum entropy to handle uncertainty related to earthquake data. Tehran was selected as the study area. In our previous research, Granular computing model based on a partition model of universe was employed. The model has some kinds of limitations in defining similarity between elements of the universe and defining granules. In the model similarity between elements is defined based on an equivalence relation. According to this relation, two objects are similar based on some attributes, provided for each attribute the values of these objects are equal.

In this research a general relation for defining similarity between elements of universe is proposed. The general relation is used for defining similarity and instead of partitioning the universe, granulation is done based on covering of universe. As a result of the study, a physical seismic vulnerability map of Tehran has been produced based on granular computing model. The accuracy of the seismic vulnerability map is evaluated using granular computing model based on covering of universe. The comparison between this model and granular computing model based on partition model of universe is undertaken which verified the superiority of the GrC based on covering of the universe in terms of the match between the achieved results with those confirmed by the related experts' judgments.

Conference paper (PDF, 1374 KB)


Citation: Khamespanah, F., Delavar, M. R., and Zare, M.: UNCERTAINTY MANAGEMENT IN SEISMIC VULNERABILITY ASSESSMENT USING GRANULAR COMPUTING BASED ON COVERING OF UNIVERSE, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-2/W1, 121-126, https://doi.org/10.5194/isprsarchives-XL-2-W1-121-2013, 2013.

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