2017年“8.8”九寨沟地震滑坡自动识别与空间分布特征

2017年8月8日发生的7.0级九寨沟地震诱发九寨沟熊猫海附近产生大量的滑坡体,造成道路阻塞,严重影响地震应急救援进度。为快速准确地识别滑坡分布范围,本文在深入分析滑坡遥感影像特征的基础上,引入面向对象分析方法,实现了基于无人机影像的震后滑坡体的自动识别。通过多尺度分割算法获取滑坡多层次影像对象,利用SEaTH算法自动构建每一层次特征规则集,实现基于不同层次分析的滑坡体自动识别。分析滑坡体在地形、活动断层等因子中的空间分布特征,为地震滑坡预测与危险性评价奠定基础。与人工目视解译结果相比较,基于面向对象的滑坡自动识别方法提取精度可达94.8%,Kappa系数为0.827,在电脑配置相同的情况下,自动识别方法的效率是人工目视解译效率的一倍。空间分布特征分析表明,地震滑坡的空间分布与斜坡坡度、地形起伏度呈正相关关系,与地表粗糙度存在负相关关系,研究区滑坡体分布存在明显的断层效应。     

高分三号卫星全极化SAR影像九寨沟地震滑坡普查

基于光学遥感影像的区域滑坡普查易受云雾天气的影响,存在滑坡体调查不全面的问题,无法满足震后应急调查与恢复重建的需求。本文提出了一种极化SAR卫星数据滑坡普查方法,采用高分三号全极化SAR卫星影像数据,以九寨沟地震震区为实验区,在深入分析滑坡体和其他地物类型散射特征的基础上,融合极化特征、纹理特征和地形特征等多维特征信息,结合高分二号影像获取的训练样本,构建基于BP神经网络的全极化SAR数据滑坡自动识别模型,实现滑坡体的自动快速识别。与高分辨率光学影像与无人机航空影像目视解译结果相比较,总体识别精度为92.8%,Kappa系数为0.715,识别准确度满足地震应急实际应用的需求。研究成果可用于震区大区域滑坡体的普查,为后续开展无人机高分辨率影像滑坡体详查、灾后应急与景区恢复提供辅助信息支撑,并促进国产高分SAR卫星数据在防震减灾中的应用。     

基于地理信息二三维联合显示的地质灾害体遥感解译研究

滑坡是指在重力作用下,岩体或其他碎屑沿一个或多个破裂滑动面向下做整体滑动的现象。在我国乃至全世界范围内,滑坡常常给工农业生产以及人民生命财产造成巨大损失。但是由于滑坡所处位置具有危险性、隐蔽性的特点,在一定程度上给人们进行实地监测、预警带来了诸多不便。近年来,遥感和GIS技术飞速发展,尤其在自然灾害的识别、监测等领域正发挥越来越重要的作用。论文选择澜沧江中下游的部分沿岸区域作为研究区,针对目前滑坡灾害的研究现状,探讨在ARCGIS和ENVI软件平台上,基于30m空间分辨率的LandSat5TM影像和2.5m空间分辨率的Spot5卫星影像以及DEM数字高程影像进行二三维联合显示,提高目视识别验证的效果;并依次通过决策树分类,遥感影像的目视解译进行滑坡的粗提取;基于山影数据、分水线、汇水线、坡度分类等数据精确识别滑坡;并利用谷歌地图和实测的滑坡数据对结果进行验证,取到了较好的识别效果。     

地震滑坡高分辨率遥感影像识别

区域性地震滑坡信息获取目前主要通过遥感目视解译和计算机提取,存在主观性强、耗时费力、提取精度低等问题,导致难以满足灾后应急调查、灾情评估等方面的应用需求。采用资源三号、高分一号高分辨率遥感影像,以汶川震区为实验区,在地震滑坡灾害特征分析的基础上,通过多尺度最优分割方法构建多层次滑坡对象,融合光谱、纹理、几何等影像特征和地形特征信息建立多维滑坡识别规则集合,基于高分辨率影像认知模式与场景理解过程提出滑坡分层识别模型,从而实现地震滑坡空间分布及其滑源区、滑移区和堆积区的准确识别。实验区分析结果显示最低识别精度为81.89%,而滑坡的堆积区最容易被分辨,识别方法具有可推广性。研究成果可为灾后应急调查提供技术支撑,并促进国产高分辨率遥感卫星的地质灾害应用。     

泸定Ms 6.8地震对海螺沟冰川的影响应急分析

2022-09-05四川省甘孜州泸定县发生Ms 6.8地震,震中距离海螺沟冰川约10 km,海螺沟冰川受此次地震影响如何,受到社会广泛关切。利用多时相Landsat 8和Sentinel-2光学卫星影像,基于归一化雪覆盖指数对海螺沟冰川面积进行监测,并利用Sentinel-1雷达卫星影像,基于像素偏移追踪技术对海螺沟地震前和震中位移进行监测。结果表明,2016―2022年海螺沟冰川8月份面积呈波动变化趋势,与日平均最高气温具有负相关性,冰川运动速度与地形坡度和日平均最高气温具有正相关性。泸定地震未造成海螺沟冰川运动速度大范围显著增大,但对冰瀑布前缘区域扰动明显。震后冰崩直接致灾可能性较小,但增加了泥石流致灾风险。     

大型岩质滑坡形变历史回溯及其启示

大型岩质滑坡一般具有高位、隐蔽性强、高速远程等特点,往往造成严重的人员伤亡和财产损失。揭示其形变历史和发展演化规律,可以为类似滑坡灾害的早期识别提供参考。收集了近年来发生在中国大陆的5处典型大规模岩质滑坡滑前的多时相高精度遥感影像,通过对多时相高精度遥感影像的目视解译,对其形变迹象进行识别,并对其发展演化规律进行分析。发现大型岩质滑坡在发育演化过程中均会产生显著的地表变形迹象,这些形变信息可利用高分辨率光学遥感影像（亚米级）进行识别,变形的孕育演化时间可达数年甚至数10 a。大型岩质滑坡往往不具备“圈椅状”地貌特征,利用光学遥感影像对其早期识别的标志主要为坡体后源是否存在拉裂缝和坡体前缘是否存在局部滑塌。     

基于高分遥感的金沙江流域滑坡识别——以巴塘县王大龙村为例

金沙江流域因两岸地势陡峭、软弱岩层发育、降雨集中等,使得流域内滑坡灾害分布密集。高分辨率遥感是滑坡识别的重要手段,但通过目视解译法开展的大范围滑坡灾害识别,具有工作量大、效率低的特点。针对此问题,本文采用基于面向对象的分类方法,提出了利用滑坡灾害的光谱、形状、空间等特征进行区域内滑坡灾害的快速识别。同时,选取金沙江流域巴塘县王大龙村区段进行了滑坡识别提取试验,区域内利用面向对象分类方法识别出滑坡18处,其中12处与目视解译结果相同,一致性为75%;发现3处目视解译未识别出的隐蔽性滑坡。结果表明,该方法识别效果较好,可为后续的金沙江流域乃至川藏铁路沿线的大范围滑坡识别提取及滑坡编目工作提供参考。     

基于GEE的杭州湾慈溪段潮滩提取及时空变化分析

当前常见的潮滩遥感提取方法往往通过估算来确定潮滩的边界,难以保证较高的提取精度.本研究结合GEE遥感云计算平台和GIS技术,选用1990—2021年间共77景Landsat卫星影像,通过目视解译人工海岸线作为平均高潮线,利用水边线拟合平均低潮线,实现了对杭州湾南岸慈溪段的潮滩提取和面积估算,分析了潮滩区域时空变化.研究...     

基于无人机遥感的湖南金童山保护区滑坡监测

以湖南金童山国家级自然保护区内某条山区公路为例,利用无人机飞行获取高分辨率影像与高精度数字地形模型,使用基于面向对象的方法对滑坡信息进行提取,对无人机数据进行多尺度分割与光谱差异分割,选取了研究区内植被、道路、滑坡三类感兴趣地物的影像特征建立了规则集,充分利用了影像对象的光谱特征、几何特征、地形特征、空间关系,使用了阈值分类,隶属度函数与决策树分类方法.利用实地验证与基于无人机影像的目视解译对提取结果进行了精度评价,总体提取精度为94.75％,滑坡提取精度超过80％.该研究为快速监测山区内滑坡信息提供了借鉴.     

基于纹理特征的SAR影像各拉丹冬冰川信息提取

冰川面积是监测冰川变化信息的重要参数。本文以各拉丹东地区为例,根据冰川区域特有的纹理特征,选取时间间隔为35天的ENVISAT ASAR干涉对,利用灰度共生矩阵提取纹理特征,通过波段组合进行监督分类,进而提取研究区冰川面积。同时以Landsat TM光学影像为依据,评价利用纹理特征提取结果的精度。研究表明:基于纹理特征并利用SAR影像提取冰川面积的方法是可行的,为提取冰川信息提供了又一可靠手段。     

Mapping and Change Detection Study of Nepal-2015 Earthquake Induced Landslides

The devastating earthquake that struck Nepal in 25 April (Mw7.8) and 12 May (Mw7.3) 2015 have triggered numerous landslides and reactivated existing landslides extending over large areas. These two shocks mostly affected the northwest and northeast region of Kathmandu which accelerated large region along with southward up thrusting in the region. To detect the event of the landslides in time and space satellite images have been analysed using space remote sensing techniques like pseudo colour transformation technique and was employed to pre and post-earthquake images of the event to bring out only landslide affected areas from the image by masking the remaining part, where field based survey of the landslides provided information on real nature of it, slope and rock type. Surprisingly the observed mass movements are mostly belong to debris flow and rock fall types beginning from the top part of the ridge slope with south-westerly faces i.e. sun facing. Further, satellite images of different dates could be gathered which facilitated analysis on development of landslide with time. This study also revealed that the NE–SW trending geological faults have controlled the landslide occurrence especially in Ramche area and along the Bagmati river valley near Shital-chowk village on Kathmandu-Hetauda road.     

Spatial distribution and susceptibility analyses of pre-earthquake and coseismic landslides related to the Ms 6.5 earthquake of 2014 in Ludian,Yunan, China

On 3 August 2014, an earthquake struck Ludian County, Yunnan Province, China, which has caused a large number of coseismic landslides. Visual interpretation permitted 284 and 1053 landslides before and after the event to be mapped, respectively. This work attempted to analyse these two kinds of landslides. Conditioning factors, such as slope angle, aspect, curvature, elevation, distance from drainages, intensity and lithology, and the index of Landslide Number Density (LND) were used to describe the spatial distribution of these landslides. Then, the pre-earthquake and coseismic landslide susceptibility maps were produced using the information value model. The areas under curve are 84.73 and 77.05%, for the pre-earthquake and coseismic landslides, respectively. The results show that the LND values as well as the information values of coseismic landslides are larger than those of the pre-earthquake case. This also indicates that this Ludian earthquake has a relatively larger ability to trigger landslides.     

珠峰及周边地区强震影响垂直形变特征研究

2015年尼泊尔地震对珠穆朗玛峰高程的影响,近年一直受到全世界关注.2020年珠穆朗玛峰高程测量在珠穆朗玛峰及周边地区布设了高精度的全球导航卫星系统(global navigation satellite system,GNSS)形变监测网,收集了1999-2020年跨喜马拉雅山脉的32个连续运行参考站(continu...     

基于不同斜坡单元划分方法和BP神经网络的泥石流易发性评价

选取合适的评价单元是泥石流易发性评价的关键,为探索斜坡单元不同划分方法对泥石流易发性评价结果的影响,本文以泥石流多发地东川区为例,对比分析了水文分析法和曲率分水岭法两种斜坡单元划分方法在泥石流易发性评价中的效果。首先在解译泥石流点的基础上,采用不同划分方法的斜坡单元作为评价单元,然后对初步选取的指标因子进行多重共线性和贡献率分析,以完善指标因子体系,最后构建基于BP神经网络的泥石流易发性评价模型。结果表明,泥石流极高和高易发区主要集中分布于研究区小江河谷和金沙江南岸,该地区地质环境脆弱,危险性较高。基于曲率分水岭法的易发性模型AUC值为0.865 8,高于水文分析法的0.815 3,表明采用曲率分水岭法划分的斜坡单元更适用于研究区泥石流易发性评价。     

基于ArcGIS的土壤稳定性评估——以张飞庙景区为例

近年来山体滑坡以及泥石流等自然灾害事故频发,为能够减少灾害的影响,需要对特定区域的土壤稳定性进行调查或评估。传统对于土壤稳定性的评估一般是采用实地调查的方法,这种方法不仅效率低,而且对事故多发地段对于调查人员的安全影响较大。因此论文利用ArcGIS软件,根据DEM数据以及地区矢量图,通过计算坡度或坡向等方法对云阳县张飞庙景区进行土壤稳定性评估。运用该方法能够快速得到张飞庙景区土壤稳定性情况,确定不稳定区域范围,具有较强的实效性和实用性。     

The spatial response pattern of coseismic landslides induced by the 2008 Wenchuan earthquake to the surface deformation and Coulomb stress change revealed from InSAR observations

The 2008 Mw 7.9 Wenchuan earthquake triggered plenty of coseismic giant landslides, which resulted in almost one third of total fatalities and economic losses during the event. Previous studies investigated the spatial relations between landslide distribution and topographic and seismic factors such as elevation, slope aspect, distance from rupture trace and seismic intensity. However, few studies are performed exploring the effects of coseismic surface deformation and Coulomb stress change on triggering landslides due to lack of adequate deformation observation data and stress calculation model for slope failure. In this study, we develop an envelope method to map an entire coseismic deformation field in both near- and far-field areas of seismic faults through the data fusion from InSAR and pixel offset-tracking (POT) techniques. The change in static Coulomb stress (SCS) acting on coseismic landsliding surface caused by the event is determined using the faulting model derived from the joint inversion of InSAR and GPS data, and also with the use of the elastic half-space dislocation theory and the generalized Hook’s law. The analysis suggests the spatial response pattern of seismic landslides to the coseismic ground motion and stress change, especially in the vicinity of fault rupture trace. The landslide density dramatically rises with the stress increase within the range from Yingxiu to Beichuan areas along the major surface rupture. Moving further and eastward along the fault strike, most of large landslides are triggered as the zone of positive SCS change narrows. Moreover, the high-magnitude surface displacements are possibly responsible for the giant landsliding events in the easternmost section. From the analysis of the stress transfer, the occurrence of landslides in the study area is largely controlled by the Yingxiu-Beichuan fault with overwhelming rupture length and fault slip, yet the Pengguan fault indeed shows dominance in the area between the two faults. The results show that coseismic surface deformation (derived from InSAR data in this study) and static Coulomb stress change can serve as two significant controlling factors on seismic landslide distribution and that the stress factor seems more significant in the vicinity of surface rupture.