利用光学遥感影像光流场模型进行地表形变分析

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中文摘要：光学遥感影像像素偏移量追踪是反演同震形变场和监测滑坡的一种重要手段.基于相关性匹配的传统像素偏移量追踪方法,通过搜索相关性最强的匹配窗口估计中心像素的位移,计算效率低且在大梯度形变区域失相关现象严重,存在形变边界提取不精确的问题.为高效获取精确的地表形变,将计算机视觉领域的光流场模型引入像素偏移量追踪问题,提出适用于光学遥感影像反演地表形变的光流场方法,给出像素偏移量时序反演的加权改进算法.通过塔吉克斯坦同震形变场模拟实验,评估光流场方法估计地表形变场的可行性及其在最小可探测形变方面的性能;通过加州地震同震形变场反演和白格滑坡偏移量估计实验,讨论光流场方法的计算效率优势和形变区域提取的精确性;通过白格滑坡时序形变分析,进一步论述利用光流场方法估计大梯度形变的有效性和时序反演加权改进算法的鲁棒性.结果显示,相比于传统窗口相关性匹配方法,光流场方法的偏移量追踪精度为0.032像素,计算效率提升了 20倍左右,形变区范围提取精度提升了 25.9％;改进的加权时序反演算法将光学遥感影像东西向和南北向位移估计的不确定性分别降低了 16.2％和 12.4％.

外文标题：Analysis of Surface Deformations on the Basis of Optical Flow Field Models from Optical Remote Sensing Images

外文摘要：Objectives:Pixel offset tracking(POT)for optical remote sensing imagery is widely used to in-vert coseismic deformation fields and monitor landslides.Traditional pixel offset tracking method estimates the displacement of the central pixel by searching for the matching window with the highest correlation,which is computationally inefficient and suffers from inaccurate deformation boundary extraction due to the decoherence effects in the region with dynamical deformation.We introduce the optical flow field model commonly used in computer vision to the pixel offset tracking problem to obtain accurate surface deforma-tion efficiently.Methods:The optical flow field method applicable to optical remote sensing images and the improved inversion algorithm for the time series analysis are proposed to inverse the surface deformation.Experiments on the simulated coseismic deformation fields in Tajikistan are detailed to assess the feasibility and the minimum detectable deformation of the optical flow field method.The advantages of the proposed method over computational cost and deformation boundary extraction accuracy are illustrated by the co-seis-mic deformation field of the California earthquake and the displacement of the Baige landslide.Further-more,the performance on estimating large gradient deformation and the robustness of the improved time se-ries inversion algorithm are discussed by analyzing the time series deformation of the Baige landslide.Re-sults:The results show that compared with the traditional window correlation matching method,the optical flow field method has an offset tracking accuracy of 0.032 pixel,which improves the computational efficien-cy by about 20 times,and the accuracy of the deformation zone is improved by 25.9％.The time series weighted inversion algorithm reduces the uncertainties in the estimation of east-west and north-south dis-placements of optical remote sensing images by 16.2％and 12.4％,respectively.Conclusions:The pro-posed method alleviates the pixel offset tracking problem in the boundary region with large gradient defor-mation.

外文关键词：

optical flow field methodlandslidescoseismic deformationcomputational efficiencyweighted time series inversion algorithm

作者：

丁明涛、陈浩杰、李振洪、刘振江

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作者单位：

长安大学地质工程与测绘学院,陕西西安,710054

黄土科学全国重点实验室,陕西西安,710054

长安大学地学与卫星大数据研究中心,陕西西安,710054

自然资源部生态地质与灾害防控重点实验室,陕西西安,710054

智慧地球重点实验室,北京,100029

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关键词：

光流场方法滑坡同震形变计算效率加权时序反演算法

基金：

国家重点研发计划国家自然科学基金陕西省科技创新团队陕西省地学大数据与地质灾害防治创新团队(2022)智慧地球重点实验室基金高分专项川藏区域综合治理应用与规模化产业化示范项目中央高校基本科研业务费专项中央高校基本科研业务费专项

项目编号：

2021YFC300400423740272021TD-51KF2023YB04-0187-Y50G28-9001-22/23300102262203300102262902

出版年：

2024

DOI：

10.13203/j.whugis20240071

武汉大学学报(信息科学版)

武汉大学

武汉大学学报(信息科学版)

CSTPCD北大核心

影响因子：1.072

ISSN：1671-8860

年,卷(期)：2024.49(8)

参考文献量8