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In this paper, for fuzzy uncertainty of data in disaster risk assessment, we suggest a method to granule the information. Its characteristics lie in exploiting the tolerance for imprecision, uncertainty and partial truth to achieve tractability, robustness, low solution cost and better support with reality. Its operation is more simple and transparent compared with other methods. It provides an important theory and method to describe fuzzy uncertainty of data. In addition, theoretically, we discuss the benefits of suggested method by their representations based on probability and rough set. And then, a simple application of estimating isoseismal area in disaster risk assessment fully demonstrates these advantages.