The tides of the Qiantang River in eastern China are one of the three major tides in the world. Although these tides are spectacular, they seriously threaten the seawalls of the river. Rapid and accurate monitoring of ground deformations along the seawalls is important not only to the seawalls themselves but also to the vast amount of land behind them. We carried out comprehensive, unprecedented high-density mapping of ground deformations along the seawalls of the Qiantang River using the latest full scatterer (FS) interferometric synthetic aperture radar (InSAR) technique with 56 Sentinel-1 SAR images acquired from October 2020 to October 2022. The InSAR-derived deformations were then validated with quasi-synchronous leveling measurements. The results demonstrate that there are five subsidence centers on the northern seawalls and three on the southern seawalls, with a maximum subsidence rate of 96 mm/a and a measuring density of 1293 points/km2. The main reasons for the severe subsidence are the natural consolidation of soft soil in reclaimed areas, groundwater overexploitation due to aquaculture, and foundation pit drainage. We present, for the first time, a comprehensive mapping of ground deformations along the seawalls of the Qiantang River at ultrahigh density, which is very important for the health management of seawalls and the safety of the river on both sides.
Marine reclamation took place at large scale in Lianyungang city of Jiangsu province, China during last two decades in order to provide extra land for economy growth. However, large land subsidence usually occurs on newly reclaimed land, which may bring damages to buildings and infrastructures constructed over the reclaimed land and seriously hinder the regional development in turn. Therefore, knowing detailed information about land subsidence over the reclaimed land is of great significance. As a new remote sensing monitoring method, synthetic aperture radar interferometry technology has great advantages in ground subsidence monitoring. Therefore, in this paper, the Sentinel-1A SAR images acquired from 2016 to 2021 are processed using InSAR time series technology to monitor and analyze the spatio-temporal characteristics of ground subsidence in the region. The results show that by the end of 2021, large subsidence occurred over the reclamation area of Lianyungang which is mainly caused by soil consolidation. The maximum subsidence rate is -165 mm/year, and the maximum cumulative subsidence reaches -991 mm during the 6 years, which is located in the northeast of Lianyungang. The deformation monitoring of the region has certain theoretical references for disaster prevention and control.
Conventional singe baseline InSAR is easily affected by atmospheric artifacts, making it difficult to generate highprecision DEM. To solve this problem, in this paper, a multi-baseline interferometric phase accumulation method with weights fixed by coherence is proposed to generate higher accuracy DEM. The mountainous area in Kunming, Yunnan Province, China is selected as study area, which is characterized by cloudy weather, rugged terrain and dense vegetation. The multi-baseline InSAR experiments are carried out by use of four ALOS-2 PALSAR-2 images. The generated DEM is evaluated by Chinese Digital Products of Fundamental Geographic Information 1:50000 DEM. The results demonstrate that: 1) the proposed method can reduce atmospheric artifacts significantly; 2) the accuracy of InSAR DEM generated by six interferograms satisfies the standard of 1:50000 DEM Level Three and American DTED-1.
The uneven settlement of high-speed railway (HSR) brings about great threat to the safe operation of trains. Therefore, the subsidence monitoring and prediction of HSR has important significance. In this paper, an improved multitemporal InSAR method combing PS-InSAR and SBAS-InSAR, Multiple-master Coherent Target Small-Baseline InSAR (MCTSB-InSAR), is used to monitor the subsidence of partial section of the Beijing-Tianjin HSR (BTHSR) and the Beijing-Shanghai HSR (BSHSR) in Beijing area. Thirty-one TerraSAR-X images from June 2011 to December 2016 are processed with the MCTSB-InSAR, and the subsidence information of the region covering 56km*32km in Beijing is dug out. Moreover, the monitoring results is validated by the leveling measurements in this area, with the accuracy of 4.4 mm/year. On the basis of above work, we extract the subsidence information of partial section of BTHSR and BSHSR in the research area. Finally, we adopt the idea of timing analysis, and employ the back-propagation (BP) neural network to simulate the relationship between former settlement and current settlement. Training data sets and test data sets are constructed respectively based on the monitoring results. The experimental results show that the prediction model has good prediction accuracy and applicability.
Affected by over-exploration of groundwater for a long time, the Hangjiahu Plain in Zhejiang province, southeast of China, has suffering serious ground subsidence during the past several decades. In this paper, we investigate the time series InSAR technique for the generation of subsidence maps over this plain. 25 Radarsat-2 images acquired from Jan 2012 to Nov 2014 are used. The results show that serious subsidence has taken place in the north and southeast of Jiaxing, the east and north of Huzhou, and the north of Hangzhou. Meanwhile some rebound occurs in the east of Jiaxing and the southeast of Huzhou. The results are compared with 35 levelling measurements. The standard deviation of the error between the two data is 3.01mm, which demonstrate that time series InSAR technique has good accuracy for subsidence monitoring.
Due to long term over-exploring groundwater, ground subsidence has taken place in Urumqi city for many years.
Traditional ways of monitoring ground deformation utilize levelling and global positioning system (GPS) measurement.
They have the advantage of high accuracy. However, they are very costly and cannot achieve enough spatial sampling
density. Recently, space-born synthetic aperture radar interferometry (InSAR) is playing an important role in monitoring
ground deformation. In this paper, 11 ALOS PALSAR images from 2007 to 2010 have been acquired to monitor the
Urumqi City using small baseline time series InSAR technique. Results show that the subsidence is mainly taken place in
Qidaowan Industry Park, Urumqi Development Zone and North Industry Park. The maximum subsidence velocity can
reach to -64.6mm/year.
The Sichuan Earthquake, occurred on May 12, 2008, is the strongest earthquake to hit China since the 1976
Tangshan earthquake. The earthquake had a magnitude of M 8.0, and caused surface deformation greater than 3 meters.
This paper presents the research work of measuring the co-seismic deformations of the earthquake with satellite
differential interferometric SAR technique. Four L-band SAR images were used to form the interferogram with 2 pre-
scenes imaged on Feb 17, 2008 and 2 post- scenes on May 19, 2008. The Digital Elevation Models extracted from
1:50,000-scale national geo-spatial database were used to remove the topographic contribution and form a differential
interferogram. The interferogram presents very high coherence in most areas, although the pre- and post- images were
acquired with time interval of 92 days. This indicates that the L-band PALSAR sensor is very powerful for
interferometry applications. The baseline error is regarded as the main phase error source in the differential interferogram.
Due to the difficulties of doing field works immediately after the earthquake, only one deformation measurement
recorded by a permanent GPS station is obtained for this research. An approximation method is proposed to eliminate the
orbital phase error with one control point. The derived deformation map shows similar spatial pattern and deformation
magnitude compared with deformation field generated by seismic inversion method.
The polarization feature of the target could be expressed by both the scattering matrix and the Stokes matrix. In the
Back Scattering Alignment (BSA) system, scattering matrix meets the principle of reciprocity and every element of it is
a complex number. Stokes matrix is a transformed format of scattering matrix and reflects the relationship between SAR
received power and transceiver antenna polarization status. For a deterministic target, there is a one-to-one
correspondence between the scattering matrix and the Stokes matrix. Since the Stokes matrix is always a real symmetric
matrix and has the nature of normal matrix. It is usually used to save polarized scattering data. With the development of
polarization technology, polarization synthesis has already become one of the most important tools for polarization data
analysis. An optimal polarization status and the maximum reception power must exist through different parameters
combinations. That means target's optimal polarization. Traditional target's optimal polarization theory was based on
the scattering matrix. But the scattering matrix is usually obtained difficultly, so the calculating process always be much
complex. In this paper, we deduce the formulae optimal receive power based on Stokes matrix and polarization
synthesis. The algorithm could be carried out easily and the programming process is much directly. Some experiments
proof that ideal results could received by proposed algorithm.
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