Multi-hazard susceptibility mapping based on Convolutional Neural Networks     

《地学前缘(英文版)》2022,13(5):101425

Multi-hazard susceptibility prediction is an important component of disasters risk management plan. An effective multi-hazard risk mitigation strategy includes assessing individual hazards as well as their interactions. However, with the rapid development of artificial intelligence technology, multi-hazard susceptibility prediction techniques based on machine learning has encountered a huge bottleneck. In order to effectively solve this problem, this study proposes a multi-hazard susceptibility mapping framework using the classical deep learning algorithm of Convolutional Neural Networks (CNN). First, we use historical flash flood, debris flow and landslide locations based on Google Earth images, extensive field surveys, topography, hydrology, and environmental data sets to train and validate the proposed CNN method. Next, the proposed CNN method is assessed in comparison to conventional logistic regression and k-nearest neighbor methods using several objective criteria, i.e., coefficient of determination, overall accuracy, mean absolute error and the root mean square error. Experimental results show that the CNN method outperforms the conventional machine learning algorithms in predicting probability of flash floods, debris flows and landslides. Finally, the susceptibility maps of the three hazards based on CNN are combined to create a multi-hazard susceptibility map. It can be observed from the map that 62.43% of the study area are prone to hazards, while 37.57% of the study area are harmless. In hazard-prone areas, 16.14%, 4.94% and 30.66% of the study area are susceptible to flash floods, debris flows and landslides, respectively. In terms of concurrent hazards, 0.28%, 7.11% and 3.13% of the study area are susceptible to the joint occurrence of flash floods and debris flow, debris flow and landslides, and flash floods and landslides, respectively, whereas, 0.18% of the study area is subject to all the three hazards. The results of this study can benefit engineers, disaster managers and local government officials involved in sustainable land management and disaster risk mitigation.  相似文献   

云南一次持续性风雹过程中低空急流的若干特征   总被引：4，自引：0，他引：4  

李英  徐银梓 《气象科学》2000,20(4):503-510

本文分析了１９９７年３月１５～１９日滇南一次持续性风雹天气过程中低空急流的动力、热力特征及其与昆明准静止锋的关系。结果表明,大风冰雹出现在急流轴左侧具有较强正涡度及风场气旋式切变的区域内,当低空急流区伴随强的辐合上升运动且低层有冷气活动时,有利于风雹天气的发生,风雹地区具有较强的斜压不稳定层结。  相似文献