基于多时相光学遥感影像亚像素相关的边坡监测——以溪洛渡电站为例

doi:10.13474/j.cnki.11-2246.2024.0107

测绘通报 ›› 2024, Vol. 0 ›› Issue (1): 38-43,108.doi: 10.13474/j.cnki.11-2246.2024.0107

基于多时相光学遥感影像亚像素相关的边坡监测——以溪洛渡电站为例

叶江¹, 李才艺¹, 高红旗², 徐卫红², 向南松¹

1. 成都理工大学地球科学学院, 四川成都 610059;
2. 浙江华东测绘与工程安全技术有限公司, 浙江杭州 310014

收稿日期:2023-04-08 出版日期:2024-01-25 发布日期:2024-01-30
作者简介:叶江(1978—),男,博士,副教授,主要研究方向为卫星摄影测量与精密工程测量。E-mail:yejiang@cdut.edu.cn
基金资助:
四川省科技厅自然科学面上项目(2019YJ0504);国家自然科学基金(42271461)

Sub-pixel correlation-based slope monitoring using multi-temporal optical remote sensing images: a case study of Xiluodu hydropower station

YE Jiang¹, LI Caiyi¹, GAO Hongqi², XU Weihong², XIANG Nansong¹

1. College of Geosciences, Chengdu University of Technology, Chengdu 610059, China;
2. Zhejiang Huadong Surveying, Mapping and Engineering Safety Technology Co., Ltd., Hangzhou 310014, China

Received:2023-04-08 Online:2024-01-25 Published:2024-01-30

摘要/Abstract

摘要： 水电站高边坡监测是水电站灾害防治中的关键问题,基于卫星遥感技术进行库区滑坡监测是解决该问题的重要手段之一。利用卫星影像亚像素相关性算法获取地表形变位移场,能够克服SAR影像失相关因素,在水电站边坡监测中具有重大的应用潜力。本文以溪洛渡电站2015—2019年5期Google Earth影像和2019—2022年4期Sentinel-2影像为数据源,采用相位相关算法计算了边坡形变量,通过构建一次多项式曲面拟合模型去除轨道误差等趋势性误差,获取了2016、2017和2019年溪洛渡电站下游边坡形变值。分析显示,两种影像提取得到的边坡形变量具有相同的变化趋势,均与谷幅实测数据吻合较好。本文结果验证了基于多时相遥感数据将亚像素相关性匹配技术运用于大型水电站边坡形变监测的可行性。

关键词: 边坡监测, 光学遥感影像, 亚像素相关, 趋势误差

Abstract: The monitoring of high slope in hydropower plant is a key issue in disaster prevention and control of hydropower plant. The use of satellite remote sensing technology for reservoir landslide monitoring is an important way to solve the problem. The use of subpixel correlation algorithm to obtain the ground deformation displacement field can overcome the phase decorrelation factors in SAR images, and has great potential application in the monitoring of hydropower station slopes. In this paper, Google Earth images from 2015 to 2019 and Sentinel-2 images from 2019 to 2022 were used as data sources, and the slope deformation variables were calculated by the phase correlation algorithm. The trend error such as orbit error was removed by constructing a first-order polynomial surface fitting model, and the slope deformation values of the downstream slope of Xiluodu Station in 2016, 2017, and 2019 were obtained. The analysis showed that the slope deformation values obtained from two images had the same trend, and were in good agreement with the measured data of valley width. The results of this paper verified the feasibility of applying the subpixel correlation matching technique, based on multi-temporal remote sensing data, for monitoring the slope deformation of large hydropower plants.

Key words: slope monitoring, optical remote sensing images, subpixel correlation, trend errors

中图分类号:

P237

叶江, 李才艺, 高红旗, 徐卫红, 向南松. 基于多时相光学遥感影像亚像素相关的边坡监测——以溪洛渡电站为例[J]. 测绘通报, 2024, 0(1): 38-43,108.

YE Jiang, LI Caiyi, GAO Hongqi, XU Weihong, XIANG Nansong. Sub-pixel correlation-based slope monitoring using multi-temporal optical remote sensing images: a case study of Xiluodu hydropower station[J]. Bulletin of Surveying and Mapping, 2024, 0(1): 38-43,108.

参考文献

[1] BICKEL V,MANCONI A,AMANN F. Quantitative assessment of digital image correlation methods to detect and monitor surface displacements of large slope instabilities[J]. Remote Sensing,2018,10(6)13.
[2] 李晓恩,周亮,苏奋振,等. InSAR技术在滑坡灾害中的应用研究进展[J]. 遥感学报,2021,25(2): 614-629.
[3] LEPRINCE S,BARBOT S,AYOUB F,et al. Automatic and precise orthorectification,coregi stration,and subpizel correlation of satellite images,application to ground deformati on measurements[J]. IEEE Transactions on Geosaience and Remote Sensing,2007,45(6): 1529-1558.
[4] DAS S,SHARMA M C. Glacier surface velocities in the Jankar Chhu Watershed,western Himalaya,India: Study using Landsat time series data (1992—2020)[J]. Remote Sensing Applications: Society and Environment,2021,24(80):100615.
[5] ZHENG Z J,DU S,TAUBENBOCK H,et al. Remote sensing techniques in the investigation of aeolian sand dunes: a review of recent advances[J]. Remote Sensing of Environment,2022,271:112913.
[6] AHMAD N,SHAFIQUE M,HUSSAIN M L. Landslide assessment by using multi-temporal UAV datasets: a case study in northern Pakistan[J]. Arabian Journal of Geosciences,2021,14(18):1855.
[7] 黄俊. 改进量子粒子群算法优化的SVM边坡形变预测研究[D]. 赣州: 江西理工大学,2020.
[8] 柳志丹. 四川金沙江溪洛渡水电站边坡治理技术[J]. 黄河水利职业技术学院学报,2014,26(1):5-8.
[9] 方俊睿. 基于Google Earth的陆家嘴城市高度信息快速提取和历史变化分析[D]. 上海: 上海师范大学,2019.
[10] TÉLLEZ-VELÁZQUEZ A,CRUZ-BARBOSA R. On the feasibility of fast fourier transform separability property for distributed image processing[J]. Scientific Programming,2021:1-8.
[11] 宋豪峰. 基于光学和SAR影像偏移量估计的区域滑坡时序形变监测和应用[D].广州:广州大学,2021.
[12] 彭颖,李鹏. 融合光学与SAR遥感影像的同震地表三维形变监测适用性研究[J]. 测绘与空间地理信息,2019,42(10): 86-89.
[13] JIANG X,YU J,JIANG J. Research on feature point generation and matching method optimization in image matching algorithm[J/OL]. Wireless Networks.2021-07-19[2023-03-10].https://link.springer.com/article/10.1007/s11276-021-02688-x?utm_source=xmol&utm_content=meta.
[14] ANA M R,MARC P D,ARTHUR D,et al. Measurement of ground displacement from optical satellite image correlation using the free open-source software MicMac[J]. ISPRS Journal of Photogrammetry and Remote Sensing,2015,100:48-59.
[15] 朱建军,李志伟,胡俊. InSAR形变监测方法与研究进展[J]. 测绘学报,2017,46(10): 1717-1733.
[16] CAPOROSSI D,MAZZANTI P,BOZZANO F. Digital image vorrelation (DIC) snalysis of the 3 December 2013 Montescaglioso landslide (Basilicata,southern Italy): results from a multi-dataset investigation[J]. ISPRS International Journal of Geo-Information,2018,7(9):372.

基于多时相光学遥感影像亚像素相关的边坡监测——以溪洛渡电站为例

Sub-pixel correlation-based slope monitoring using multi-temporal optical remote sensing images: a case study of Xiluodu hydropower station

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