联合哨兵2号和Landsat 8估计白格滑坡时序偏移量

Time-Series Offset Tracking of the Baige Landslide Based on Sentinel-2 and Landsat 8

光学影像时序偏移量跟踪是滑坡监测的一种重要手段。针对单平台光学时序偏移量估计时间采样率不足的问题,利用多源时序偏移量估计获取了白格滑坡2014-11—2018-09期间的形变。首先,基于哨兵2号和陆地卫星(Landsat)8分别进行单平台和双平台下的时序偏移量计算。其次,以稳定区域统计值和交叉验证两种方式进行精度评定。然后,基于双平台下的时序形变对滑坡进行阶段划分,并探讨其成因。结果表明:(1)双平台时序偏移量精度优于单平台,哨兵2号在东西向和南北向的精度分别提升3.02%和5.37%,Landsat 8在两方向上的精度分别提升了3.61%和0.40%;期间的最大累计形变和最大平均形变速率分别为42.90 m和9.06 m/a。(2)白格滑坡可划分为初始、等速和加速(初加速和中加速)3阶段,截至2018-02-05已进入中加速阶段。(3)时序形变与降雨量相关性系数高达0.88。

Objectives:Time-series offset tracking is a critical technique for landslide monitoring with optical images,which has been applied worldwide successfully in the recent years.The continued monitoring of landslide can provide early warning and emergency information for the nature hazard prevention.However,the resolution in the temporal domain is restricted by the single-platform datasets,especially in the case of bad weather.To solve this issue,we use the multi-source optical images,including Sentinel-2 and Landsat 8 to generate the long time-series deformation of landslides.The high resolution of deformation in the temporal domain can help us know more about the development process of the landslide.Methods:The method is executed based on the idea of small baseline subset(SBAS)in the interferometric synthetic aperture radar(InS AR)technique,aiming to reduce the influence of the temporal baseline and noise on the signal noise ratio(SNR).Meanwhile,to obtain time-series deformation of the multi-platform optical images,we use a weighted singular value decomposition(SVD)method to obtain the time-series deformation of the multi-platform optical images.11 Sentinel-2 datasets and 16 Landsat 8 datasets are used to generate two-dimensional horizontal time-series deformations of the Baige landslide from 2014-11 to 2018-09.Firstly,we calculate the time-series offset tracking of the single platform,i.e.,Sentinel-2 and Landsat 8,and the dual-platform by considering the selection of the image pair,search window size,step length,and the threshold of SNR respectively.And a time-series deformation of 27 images are obtained with offset tracking technique of the dual-platform.Secondly,the accuracy of the results for the single-platform and the dual-platforms is evaluated by two commonly used methods:Stable area statistics with a priori knowledge and cross-validation of independent datasets.Then,the developmental stages of the Baige landslide is divided based on the long time-series deformation of the dual-platform,the creep deformation theory,and the tangential angle of the time-series curve.Finally,the relationship between precipitation and deformation is discussed to analyze the causes of the landslide.Results:The results show that:(1)The time-series deformation of the dual-platform can obtain more details compared the results of the single platform.(2)The deformation accuracy of the dual-platform is higher than that of the single platform.For example,the improvements of the dual-platform in the east-west direction and the north-south direction are 3.02%and 5.37%respectively compared to the Sentinel-2.In the Landsat 8 case,the results are 3.61%and 0.40%respectively.During the time span,the maximum accumulated deformation and the deformation rate reach to 42.90 in and 9.06 m/a respectivley.In addition,the deformation accuracy of the Sentinel-2 is higher than that of the Landsat 8 in the similar situation of observations.(3)The pre-event of the Baige landslide can be divided into the initial stage,the uniform stage,the initial acceleration,and the medium-term acceleration.The corresponding average deformation rates of each stage are 7.05 mm/d,10.27 mm/d,26.80 mm/d,and65.79 mm/d respectively.The landslide is going through the medium-term acceleration stage until the 5 th,Feb.2018.(4)the correlation between the deformation and precipitation is 0.88,which indicates that heavy rainfall is one of the major causes for the B aige landslide.Conclusions:Although the deformation resolution of the multi-platform optical image is higher than that of the single platform,the fusion accuracy is limited by the accuracy of different individual platforms caused by the sensitivity for the topography.Hence,in the future work,we will focus on the combined estimation of the multi-platform based on the variance component estimation.