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Quick and automatic detection of co-seismic landslides with multifeature deep learning model

Science China Earth Sciences 2024年第7期67卷 2311-2325页

作者： Wenchao HUANGFU Haijun QIU Peng CUI Dongdong YANG Ya LIU Bingzhe TANG Zijing LIU Mohib ULLAH college of Urban and Environmental Sciences Northwest UniversityXi'an 710127China Institute of Mountain Hazards and Environment Chinese Academy of SciencesChengdu 610041China Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity Northwest UniversityXi'an 710127China Institute of Earth Surface System and Hazards Northwest UniversityXi'an 710127China

co-seismic landslide detection is essential for post-disaster rescue and risk assessment after an earthquake ***,a variety of ground objects,including roads and bare land,have spectral characteristics similar to those of co-seismic landslides,making it difficult to gather information and assess their impact rapidly and ***,an automatic detection method based on a deep learning model,named ENVINet5,with multiple features(ENVINet5_MF)was proposed to solve this problem and improve the detection accuracy of co-seismic *** ENVINet5_MF method is advantageous for co-seismic landslide detection because it features a landslide gain index(LGI)that effectively eliminates the spectral interference of bare land and *** conducted two experiments using multi-temporal PlanetScope images acquired in Hokkaido,Japan,and Mainling,*** accuracy evaluation and rationality analysis show that ENVINet5_MF performed better than comparative methods and that the co-seismic landslide areas detected by ENVINet5_MF were the most consistent with ground reference *** findings of this study suggest that ENVINet5_MF can provide an efficient and accurate method for coseismic landslide detection to ensure a rapid response to co-seismic landslide disasters.

关键词： co-seismic landslide Automatic detection Deep learning landslide gain index PlanetScope images

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Joint Effects and Spatiotemporal Characteristics of the Driving Factors of landslides in Earthquake Areas

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Journal of Earth Science 2023年第2期34卷 330-338页

作者： Jintao Yang Chong Xu Xu Jin State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China University of Chinese Academy of Sciences Beijing 100049China National Institute of Natural Hazards Ministry of Emergency Management of ChinaBeijing 100085China Key Laboratory of compound and Chained Natural Hazards Dynamics Ministry of Emergency Management of ChinaBeijing 100085China Chengdu Yuanjing Technology co. Ltd.Chengdu 610093China

Understanding the joint effects of earthquakes and driving factors on the spatial distribution of landslides is helpful for targeted disaster prevention and mitigation in earthquake-prone *** far,little work has been done on this *** study analyzed the co-seismic landslide of the Ms8.0 Wenchuan earthquake in 2008 and *** joint effects and spatiotemporal characteristics of the driving factors in seismic regions were *** show that(a)between 2008 and 2014,the dominant driving-factor for landslides has changed from earthquake to rock mass;(b)driving factors with weak driving force have a significant enhancement under the joint effects of other factors;(c)the joint effects of driving factors and earthquake decays with *** study concluded that the strong vibration of the Wenchuan earthquake and the rock mass strength are the biggest contributors to the spatial distribution of landslides in 2008 and 2014,*** means that the driving force of the earthquake is weaker than that of the rock mass after six years of the Wenchuan ***,the landslide spatial distribution can be attributed to the joint effects of the Wenchuan earthquake and driving factors,and the earthquake has an enhanced effect on other factors.

关键词： geodetector co-seismic landslide spatial pattern triggering factors interaction effects driving force engineering geology

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Seismotectonics and consequences of the 1930s large earthquakes in eastern Mazandaran,north of Iran

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Journal of Mountain Science 2022年第2期19卷 513-528页

作者： Mohsen EHTESHAMI-MOINABADI Ehsan ABBASI Ali SAKET Department of Sedimentary Basins and Petroleum Shahid Beheshti UniversityTehran ***Iran Natural Disaster Research Institute Tehran ***Iran

Early in the 1930 s,two relatively large earthquakes(Kosout,magnitude 6.8,and Talarrud,magnitude 5.8)shook the eastern Mazandaran,northern *** the historical and instrumental seismic activity of the eastern region of Mazandaran,little is known about the status of seismotectonics and consequences of these *** paper presents a compilation of available data from early reports of these earthquakes with new structural,geomorphic and local data on the effects of this earthquake,especially co-seismic landslides and liquefaction,to assess the seismotectonics and probable causative faults of the *** is proposed that the close times of occurrence of two earthquakes might be due to local loading or triggering effect of the first earthquake on the second *** many other instrumental earthquakes in the Central Alborz,it is difficult to find the exact causative faults of important earthquakes,however the Qadikola,Chachkam or North Alborz Fault have the potential of producing Kosout earthquake and the Lalehband fault is more promising for Talarrud ***,the structural complexity of the area is also discussed in the form of a hybrid tectonic *** this model,the boundary zone of thick-skinned and active thin-skinned domains has more structural complexity than outer ***-Badeleh Shahvar pop-up structure is bounded by major faults with thick-skinned deformation *** role of older inherited fault structures and their interaction with low-slope Neogene thrusts driven from north to south by crustal tectonics and deformation is ***-seismic landslides and rock falls have great potential to be investigated in the Alborz Range for identification of prehistoric earthquakes.

关键词： Seismotectonics co-seismic landslide Alborz Active Fault Earthquake

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