Landslide hazard susceptibility evaluation takes on critical significance in early warning and disaster prevention and reduction.In order to solve the problems of poor effectiveness of landslide data and complex calcu...Landslide hazard susceptibility evaluation takes on critical significance in early warning and disaster prevention and reduction.In order to solve the problems of poor effectiveness of landslide data and complex calculation of weights for multiple evaluation factors in the existing landslide susceptibility evaluation models,in this study,a method of landslide hazard susceptibility evaluation is proposed by combining SBAS-InSAR(Small Baseline Subsets-Interferometric Synthetic Aperture Radar)and SSA-BP(Sparrow Search Algorithm-Back Propagation)neural network algorithm.The SBAS-InSAR technology is adopted to identify potential landslide hazards in the study area,update the cataloging data of landslide hazards,and 11 evaluation factors are chosen for constructing the SSA-BP model for training and validation.Baihetan Reservoir area is selected as a case study for validation.As indicated by the results,the application of SBAS-InSAR technology,combined with both ascending and descending orbit data,effectively addresses the incomplete identification of landslide hazards caused by geometric distortion of single orbit SAR data(e.g.,shadow,overlay,and perspective contraction)in deep canyon areas,thereby enabling the acquisition of up-to-date landslide hazard data.Moreover,in comparison to the conventional BP(Back Propagation)algorithm,the accuracy of the model constructed by the SSA-BP algorithm exhibits a significant increase,with mean squared error and mean absolute error reduced by 0.0142 and 0.0607,respectively.Additionally,during the process of susceptibility evaluation,the SSA-BP model effectively circumvents the issue of considerable manual interventions in calculating the weight of evaluation factors.The area under the curve of this model reaches 0.909,surpassing BP(0.835),random forest(0.792),and the information value method(0.699).The risk of landslide occurrence in the Baihetan Reservoir area is positively correlated with slope,surface temperature,and deformation rate,while it is negatively correlated with fault distance and normalized difference vegetation index.Geological lithology exerts minimal influence on the occurrence of landslides,with the risk being low in forest land and high in grassland.The method proposed in this study provides a useful reference for disaster prevention and mitigation departments to perform landslide hazard susceptibility evaluations in deep canyon areas under complex geological conditions.展开更多
Landslides are significant natural geological hazards.Landslide susceptibility evaluation involves the quantitative assessment and prediction of potential landslide locations and their probabilities.Research has explo...Landslides are significant natural geological hazards.Landslide susceptibility evaluation involves the quantitative assessment and prediction of potential landslide locations and their probabilities.Research has explored susceptibility assessment methods based on spatial-scale analysis.This evaluation integrates two models—global and local scale—using a CNN model and a PSO-CNN coupled model.Key aspects include selecting evaluation factors and optimizing model parameters for landslide susceptibility at different scales.A major focus of current landslide research is utilizing prediction results to enhance prevention and control measures.展开更多
This study develops a geological hazard evaluation index system for Shouning County,a key area for disaster prevention in Fujian Province.Through detailed investigation reports and field surveys,six factors were selec...This study develops a geological hazard evaluation index system for Shouning County,a key area for disaster prevention in Fujian Province.Through detailed investigation reports and field surveys,six factors were selected,including elevation,slope gradient,slope aspect,stratigraphic lithological group,distance from the water systems,and geological structures.A geological hazard susceptibility zoning map was created using the Information Quantity Method(IQM).The evaluation showed that elevation,slope aspect,and distance from the water systems are primary risk factors,with high and extremely high susceptibility areas covering 168.57 km^(2)(52.63%of the study area)and a disaster point density of 3.07 points/km^(2).The model achieved an accuracy of 0.73,validating its effectiveness in hazard assessment.These findings provide a valuable reference for disaster prediction and mitigation in Shouning County,supporting improved planning and risk management efforts.展开更多
Diffuse axonal injury（DAI）is axonal and small vessel injury produced by a sudden acceleration of the head by an external force,and is a major cause of death and severe disability（Paterakis et al.,2000）.Prognosis i...Diffuse axonal injury（DAI）is axonal and small vessel injury produced by a sudden acceleration of the head by an external force,and is a major cause of death and severe disability（Paterakis et al.,2000）.Prognosis is poorer in patients with apparent hemorrhage than in those without（Paterakis et al.,2000）.Therefore,it is important to identify the presence and precise position of hemorrhagic foci for a more accurate diagnosis.CT and magnetic resonance imaging（MRI）have long been applied in the diagnosis of DAI, but they are not sensitive enough for the detection of small hemorrhagic foci, and cannot meet the requirements for early diagnosis. A major advance in MRI has been the development of susceptibility weighted imaging （SWI）, which has greatly increased the ability to detect small hemorrhagic foci after DAI （Ashwal et al., 2006）.展开更多
Early defoliation,which usually occurs during summer in pear trees,is gradually becoming a major problem that poses a serious threat to the pear industry in southern China.However,there is no system for evaluating the...Early defoliation,which usually occurs during summer in pear trees,is gradually becoming a major problem that poses a serious threat to the pear industry in southern China.However,there is no system for evaluating the responses of different cultivars to early defoliation,and our knowledge of the potential molecular regulation of the genes underlying this phenomenon is still limited.In this study,we conducted field investigations of 155 pear accessions to assess their resistance or susceptibility to early defoliation.A total of 126 accessions were found to be susceptible to early defoliation,and only 29 accessions were resistant.Among them,19 resistant accessions belong to the sand pear species(Pyrus pyrifolia).To identify the resistance genes related to early defoliation,the healthy and diseased samples of two sand pear accessions,namely,the resistant early defoliation accession‘Whasan’and the susceptible early defoliation accession‘Cuiguan’,were used to perform RNA sequencing.Compared with‘Cuiguan’,a total of 444 genes were uniquely differentially expressed in‘Whasan’.Combined with GO and KEGG enrichment analyses,we found that early defoliation was closely related to the stress response.Furthermore,a weighted gene co-expression network analysis revealed a high correlation of WRKY and ethylene responsive factor(ERF)transcription factors with early defoliation resistance.This study provides useful resistant germplasm resources and new insights into potentially essential genes that respond to early defoliation in pears,which may facilitate a better understanding of the resistance mechanism and molecular breeding of resistant pear cultivars.展开更多
In conventional susceptibility evaluation of geo-hazards,there are some limits,such as unreasonable division of evaluated region,difficulty in quantifying evaluation indicators,time-consuming calculation.To address th...In conventional susceptibility evaluation of geo-hazards,there are some limits,such as unreasonable division of evaluated region,difficulty in quantifying evaluation indicators,time-consuming calculation.To address these problems,we try to employ the software ArcGIS to evaluate geo-hazards susceptibility.The study area of Yaozhou County is automatically divided into 3562 units.Based on the spatial overlay analysis function of ArcGIS,quantitative evaluation of geo-hazards susceptibility is implemented in the study area,and the geo-hazards susceptibility zoning is mapped.It is observed that the evaluation results match well with field investigations.展开更多
The Hengduan Mountains Region(HMR)is one of the areas that experience the most frequent geological hazards in China.However,few reports are available that address the geological hazard susceptibility of the region.Thi...The Hengduan Mountains Region(HMR)is one of the areas that experience the most frequent geological hazards in China.However,few reports are available that address the geological hazard susceptibility of the region.This study developed six machine learning models to assess the geological hazard susceptibility.The results show that areas with medium and high susceptibility to geological hazards as a whole account for almost 21%of the total area,while both are 18%when it comes to the single hazard of landslide and rockfall respectively.Medium and high geological hazard susceptibility is found in three parts of the HMR with different characteristics:(1)the central and southern parts,where the population of the region concentrates;(2)the northern part,where higher geological hazard susceptibility is found along the mountain ranges;and(3)the junction of Tibet,Yunnan,and Sichuan in the eastern part,which is prone to larger-scale geological hazards.Of all the potential influencing factors,topographic features and climatic variables act as the major driving factors behind geological hazards and elevation,slope,and precipitation are crucial indicators for geological hazard susceptibility assessment.This study developed the geological hazard susceptibility maps of the HMR and provided information for the multi-hazard risk assessment and management of the region.展开更多
基金funded by the National Natural Science Foundation of China(Grant No.41861134008)Muhammad Asif Khan academician workstation of Yunnan Province(Grant No.202105AF150076)+6 种基金General program of Yunnan Province Science and Technology Department(Grant No.202105AF150076)Key Project of Natural Science Foundation of Yunnan Province(Grant No.202101AS070019)Key R&D Program of Yunnan Province(Grant No.202003AC100002)General Program of basic research plan of Yunnan Province(Grant No.202001AT070059)Major scientific and technological projects of Yunnan Province:Research on Key Technologies of ecological environment monitoring and intelligent management of natural resources in Yunnan(No:202202AD080010)“Study on High-Level Hidden Landslide Identification Based on Multi-Source Data”of Key Laboratory of Early Rapid Identification,Prevention and Control of Geological Diseases in Traffic Corridor of High Intensity Earthquake Mountainous Area of Yunnan Province(KLGDTC-2021-02)Guizhou Scientific and Technology Fund(QKHJ-ZK[2023]YB 193).
文摘Landslide hazard susceptibility evaluation takes on critical significance in early warning and disaster prevention and reduction.In order to solve the problems of poor effectiveness of landslide data and complex calculation of weights for multiple evaluation factors in the existing landslide susceptibility evaluation models,in this study,a method of landslide hazard susceptibility evaluation is proposed by combining SBAS-InSAR(Small Baseline Subsets-Interferometric Synthetic Aperture Radar)and SSA-BP(Sparrow Search Algorithm-Back Propagation)neural network algorithm.The SBAS-InSAR technology is adopted to identify potential landslide hazards in the study area,update the cataloging data of landslide hazards,and 11 evaluation factors are chosen for constructing the SSA-BP model for training and validation.Baihetan Reservoir area is selected as a case study for validation.As indicated by the results,the application of SBAS-InSAR technology,combined with both ascending and descending orbit data,effectively addresses the incomplete identification of landslide hazards caused by geometric distortion of single orbit SAR data(e.g.,shadow,overlay,and perspective contraction)in deep canyon areas,thereby enabling the acquisition of up-to-date landslide hazard data.Moreover,in comparison to the conventional BP(Back Propagation)algorithm,the accuracy of the model constructed by the SSA-BP algorithm exhibits a significant increase,with mean squared error and mean absolute error reduced by 0.0142 and 0.0607,respectively.Additionally,during the process of susceptibility evaluation,the SSA-BP model effectively circumvents the issue of considerable manual interventions in calculating the weight of evaluation factors.The area under the curve of this model reaches 0.909,surpassing BP(0.835),random forest(0.792),and the information value method(0.699).The risk of landslide occurrence in the Baihetan Reservoir area is positively correlated with slope,surface temperature,and deformation rate,while it is negatively correlated with fault distance and normalized difference vegetation index.Geological lithology exerts minimal influence on the occurrence of landslides,with the risk being low in forest land and high in grassland.The method proposed in this study provides a useful reference for disaster prevention and mitigation departments to perform landslide hazard susceptibility evaluations in deep canyon areas under complex geological conditions.
基金Jiangxi Provincial Innovative Training Project“Post-earthquake Landslide Risk Evaluation Study under Spatial Scale Modelling”(Project No.:S202311318050)。
文摘Landslides are significant natural geological hazards.Landslide susceptibility evaluation involves the quantitative assessment and prediction of potential landslide locations and their probabilities.Research has explored susceptibility assessment methods based on spatial-scale analysis.This evaluation integrates two models—global and local scale—using a CNN model and a PSO-CNN coupled model.Key aspects include selecting evaluation factors and optimizing model parameters for landslide susceptibility at different scales.A major focus of current landslide research is utilizing prediction results to enhance prevention and control measures.
基金2024 Guiding Science and Technology Program of Fujian Province(No.2024H0026)2025 Innovation Fund Project of Fujian Province(No.2025C0004).
文摘This study develops a geological hazard evaluation index system for Shouning County,a key area for disaster prevention in Fujian Province.Through detailed investigation reports and field surveys,six factors were selected,including elevation,slope gradient,slope aspect,stratigraphic lithological group,distance from the water systems,and geological structures.A geological hazard susceptibility zoning map was created using the Information Quantity Method(IQM).The evaluation showed that elevation,slope aspect,and distance from the water systems are primary risk factors,with high and extremely high susceptibility areas covering 168.57 km^(2)(52.63%of the study area)and a disaster point density of 3.07 points/km^(2).The model achieved an accuracy of 0.73,validating its effectiveness in hazard assessment.These findings provide a valuable reference for disaster prediction and mitigation in Shouning County,supporting improved planning and risk management efforts.
基金supported by a grant from the Key Science and Technology Development Project of Nanjing Medical University in ChinaNo.08NMU054
文摘Diffuse axonal injury（DAI）is axonal and small vessel injury produced by a sudden acceleration of the head by an external force,and is a major cause of death and severe disability（Paterakis et al.,2000）.Prognosis is poorer in patients with apparent hemorrhage than in those without（Paterakis et al.,2000）.Therefore,it is important to identify the presence and precise position of hemorrhagic foci for a more accurate diagnosis.CT and magnetic resonance imaging（MRI）have long been applied in the diagnosis of DAI, but they are not sensitive enough for the detection of small hemorrhagic foci, and cannot meet the requirements for early diagnosis. A major advance in MRI has been the development of susceptibility weighted imaging （SWI）, which has greatly increased the ability to detect small hemorrhagic foci after DAI （Ashwal et al., 2006）.
基金supported by the earmarked fund for Jiangsu Agricultural Industry Technology System,China(JATS[2021]453)the National Key Research and Development Program of China(2021YFD1200200)the earmarked fund for China Agriculture Research System(CARS-28).
文摘Early defoliation,which usually occurs during summer in pear trees,is gradually becoming a major problem that poses a serious threat to the pear industry in southern China.However,there is no system for evaluating the responses of different cultivars to early defoliation,and our knowledge of the potential molecular regulation of the genes underlying this phenomenon is still limited.In this study,we conducted field investigations of 155 pear accessions to assess their resistance or susceptibility to early defoliation.A total of 126 accessions were found to be susceptible to early defoliation,and only 29 accessions were resistant.Among them,19 resistant accessions belong to the sand pear species(Pyrus pyrifolia).To identify the resistance genes related to early defoliation,the healthy and diseased samples of two sand pear accessions,namely,the resistant early defoliation accession‘Whasan’and the susceptible early defoliation accession‘Cuiguan’,were used to perform RNA sequencing.Compared with‘Cuiguan’,a total of 444 genes were uniquely differentially expressed in‘Whasan’.Combined with GO and KEGG enrichment analyses,we found that early defoliation was closely related to the stress response.Furthermore,a weighted gene co-expression network analysis revealed a high correlation of WRKY and ethylene responsive factor(ERF)transcription factors with early defoliation resistance.This study provides useful resistant germplasm resources and new insights into potentially essential genes that respond to early defoliation in pears,which may facilitate a better understanding of the resistance mechanism and molecular breeding of resistant pear cultivars.
基金Supported by the Key Project of National Natural Science Foundation(41130753)China Geological Survey Bureau Land Resources Survey Project(1212011014012)
文摘In conventional susceptibility evaluation of geo-hazards,there are some limits,such as unreasonable division of evaluated region,difficulty in quantifying evaluation indicators,time-consuming calculation.To address these problems,we try to employ the software ArcGIS to evaluate geo-hazards susceptibility.The study area of Yaozhou County is automatically divided into 3562 units.Based on the spatial overlay analysis function of ArcGIS,quantitative evaluation of geo-hazards susceptibility is implemented in the study area,and the geo-hazards susceptibility zoning is mapped.It is observed that the evaluation results match well with field investigations.
基金financially supported by the China National Key R&D Program,Grant No.2019YFA0606900by the Scientific Investigation of the Qinghai-Tibet Plateau,Grant No.2019QZKK0900。
文摘The Hengduan Mountains Region(HMR)is one of the areas that experience the most frequent geological hazards in China.However,few reports are available that address the geological hazard susceptibility of the region.This study developed six machine learning models to assess the geological hazard susceptibility.The results show that areas with medium and high susceptibility to geological hazards as a whole account for almost 21%of the total area,while both are 18%when it comes to the single hazard of landslide and rockfall respectively.Medium and high geological hazard susceptibility is found in three parts of the HMR with different characteristics:(1)the central and southern parts,where the population of the region concentrates;(2)the northern part,where higher geological hazard susceptibility is found along the mountain ranges;and(3)the junction of Tibet,Yunnan,and Sichuan in the eastern part,which is prone to larger-scale geological hazards.Of all the potential influencing factors,topographic features and climatic variables act as the major driving factors behind geological hazards and elevation,slope,and precipitation are crucial indicators for geological hazard susceptibility assessment.This study developed the geological hazard susceptibility maps of the HMR and provided information for the multi-hazard risk assessment and management of the region.
