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| 1 | Multi-hazard susceptibility mapping based on Convolutional Neural Networks显示文摘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. | Kashif Ullah Yi Wang Zhice Fang Lizhe Wang Mahfuzur Rahman | 2022 | Geoscience Frontiers2022，13，5： | 4 |
| 2 | Photocatalytic activities of N-doped nano-titanias and titanium nitride显示文摘 | Zhice Zhang Josephine B.M. Goodall David J. Morgan Sonal Brown Robin J.H. Clark Jonathan C. Knowles Nicola J. Mordan Julian R.G. Evans Albert F. Carley Michael Bowker Jawwad A. Darr | 2009 | Journal of the European Ceramic Society2009，，11： | 1 |
| 3 | 显示文摘 | Zhao Dishun Liu Huiru Xu Zhice | 2005 | Chemical Journal of Chinese Universities2005，26，2： | 1 |
| 4 | Direct continuous hydrothermal synthesis of high surface area nanosized titania显示文摘 | Zhice Zhang Sonal Brown Josephine B M | 2009 | Journal of Alloys and Compounds2009，，476： | 1 |
| 5 | Correlation analysis of longitudinal cracks and vertical deformation within asphalt pavement of cold regions显示文摘The asphalt pavement longitudinal crack is a common distress in cold regions,resulting from uneven deformation of the subgrade.Analysis of the correlation law between uneven deformation and crack distress is of positive significance for understanding the mechanism of crack initiation,and putting forward treatment measures.In view of the complexity of longitudinal crack inducement and road surface deformation,the grey relational method was used to analyze this relationship.Through long-term monitoring of the vertical deformation data of typical road sections,the vertical deformation law of the pavement surface and its deformation characteristics under the action of temperature field are analyzed.Parameters such as vertical relative deformation,vertical relative deformation rate and vertical differential deformation VDSr were constructed to describe vertical deformation characteristics.Typical distribution characteristics of longitudinal fractures and their length and distribution characteristics are also described.The grey correlation analysis theory was utilized to analyze the relationship between deformation characteristics of sections,cross sections and monitoring points and longitudinal crack characteristics(length and location).The analysis reveals a linear positive correlation or a high correlation between several indicators.This study can provide a deeper understanding of the occurrence and development mechanism of longitudinal cracks in asphalt pavement of cold areas,and give references for the research of road engineering structure,materials and distress prevention. | Ke Chen Lun Ji ZeYu Xiao JinQi Wu LinLin Xu ZhiCe Cheng | 2023 | Research in Cold and Arid Regions2023，15，6： | 0 |
| 6 | From spatio-temporal landslide susceptibility to landslide risk forecast显示文摘The literature on landslide susceptibility is rich with examples that span a wide range of topics.However,the component that pertains to the extension of the susceptibility framework toward space–time modeling is largely unexplored.This statement holds true,particularly in the context of landslide risk,where few scientific contributions investigate risk dynamics in space and time.This manuscript proposes a modeling protocol where a dynamic landslide susceptibility is obtained via a binomial Generalized Additive Model whose inventories span nine years(from 2013 to 2021).For the analyses,the data cube is organized with a mapping unit consisting of 26,333 slope units repeated over an annual temporal unit,resulting in a total of 236,997 units.This phase already includes several interesting modeling experiments that have rarely appeared in the landslide literature(e.g.,variable interaction plots).However,the main innovative effort is in the subsequent phase of the protocol we propose,as we used climate projections of the main trigger(rainfall)to obtain future estimates of yearly susceptibility patterns.These estimates are then combined with projections of urban settlements and associated populations to create a dynamic risk model,assuming vulnerability=1.Overall,this manuscript presents a unique example of such a modeling routine and offers a potential standard for administrations to make informed decisions regarding future urban development. | Tengfei Wang Ashok Dahal Zhice Fang Cees van Westen Kunlong Yin Luigi Lombardo | 2024 | Geoscience Frontiers2024，15，2： | 0 |
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