类尺度不变特征变换的陆探一号卫星影像初配准算法——以积石山地震为例

王文昕, 杨德芳, 李龙, 李文军, 冯光财, 贺礼家, 熊志强, 李宁, 蒋泓波, 罗吴林洪, 汪亿林

王文昕, 杨德芳, 李龙, 李文军, 冯光财, 贺礼家, 熊志强, 李宁, 蒋泓波, 罗吴林洪, 汪亿林. 类尺度不变特征变换的陆探一号卫星影像初配准算法——以积石山地震为例[J]. 武汉大学学报 ( 信息科学版), 2025, 50(2): 377-390. DOI: 10.13203/j.whugis20240087
引用本文: 王文昕, 杨德芳, 李龙, 李文军, 冯光财, 贺礼家, 熊志强, 李宁, 蒋泓波, 罗吴林洪, 汪亿林. 类尺度不变特征变换的陆探一号卫星影像初配准算法——以积石山地震为例[J]. 武汉大学学报 ( 信息科学版), 2025, 50(2): 377-390. DOI: 10.13203/j.whugis20240087
WANG Wenxin, YANG Defang, LI Long, LI Wenjun, FENG Guangcai, HE Lijia, XIONG Zhiqiang, LI Ning, JIANG Hongbo, LUO Wulinhong, WANG Yilin. Image Initial Registration Algorithm for Lutan-1 Satellite Based on Scale-Invariant Feature Transform-Like Algorithm— A Case Study of the Jishishan Earthquake[J]. Geomatics and Information Science of Wuhan University, 2025, 50(2): 377-390. DOI: 10.13203/j.whugis20240087
Citation: WANG Wenxin, YANG Defang, LI Long, LI Wenjun, FENG Guangcai, HE Lijia, XIONG Zhiqiang, LI Ning, JIANG Hongbo, LUO Wulinhong, WANG Yilin. Image Initial Registration Algorithm for Lutan-1 Satellite Based on Scale-Invariant Feature Transform-Like Algorithm— A Case Study of the Jishishan Earthquake[J]. Geomatics and Information Science of Wuhan University, 2025, 50(2): 377-390. DOI: 10.13203/j.whugis20240087

类尺度不变特征变换的陆探一号卫星影像初配准算法——以积石山地震为例

基金项目: 

国家自然科学基金 42174039

详细信息
    作者简介:

    王文昕,硕士生,研究方向为InSAR技术滑坡识别与监测。wangwx@csu.edu.cn

    通讯作者:

    冯光财,博士,教授。fredgps@csu.edu.cn

Image Initial Registration Algorithm for Lutan-1 Satellite Based on Scale-Invariant Feature Transform-Like Algorithm— A Case Study of the Jishishan Earthquake

  • 摘要:

    陆探一号(Lutan-1, LT-1)合成孔径雷达(synthetic aperture radar,SAR)卫星是中国首个以干涉为核心任务的L波段全极化民用SAR卫星星座,适用于地震、滑坡等灾害的监测和应急响应。然而,受该卫星实时轨道数据不精确的影响,LT-1 SAR影像的初始配准精度不高,容易导致配准失败,影响影像自动化处理效率。针对该问题,提出基于类尺度不变特征变换的LT-1影像初配准算法和处理策略,旨在提高其配准成功率。以2023⁃12⁃18甘肃临夏回族自治州积石山Ms 6.2地震为例验证算法的可靠性,将配准成功率由34.5%提高到100%,成功获取了该地震的同震形变场,同时也获取了Sentinel-1A/B升、降轨形变结果,用于对LT-1结果进行精度验证和分析。综合LT-1和Sentinel-1A/B的结果表明,该地震以抬升为主,最大抬升量达6.3 cm,属于逆冲型地震。通过震前Sentinel-1升、降轨时序形变结果分别识别出195和179个滑坡,并发现该地震触发的草滩村液化滑坡-泥流在震前已出现明显形变,形变速率超过9 mm/a。并讨论了LT-1影像分幅不规则对算法有效性的影响,展望了LT-1卫星在地震及同震地质灾害监测领域的应用潜力。

    Abstract:
    Objectives 

    The Lutan-1 (LT-1) synthetic aperture radar (SAR) satellite, the first group of L-band fully polarimetric civilian SAR satellites in China with interferometry as its core mission, is suitable for monitoring and emergency response to disasters such as earthquakes and landslides. However, due to the inaccuracy of the satellite's real-time orbit data, the initial registration precision of the LT-1 SAR images is not high, which easily leads to registration failure and affects the efficiency of the image-automated registration process.

    Methods 

    In response to this issue, this study proposes a LT-1 image initial registration method and processing strategy based on a scale invariant feature transform like (SIFT-Like) algorithm to enhance the registration success rate. Taking the Ms 6.2 earthquake in Jishishan, Gansu, on December 18, 2023, as an example, the algorithm’s reliability was verified, with the registration success rate increased from 34.5% to 100%, successfully obtaining the coseismic deformation field of this earthquake. Furthermore, the coseismic deformation results of Sentinel-1A/B for this earthquake were also acquired for precision validation and analysis of the LT-1 results.

    Results 

    Integration of LT-1 and Sentinel-1A/B results indicate that the earthquake was primarily characterized by uplift, with a maximum uplift of 6.3 cm, classifying it as a thrust earthquake. Using pre-earthquake Sentinel-1 ascending and descending orbit interferometric results, 195 and 179 landslides were respectively identified, and it was observed that the liquefaction landslide-debris flow triggered by the earthquake in Caotan Village had exhibited significant deformation before the event, with a deformation rate exceeding 9 mm/a. And the impact of irregular segmentation of LT-1 images on algorithm effectiveness is discussed, and the potential applications of LT-1 satellites in earthquake and geological hazard monitoring are highlighted.

    Conclusions 

    The proposed algorithm effectively eliminates the registration issue of the LT-1 satellite. With the increasing archive data of LT-1, this algorithm can better highlight its advantages. Combining the LT-1 data and the algorithm can better serve the deformation monitoring and emergency response of earthquakes and geological disasters in the future.

  • 感谢青海省自然资源遥感中心提供的Lutan⁃1卫星数据、欧洲航天局提供的Sentinel‐1A/B数据,本文中图件采用GMT 6.4.0绘图[35]。
    http://ch.whu.edu.cn/cn/article/doi/10.13203/j.whugis20240087
  • 图  1   基于SIFT⁃Like算法获取特征点初始偏移量的LT⁃1差分数据处理流程

    Figure  1.   Differential Data Processing Flow of LT⁃1 Based on Initial Offset of Feature PointsObtained by SIFT⁃Like Algorithm

    图  2   LT‐1和Sentinel‐1卫星数据覆盖图

    Figure  2.   Coverage Map of LT-1 and Sentinel-1 Satellite Data

    图  3   配准后SAR影像的整体干涉图及细部干涉图

    Figure  3.   Overall Interferograms and Detailed Interferograms of Registered SAR Images

    图  4   初配准时主、从影像特征点匹配

    Figure  4.   Feature Points Matching of Initial Registration for Master and Slave Images

    图  5   去除地形相位时主SAR影像与DEM模拟SAR影像特征点匹配

    Figure  5.   Matching of Feature Points Between Master SAR Image and SAR Image Simulated by DEMDuring Terrain Phase Removal

    图  6   几何配准法、SIFT⁃Like算法与目视法初始偏移量差值

    Figure  6.   Difference in Initial Offset Between Geometric Registration Method, SIFT-Like Algorithm,and Visual Inspection Method

    图  7   积石山地震LT-1卫星升轨同震形变场

    Figure  7.   Coseismic Deformation Field of the Jishishan Earthquake from LT-1 Satellite Ascending Orbit

    图  8   积石山地震Sentinel⁃1卫星数据的同震形变场

    Figure  8.   Coseismic Deformation Field of the Jishishan Earthquake Using Sentinel-1 Satellite Data

    图  9   积石山地震震前Sentinel-1卫星数据的时序形变

    Figure  9.   Time Series Deformation of Sentinel-1 Satellite Data Before the Jishishan Earthquake

    图  10   LT⁃1升轨、Sentinel⁃1升、降轨形变量统计直方图

    Figure  10.   Statistical Histogram of Displacement for LT-1 Ascending Orbit, Sentinel-1 Ascendingand Descending Orbits

    图  11   AB剖线LT⁃1升轨、Sentinel⁃1升轨同震形变曲线图

    Figure  11.   Coseismic Deformation Curves of Ascending Orbit and Sentinel-1 Ascending and Descending Orbits for AB Profile Line

    图  12   滑坡-泥流震前形变速率图、滑源区形变速率图以及时序形变图

    Figure  12.   Landslide-Debris Flow Pre-Seismic Deformation Rate Map, Deformation Rate Map of the Slip Source Area, and Temporal Deformation Map

    表  1   LT-1和Sentinel-1卫星数据参数

    Table  1   Parameters of LT-1 and Sentinel-1 Satellite Data

    卫星轨道方向主影像时间/影像起始时间从影像时间/影像终止时间时间基线/d空间基线/m数量/个
    LT⁃1(同震)升轨2023⁃12⁃182023⁃12⁃224743.134
    LT⁃1(算法实验)升轨2023⁃07⁃122024⁃03⁃2422
    Sentinel⁃1(同震)升轨(T128)2023⁃10⁃272023⁃12⁃266064.282
    降轨(T135)2023⁃12⁃142023⁃12⁃2612-116.222
    Sentinel⁃1(震前)升轨(T128)2021⁃01⁃102023⁃06⁃0567
    降轨(T135)2021⁃01⁃052023⁃12⁃1451
    下载: 导出CSV

    表  2   LT-1卫星数据初始偏移量获取方法比较/像素

    Table  2   Comparison of LT-1 Satellite Data Initial Offset Acquisition Methods/Pixel

    类别几何配准法获取初始偏移量目视法确定特征点初始偏移量SIFT-Like自动确定特征点初始偏移量
    距离向方位向距离向方位向距离向方位向
    主、从SAR影像初配准1 1388 3211 1108 3001 1408 290
    去除地形相位时初配准00-64005399
    下载: 导出CSV

    表  3   识别的震前滑坡信息表

    Table  3   Identified Pre-Seismic Landslide Information

    轨道方向数量/个总面积/km2最小面积/km2最大面积/km2重叠个数
    升轨19583.190.0856.2893
    降轨17676.950.0858.78
    下载: 导出CSV
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  • 收稿日期:  2024-03-13
  • 网络出版日期:  2024-06-04
  • 刊出日期:  2025-02-04

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