Abstract:

In recent years, the frequent outbreaks of mountain floods have seriously threatened peoples' lives and property. Risk analysis such as flooding susceptibility assessment is one of the critical approaches to prevent and mitigate flooding disaster. However, the inadequate field survey and lack of data might become the significant challenges for the mapping of flood susceptibility. In the era of big data, user-generated data provides new opportunities for flood risk management. This paper takes Ji’an City as the focus area, using the flooding disaster data generated by users on the Internet. 70% flood events were randomly selected as training sample and eight flood-conditioning factors including elevation, slope, aspect, curvature, rainfall, river distance, land use and normalized vegetation index were chosen to evaluate the flooding disaster by logistic regression model. The confusion matrix and ROC curve were used to verify the evaluation results. The results show that: (1) The area with low terrain, close to water system, large rainfall, and construction land have a higher probability of flood occurrence. (2) According to the confusion matrix, the overall accuracy rate of classification is 80.6%.Verified by ROC curves, the AUC value of the training sample and the validation sample is 0.888 and 0.980 respectively. The AUC values are both greater than 0.8, indicating that the evaluation accuracy of the model is relatively high. (3) The proportion of high-risk and extremely high-risk areas is 28.71%, including 80.99% of the flood events in the study area, which shows these areas are densely distributed and highly susceptible. The evaluation outcomes were consistent with the actual situation based on the verification of the flood events from June 1 to June 8, 2020. It can be concluded from the results above that it is feasible to use the data generated by users on the Internet in mountainous areas where the data is not easy to obtain, and the evaluation results can be used to land use planning and flood risk management in Ji'an city.