选取厦门新机场填海区为研究对象,收集2016年12月至2018年11月期间的56景升轨Sentinel-1雷达影像,采用多时相In SAR(Multi-temporal In SAR,MT-InSAR)技术,获取了填海区由软土层固结压缩引起的沉降场。针对不同填海时间的场地,探讨其形...选取厦门新机场填海区为研究对象,收集2016年12月至2018年11月期间的56景升轨Sentinel-1雷达影像,采用多时相In SAR(Multi-temporal In SAR,MT-InSAR)技术,获取了填海区由软土层固结压缩引起的沉降场。针对不同填海时间的场地,探讨其形变特征及原因,并对比分析了In SAR监测结果与同期水准测量结果。结果表明,一期填海区沉降主要发生在2017年6月份以前,后期已趋于平稳,监测点最大沉降速率为-43.6mm/yr;二期填海区场地整体表现出不同程度的沉降,主要沉降区位于新近完成填海的区域,监测点最大沉降速率为-129.1mm/yr,且场地沉降量与淤泥厚度之间具有较高的正相关性。同时In SAR与水准数据具有较高的一致性,验证了MT-InSAR技术在填海区沉降监测方面的适用性,后续可为机场沉降灾害的预防和控制提供科学依据。展开更多
Rock glaciers are typical periglacial landforms with tongue or lobate morphological shapes and characterized by the distinct front,lateral margins,and often by ridge-and-furrow surface topography textures as well as k...Rock glaciers are typical periglacial landforms with tongue or lobate morphological shapes and characterized by the distinct front,lateral margins,and often by ridge-and-furrow surface topography textures as well as kinematic characteristics,widely distributed in alpine environments.Multitemporal Synthetic aperture radar interferometry(MT-InSAR),is a remote sensing technique with demonstrated effectiveness for detecting landform kinematics.However,its application to rock glaciers is challenged by temporal decorrelation and atmospheric phase noises due to complex topography and snow cover.We designed a quadtree segmentation and parallel computing-based MT-InSAR method to improve the quality and efficiency of deformation measurement of rock glaciers.We applied the method to a rock glacier inventory of the Nyainqentanglha Range,China,derived from high-resolution Gaofen-2 images,to quantify the activity rate of each rock glacier.Results showed that 32.1%(6,389)of the identified rock glaciers exhibited slope-parallel deformation rates exceeding 100 mm/y.The activities of the rock glaciers exhibited strong correlations with their distance to glaciers,precipitation,freeze-thaw magnitude,and permafrost occurrence probability.The results demonstrate the effectiveness of the developed segmentation-parallel MT-InSAR method for monitoring rock glacier deformation over a large region.展开更多
Slow-moving landslides are widespread in the Mediterranean area,causing damage to the exposed facilities and economic losses in many countries.The recognition of slow-moving landslides in urban areas is always a diffi...Slow-moving landslides are widespread in the Mediterranean area,causing damage to the exposed facilities and economic losses in many countries.The recognition of slow-moving landslides in urban areas is always a difficult task to deal with because the presence of buildings,infrastructures,and human activities usually conceals the morphological signs of these landslide activities.So,in the last decades,numerous researchers have shown new methodologies to deepen the studies of similar instability phenomena.The present research is based on an integrated approach to investigate the landslide boundaries,type of movement,failure surface depth,and vulnerability state of buildings in Rota Greca Village(Calabria region,southern Italy) affected by a slowmoving landslide.For this purpose,multi-source data were acquired through geological and geomorphological surveys,recognition of landslide-induced damage on the built environment,subsurface investigations(e.g.,continuous drill boreholes,Standard Penetration Test,Rock Quality Designation index and inclinometer monitoring),laboratory tests(direct shear tests on undisturbed samples),geophysical survey,and InSAR-derived map of deformation rates.The complete integration of multi-source data allowed for the construction of reliable landslide modelling with relative geotechnical properties.In addition,the cross-comparison between surface deformation data by SAR images and severity damage level collected on the exposed buildings enabled to obtain the vulnerability map of the built area.In particular,the achieved goals highlighted two failure surfaces at about-13 and-25 m depth,causing a high vulnerability value for the buildings allocated in the central portion of the Rota Greca Village.The knowledge acquired by the multi-approach can be used to manage and implement appropriate landslide risk mitigation strategies,providing helpful advice and best practices to state-run organisations and stakeholders for landslide management in urban sites.展开更多
Landslide susceptibility map(LSM)is a crucial tool for managing landslide hazards and identifying potential landslide areas.However,current LSMs rely primarily on static landslide-related factors with little variation...Landslide susceptibility map(LSM)is a crucial tool for managing landslide hazards and identifying potential landslide areas.However,current LSMs rely primarily on static landslide-related factors with little variation over several decades,thereby overlooking the movement of slopes and failing to capture landslide dynamics.The long-term ground deformation map(GDM)derived from multi-temporal interferometric synthetic aperture radar(MT-InSAR)can effectively address the shortcomings.Fengjie County is an important area for geohazard management in the Three Gorges Reservoir Area(TGRA),China.Landslides in this area,however,cause significant socio-economic loss due to geological,tectonic,climatic,and anthropological factors.This research aims to integrate random forest(RF)with MT-InSAR to generate a landslide dynamic susceptibility map(LDSM)for Fengjie County,enhancing the reliability of landslide risk management.First,the RF model was employed to generate a static LSM,whereas MT-InSAR was utilized to obtain the GDM of the study area from January 2020 to June 2023.The static LSM and the GDM were subsequently integrated using a dynamic weight matrix to derive the LDSM.Our analysis covered a temporal framework spanning three years,focusing on spatiotemporal changes in landslide susceptibility levels and the influence of climate factors.Compared with the static LSM,the LDSM can promptly identify moving landslide areas,reduce high landslide susceptibility areas,and achieve greater accuracy.Moreover,the spatiotemporal changes in landslide susceptibility are regulated by the total annual rainfall,with wet years being more conducive to landslides than dry years.The proposed LDSM offers useful insights for the dynamic prevention and refined management of landslide hazards in the TGRA,significantly enhancing the resilience in this region.展开更多
基金funded by the National Natural Science Foundation of China[grant number 4217011817]State Key Laboratory of Tibetan Plateau Earth System Environment and Resources(TPESER)Youth Innovation Key Program[grant number TPESER-QNCX2022ZD-04].
文摘Rock glaciers are typical periglacial landforms with tongue or lobate morphological shapes and characterized by the distinct front,lateral margins,and often by ridge-and-furrow surface topography textures as well as kinematic characteristics,widely distributed in alpine environments.Multitemporal Synthetic aperture radar interferometry(MT-InSAR),is a remote sensing technique with demonstrated effectiveness for detecting landform kinematics.However,its application to rock glaciers is challenged by temporal decorrelation and atmospheric phase noises due to complex topography and snow cover.We designed a quadtree segmentation and parallel computing-based MT-InSAR method to improve the quality and efficiency of deformation measurement of rock glaciers.We applied the method to a rock glacier inventory of the Nyainqentanglha Range,China,derived from high-resolution Gaofen-2 images,to quantify the activity rate of each rock glacier.Results showed that 32.1%(6,389)of the identified rock glaciers exhibited slope-parallel deformation rates exceeding 100 mm/y.The activities of the rock glaciers exhibited strong correlations with their distance to glaciers,precipitation,freeze-thaw magnitude,and permafrost occurrence probability.The results demonstrate the effectiveness of the developed segmentation-parallel MT-InSAR method for monitoring rock glacier deformation over a large region.
基金supported by the MIUR-ex 60% Project(responsibility of Fabio Ietto)。
文摘Slow-moving landslides are widespread in the Mediterranean area,causing damage to the exposed facilities and economic losses in many countries.The recognition of slow-moving landslides in urban areas is always a difficult task to deal with because the presence of buildings,infrastructures,and human activities usually conceals the morphological signs of these landslide activities.So,in the last decades,numerous researchers have shown new methodologies to deepen the studies of similar instability phenomena.The present research is based on an integrated approach to investigate the landslide boundaries,type of movement,failure surface depth,and vulnerability state of buildings in Rota Greca Village(Calabria region,southern Italy) affected by a slowmoving landslide.For this purpose,multi-source data were acquired through geological and geomorphological surveys,recognition of landslide-induced damage on the built environment,subsurface investigations(e.g.,continuous drill boreholes,Standard Penetration Test,Rock Quality Designation index and inclinometer monitoring),laboratory tests(direct shear tests on undisturbed samples),geophysical survey,and InSAR-derived map of deformation rates.The complete integration of multi-source data allowed for the construction of reliable landslide modelling with relative geotechnical properties.In addition,the cross-comparison between surface deformation data by SAR images and severity damage level collected on the exposed buildings enabled to obtain the vulnerability map of the built area.In particular,the achieved goals highlighted two failure surfaces at about-13 and-25 m depth,causing a high vulnerability value for the buildings allocated in the central portion of the Rota Greca Village.The knowledge acquired by the multi-approach can be used to manage and implement appropriate landslide risk mitigation strategies,providing helpful advice and best practices to state-run organisations and stakeholders for landslide management in urban sites.
基金supported by the National Science Fund for Distinguished Young Scholars(Grant No.42225702)the Maria Skłodowska-Curie Action(MSCA)-UPGRADE(mUltiscale IoT equipPed lonG linear infRastructure resilience built and sustAinable DevelopmEnt)project-HORIZON-MSCA-2022-SE-01(Grant No.101131146)。
文摘Landslide susceptibility map(LSM)is a crucial tool for managing landslide hazards and identifying potential landslide areas.However,current LSMs rely primarily on static landslide-related factors with little variation over several decades,thereby overlooking the movement of slopes and failing to capture landslide dynamics.The long-term ground deformation map(GDM)derived from multi-temporal interferometric synthetic aperture radar(MT-InSAR)can effectively address the shortcomings.Fengjie County is an important area for geohazard management in the Three Gorges Reservoir Area(TGRA),China.Landslides in this area,however,cause significant socio-economic loss due to geological,tectonic,climatic,and anthropological factors.This research aims to integrate random forest(RF)with MT-InSAR to generate a landslide dynamic susceptibility map(LDSM)for Fengjie County,enhancing the reliability of landslide risk management.First,the RF model was employed to generate a static LSM,whereas MT-InSAR was utilized to obtain the GDM of the study area from January 2020 to June 2023.The static LSM and the GDM were subsequently integrated using a dynamic weight matrix to derive the LDSM.Our analysis covered a temporal framework spanning three years,focusing on spatiotemporal changes in landslide susceptibility levels and the influence of climate factors.Compared with the static LSM,the LDSM can promptly identify moving landslide areas,reduce high landslide susceptibility areas,and achieve greater accuracy.Moreover,the spatiotemporal changes in landslide susceptibility are regulated by the total annual rainfall,with wet years being more conducive to landslides than dry years.The proposed LDSM offers useful insights for the dynamic prevention and refined management of landslide hazards in the TGRA,significantly enhancing the resilience in this region.
