Abstract
Abstract Information fusion has been a hot topic currently, how to make information fusion for intelligent decision is a challenge. Although the applications of random set theory attract many researchers, the probability function distribution is still imprecise. In this paper, we give a new definition of probability distribution function (PDF) of random set theory, and propose an integration methodology for urban flood risk assessment by fusing multi-source information (e. g., remote sensing images, Digital Elevation Model (DEM) and rainstorm data) based on random set theory. The methodology analyzes and fuses the multi-source information, which overcomes the uncertainty of the decision makers of flood risk and generates precise estimates of the probability of flood risk. In our experiments, we take Wuhan city in China and three kinds of data sources information as an example to assess flood risk level. The experiments indicate that our algorithm not only provide precise estimates of the probability of fl...
Highlights
With the development of modern scientific technology, kinds of information have increased rapidly
In this paper we propose a new definition of the probability distribution function (PDF) of a random set for flood risk, we proposed an integration operator; the results of which will be used as the PDF of random set theory in the urban flood risk analysis, which can reduce the imprecise of PDF
The study area of flood risk is composed of several districts which have different multi-source information, i.e. terrain, land use and precipitation, so the risk probability of different sample sites is different for urban flood risk
Summary
With the development of modern scientific technology, kinds of information have increased rapidly. The traditional data fusion theory is lack of strong mathematical basis and an effective comprehensive analysis and judgment It needs to find a new multi-source information fusion method. Random set theory provides a powerful mathematical tool for fusion problem of multi-source heterogeneous information and provides a new method for dealing with flood risk analysis. A model for assessing urban flood risk based on random set theory can integrate multi-source information and improve the accuracy of flood risk analysis. We take Wuhan city in middle of China as an example to make an integration of multi-source information based on random set theory to assess urban flood risk because Wuhan city is prone to be in flood risk.
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