基于开源软件GMTSAR与iGPS的时序形变自动化处理工具研发及应用

罗毅; 田云锋; 冯万鹏; 胡应顺

doi:10.19975/j.dqyxx.2023-020

基于开源软件GMTSAR与iGPS的时序形变自动化处理工具研发及应用

doi: 10.19975/j.dqyxx.2023-020

罗毅^1,,
田云锋^1, ,,
冯万鹏^{2, 3},
胡应顺⁴

1.
应急管理部国家自然灾害防治研究院，北京 100085
2.
中山大学地球科学与工程学院，珠海 519080
3.
中国地震局地质研究所，北京 100029
4.
西藏地震局，拉萨 850010

基金项目: 国家自然科学基金资助项目（41972230，42274064）；地震动力学国家重点实验室开放课题（LED2021B06）

详细信息

作者简介:
罗毅（1983-），男，助理研究员，主要从事利用InSAR、北斗等技术开展形变监测研究. E-mail：luoyi1983@126.com

通讯作者:
田云锋（1976-），男，副研究员，主要从事地壳形变研究. E-mail：y.f.tian@163.com

中图分类号: P315
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- 文章访问数: 40
- HTML全文浏览量: 38
- PDF下载量: 17
- 被引次数: 0
出版历程
- 收稿日期: 2023-04-28
- 修回日期: 2023-05-17
- 录用日期: 2023-05-18
- 网络出版日期: 2023-05-25
- 刊出日期: 2023-11-01

Development and application of automated processing tool for time series deformation analysis using open-source GMTSAR and iGPS software

Luo Yi^1
,,
Tian Yunfeng^{1
, ,},
Feng Wanpeng^{2, 3},
Hu Yingshun⁴

1.
National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing 100085, China
2.
School of Earth Science and Engineering, Sun Yat-sen University, Zhuhai 519080, China
3.
Institute of Geology, Chinese Earthquake Administration, Beijing 100029, China
4.
Xizang Earthquake Bureau, Lasa 850010, China

Funds: Supported by the National Natural Science Foundation of China (Grant Nos. 41972230, 42274064), and the State Key Laboratory of Earthquake Dynamics (Grant No. LED2021B06)

摘要

摘要: 地表形变是地球内部多种物理过程的表现，是探索深部地球物理环境的重要工具. 近年来随着数据和软件的丰富，合成孔径雷达干涉（Interferometric Synthetic Aperture Radar, InSAR）技术常被作为探测地壳形变的首选手段，因而快速掌握处理技术成为构造地质和地震过程等研究领域从业者的迫切需求. 本文扩展了形变时序分析软件包iGPS的功能，开发了一套基于InSAR开源软件GMTSAR的辅助处理程序，实现了时序InSAR分析流程的自动化，具备数据自动获取、干涉自主组织、时序分析调用、形变结果分析与展示等功能，显著简化了处理过程；以青藏高原西部现今地壳形变探测为例，详述了自动化处理流程，并与GNSS速度场进行对比检验了形变结果的可靠性. 本文处理了2015年6月至2022年9月期间Sentinel-1卫星T12轨道的61期成像数据，获取了南北跨度上千千米的InSAR形变场，显示伴随青藏高原地壳东向挤出而产生的左旋剪切主要发生在高原北部，尤其是阿尔金断裂带、玛尔盖茶卡—昆仑断裂带之间的地带，吸收了大部分塔里木盆地与青藏高原之间的相对运动；带内活动断裂分布较近，构造形变混叠在一起难以有效分离，使得准确地估计阿尔金断裂带的现今滑动速率面临挑战. 本文系统地梳理了如何借助开源InSAR软件来实现形变时序的自动化处理，有助于地球物理等领域的研究者快速熟悉与掌握相关知识与技术.
- 合成孔径雷达干涉测量 /
- GMTSAR /
- 青藏高原 /
- 构造形变 /
- iGPS
Abstract: Surface crustal deformation is often used to explore physical processes within the interior of the Earth. The observable surface changes can reflect variable subsurface physical processes that are usually inaccessible to modern instruments. For example, surface displacement observations have been widely used to study the geometric parameters of faults and slip distributions of earthquakes, to estimate interseismic slip rates and locking depths of active faults, and to constrain the physical properties of rock at depth. Therefore, a comprehensive knowledge of crustal deformation plays a key role in evaluating the seismic hazard probability in areas with active faults, particularly for heavily populated areas such as the North-South (Nanbei) Seismic Belt in western China.The two most widely used techniques for monitoring crustal movement are the Global Navigation Satellite System (GNSS) and interferometric synthetic aperture radar (InSAR). The former involves extensive fieldwork and is only applicable at locations with convenient transportation facilities. The latter can cover a relatively large region at significantly lower cost. With the increase of SAR data since the launch of Sentinel-1A satellite in 2014, InSAR has been the preferred tool for monitoring crustal deformation. Thus, there is an urgent need for a proficient application of this technique. Based on the iGPS time series analysis package, we developed a suite of programs that incorporate the open source InSAR software-GMTSAR to automate and facilitate the processing procedure of time series InSAR analysis. It can automatically download data, organize the interferometric processing tasks, perform time series, conduct data analysis, and visualize results. We first introduce the interferometric functionalities of GMTSAR and iGPS software. The processing flowchart is described in detail by deriving the present-day slow crustal deformation of the western Tibetan Plateau as an example. Owing to high coherence inherently for the Tibetan Plateau, using Sentinel-1 ascending track T12 data collected during June 2015 to September 2022, we demonstrated that a dense InSAR average velocity map of high accuracy could be obtained for a vast area spanning over 1000 km. The InSAR results showed that the eastward extrusion of the Tibetan Plateau resulted in rapid shear slip within a narrow belt between the Altyn Tagh and Margai Caka-Kunlun fault zones, absorbing over half of the relative motion between the Tarim Basin and Tibetan Plateau.This study systematically introduced how to perform automated small baseline subset (SBAS) InSAR processing using open-access SAR data and InSAR software to detect subtle crustal deformation. In the future, InSAR operators can apply this method to conduct their own processing chains for crustal deformation studies with limited inputs.
- InSAR /
- GMTSAR /
- Tibetan Plateau /
- tectonic deformation /
- iGPS

HTML全文

图 1 两种剖面线生成方案（虚线为断裂，实线为剖面线）.（a）垂直于断裂的平均走向；（b）沿断裂走向变化

Figure 1. Two strategies for generating profiles (the dotted and solid lines are fault traces and profiles, respectively). (a) Profiles perpendicular to the mean fault strike; (b) Profiles perpendicular to strikes of individual fault segments

下载: 全尺寸图片幻灯片

图 2 数据目录结构示意图

Figure 2. Schematic diagram of the data directory structures

下载: 全尺寸图片幻灯片

图 3 T12轨道数据覆盖范围. 圆圈表示卫星轨迹，蓝色框为图幅范围，实心三角形表示剪裁区域的南（1）、北（2）边界位置

Figure 3. Coverage of track T12 data. The dots represent the satellite trace; the blue boxes are footprints of Setninel-1 SAR images, and the solid triangles represent the south (1) and north (2) boundary positions of the clipped area

下载: 全尺寸图片幻灯片

图 4 处理的干涉对基线图，T表示时间（年）；D表示空间基线（m）

Figure 4. Baseline plot of the generated interferograms. T and D are time in years and spatial baselines (m), respectively

下载: 全尺寸图片幻灯片

图 5 青藏高原现今地壳形变速率（LOS向）剖面. （a）InSAR平均速率图. ATF：阿尔金断裂带；MCF：玛尔盖茶卡断裂带；KLF：昆仑断裂带；RCF：日干配错断裂带；GCF：格仁错断裂带；AKMS：阿尼玛卿—昆仑—木孜塔格缝合带；JSS：金沙缝合带；BNS：班公—怒江缝合带；YZS：雅鲁藏布江缝合带. （b） AB速率剖面，其中灰点为InSAR观测结果，蓝色线为最优位错拟合（断裂两侧200 km范围），红色线为误差区间，红色点为Wang和Shen（2020）的GNSS速度场投影到LOS向的值. （c）类似于图（b），为CD速率剖面

Figure 5. Present-day crustal deformation rate (LOS) for the Tibetan Plateau. (a) InSAR mean velocity map. ATF: Altyn Tagh Fault; MCF: Margai Caka Fault; RCF: Riganpei Co Fault; GCF: Gyaring Co Fault; AKMS: Anyimaqen-Kunlun-Muztagh Suture; JSS: JinSha Suture; BNS: Bangong-Nujiang Suture; YZS: Yarlung-Zangbo Suture; (b) Velocity profile of AB. The gray dots are InSAR results, the blue curves are optimal fitting using the elastic screw dislocation; the red curves represent error ranges; and the red dots are GNSS velocities in Wang and Shen (2020) projected to LOS direction; (c) the same as (b) but for profile CD

下载: 全尺寸图片幻灯片

表 1 常见InSAR处理软件功能对比

Table 1. Comparison of common InSAR processing software packages

软件	操作方式	干涉并行处理	对流层延迟校正	电离层延迟校正	解缠工具	时序分析工具	许可类型
GAMMA	命令行	支持 (多CPU)	时序	支持	MCF	IPTA/第三方（StaMPS）	商业
GMTSAR	命令行	支持（多CPU）	CSS法	支持	Snaphu	SBAS/第三方(StaMPS)	开源
ISCE	命令行	支持（多CPU/GPU）	时序	支持	Snaphu	第三方(Giant或StaMPS)	开源
SARScape	界面、批处理、二次开发	支持（GPU/CPU）	时序	-	Snaphu	永久散射体（PS）、短基线（SBAS）、层析SAR	商业
SNAP	界面+命令行	-	第三方	支持	Snaphu	StaMPS	开源

下载: 导出CSV

表 2 GMTSAR软件的主要程序

Table 2. Main programs in the GMTSAR software

程序名称	功能说明
pop_config.csh	自动化生成针对不同SAR数据的配置文件
preproc_batch_tops.csh preproc_batch_tops_esd.csh	对data.in中的原始图像进行预处理、图像配准；esd表示进行ESD配准优化，避免burst边界出现相位跳变
get_baseline_table.csh	基于raw目录中配准后的图像计算空间基线（baseline_table.dat）
dem2topo_ra.csh	创建地理编码关系文件，将dem.grd文件由WGS84投影转换到雷达坐标（topo_ra.grd）
intf_tops.csh intf_tops_parallel.csh	在intf目录进行干涉处理，生成干涉图、解缠、并生成预览图像文件，结果保存至intf_all目录；parallel表示单机多核CPU并行版的程序（下同）
snaphu.csh	干涉图解缠
merge_batch.csh	子条带（subswath）干涉图的合并、解缠等
proj_ra2ll.csh proj_ll2ra_ascii.csh proj_ra2ll.csh proj_ra2ll_ascii.csh SAT_llt2rat	图像、坐标值（ascii文本文件中）在雷达坐标（ra）与地理坐标（ll）之间的相互转换
sbas sbas_parallel	SBAS时序分析，输入数据为雷达坐标/地理坐标下的相干图和解缠后干涉图，生成位移时序文件及平均速率图等
grd2kml.csh	将NetCDF (*.grd)图像转换为KML文件
grd2geotiff.csh	将NetCDF (*.grd)图像转换为GeoTIFF文件
assemble_tops	同一时期多景连续S1图像的拼接（早期版本受到TIFF不能超过4GB大小的限制）
cut_slc	配准后SLC文件的裁剪
phasediff	干涉相位生成
SAT_look	计算视线向（line of sight, LOS）方向矢量

下载: 导出CSV

表 3 iGPS InSAR分析程序

Table 3. InSAR analysis programs in iGPS

程序名称	功能说明
sh_asf_s1_get_slc_py	下载ASF网站提供的Python脚本文件（download-*.py）中的S1数据文件，保存至数据下载目录
sh_asf_s1_get_slc_roi	基于空间位置、成像时间、轨道等信息，利用ASF API查询所需的S1数据文件并下载
sh_esa_s1_get_aux_orb_gnss	从ESA网站下载S1卫星轨道文件
sh_s1_unzip_manifest	提取S1数据文件（zip格式）中的元数据文件（*.manifest.safe）
esa_s1_manifest_overlap	基于元数据文件，通过空间位置匹配挑选出同一地区的S1数据文件，生成待处理的S1列表文件
sh_s1_unzip	将列表文件中的S1数据文件解压至临时目录（$esa_unzip）
sh_s1_run_tsa	时序分析（time series analysis, TSA）工具，是干涉自动处理主程序，调用GMTSAR完成：原始S1图像拼接、剪裁；主辅图像配准；地理编码转换关系生成；干涉对组合选择；干涉相位生成；相位解缠；相对基准转换；SBAS分析；地理编码等
sh_slc_cut	基于感兴趣区（area of interest, AOI）对配准后的SLC图像文件进行裁剪
sh_sar_intf_all_cut_roi	基于AOI对干涉图进行裁剪
sh_sar_intf_all_corr	相干性统计
sh_slurm_intf_tops	针对单个子条带，基于SLURM实现以干涉对为单位的计算机集群并行处理
sh_slurm_merge_batch	针对合并3个子条带后的整幅干涉图，基于SLURM实现以干涉对为单位的计算机集群并行处理
sh_s1_prep_f123	创建子条带干涉图合并的输入文件
sh_sar_gacos_tgz_unzip sh_sar_gacos_ztd2ll sh_sar_gacos_ll2ra sh_sar_gacos_intf_all sh_sar_gacos_apply_intf	借助于GACOS资料实现对流层大气噪声校正，包括解压原始二进制文件压缩文件包、二进制格式转NetCDF格式、地理坐标系转雷达坐标系、干涉对大气相位差分、干涉图的大气相位校正
sh_sar_cp_intf_png	将已处理干涉对（intf_all）的预览文件（*.png）复制到预览文件目录（intf_all_png），以检查干涉相位、生成未处理的干涉对列表、挑选用于SBAS分析的干涉对等
sar_sbas_tab_from_png	基于已处理的干涉对（intf_all_png下的预览文件），创建SBAS输入文件（intf.tab、scene.tab），绘制干涉对时空基线图
sh_sar_sbas	调用GMTSAR的SBAS程序，并进行形变结果图像掩膜、重采样、格式转换等处理
sh_sar_sbas_corr_mask	统计相干性均值，根据阈值创建掩膜文件，从SBAS形变结果中滤掉低相干区域
sh_gnss_vel2los	将GNSS三维形变场转换到LOS向
sh_gnss_correct_insar_vel	InSAR速率图由局部相对基准到GNSS LOS速度场基准的转换
sh_sar_sbas_extract_time_series_lls	提取点的InSAR位移时间序列
sar_los_profile_auto	提取沿断裂线的速率剖面，能够自动生成不同方向速率剖面（图1）
sar_los_profile_fit	通过网格搜索，利用经典的弹性位错公式（Savage and Burford，1973）反演走滑断裂的滑动速率及断面闭锁深度
sar_los_profile_fits.m	Matlab程序，调用MCMCSTAT程序包（Haario et al.，2006）来实现基于马尔可夫链蒙特卡罗算法（MCMC）的走滑断裂参数反演

下载: 导出CSV

表 4 时序InSAR分析涉及的文件和目录

Table 4. Files and directories used in time series InSAR analysis

类型	文件名/格式	所在位置及说明
S1数据文件	S1?_IW_SLC__1S?V_*.zip	$esa_data/s1/
S1元数据文件	*.manifest.safe	$esa_data/metainfo/manifest.safe/
S1 SLC图像数据及头文件	.jpgf；.xml	临时目录 $esa_unzip/ 子条带处理目录（F1/F2/F3）下的 raw0/ 子条带处理目录下的raw/
S1轨道文件	*.EOF	精密轨道星历目录 $esa_data/aux_poeorb/ 回归轨道文件目录 $esa_data/aux_resorb/ 子条带处理目录下的 raw0/ 子条带处理目录下的raw/
数字高程模型	dem.grd	DEM（digital elevation model）目录 $esa_data/topo/ 数据处理主目录子条带处理目录下的topo/
地理编码关系文件	trans.dat	子条带处理目录下的topo/
雷达坐标下的高程文件	topo_ra.grd	子条带处理目录下的topo/
图像裁剪范围文件	pins.kml	数据处理主目录；在运行TSA时添加-roi pins.kml参数， pins.kml文件包含2个点要素，点的顺序遵循时间先后次序，要截取的图像成像起始时间在前，结束时间在后，即针对升轨数据，起始点在下，结束点在上；降轨则反之
待处理的SLC数据文件列表	input.lst	数据处理主目录
GMTSAR处理配置文件	batch_tops.config	数据处理主目录
GMTSAR图像配准输入文件	data.in	子条带处理目录；包含待处理的“图像文件-轨道文件”列表文件，第一行为主图像
时空基线文件	baseline_table.dat	子条带处理目录
干涉对集合文件	intf.in	子条带处理目录
干涉处理目录	intf/	子条带处理目录
干涉相位结果	intf_all/	子条带处理目录
干涉结果预览图集合	intf_all_png/	子条带处理目录
SBAS输入参数文件	intf.tab、scene.tab	子条带处理目录

下载: 导出CSV

表 5 处理的T12轨道数据列表

Table 5. List of processed data from track T12

序号	观测日期	基线/m	序号	观测日期	基线/m	序号	观测日期	基线/m
1	2020-01-20	0.00	22	2018-05-30	20.19	43	2021-05-02	44.89
2	2015-06-03	−33.78	23	2018-09-03	−133.99	44	2021-05-14	−12.91
3	2015-06-27	−142.92	24	2018-09-15	−61.53	45	2021-05-26	−23.62
4	2015-07-21	−84.94	25	2018-09-27	−9.41	46	2021-09-11	−60.70
5	2015-09-07	−110.88	26	2019-01-01	8.10	47	2021-09-23	6.76
6	2016-01-05	5.40	27	2019-01-13	−42.01	48	2022-01-09	−67.19
7	2016-01-29	58.27	28	2019-01-25	−57.54	49	2022-01-21	38.74
8	2016-05-04	6.70	29	2019-05-01	−104.51	50	2022-05-09	−24.03
9	2016-05-28	−51.58	30	2019-05-13	−46.28	51	2022-05-21	−8.85
10	2016-09-01	111.30	31	2019-09-10	−45.44	52	2022-09-06	−245.82
11	2016-09-25	−94.32	32	2019-09-22	−120.28	53	2022-09-18	−17.67
12	2017-01-23	1.32	33	2020-01-08	38.75	54	2022-09-30	−107.30
13	2017-05-11	−65.76	34	2020-05-07	15.18	55	2023-01-04	69.28
14	2017-05-23	4.25	35	2020-05-19	−7.50	56	2023-01-16	104.84
15	2017-09-08	22.58	36	2020-05-31	−29.85	57	2023-01-28	−97.75
16	2017-09-20	−7.44	37	2020-09-04	7.12	58	2023-02-09	107.14
17	2018-01-06	−3.67	38	2020-09-16	3.27	59	2023-02-21	84.94
18	2018-01-18	13.15	39	2020-09-28	−46.95	60	2023-03-05	−83.10
19	2018-01-30	48.77	40	2021-01-02	−22.61	61	2023-03-17	95.78
20	2018-05-06	−22.02	41	2021-01-14	8.13
21	2018-05-18	−28.20	42	2021-01-26	28.19

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