scholarly journals Freeze-Thaw Deformation Cycles and Temporal-Spatial Distribution of Permafrost along the Qinghai-Tibet Railway Using Multitrack InSAR Processing

2021 ◽  
Vol 13 (23) ◽  
pp. 4744
Author(s):  
Jing Wang ◽  
Chao Wang ◽  
Hong Zhang ◽  
Yixian Tang ◽  
Wei Duan ◽  
...  
Keyword(s):  
Time Series ◽  
Large Scale ◽  
Surface Deformation ◽  
Anthropogenic Activities ◽  
Composite Index ◽  
Buffer Zone ◽  
Absolute Error ◽  
Tibet Plateau ◽  
Permafrost Region ◽  
Index Model

The Qinghai-Tibet Railway (QTR) is the railway with the highest elevation and longest distance in the world, spanning more than 1142 km from Golmud to Lhasa across the continuous permafrost region. Due to climate change and anthropogenic activities, geological disasters such as subsidence and thermal melt collapse have occurred in the QTR embankment. To conduct the large-scale permafrost monitoring and geohazard investigation along the QTR, we collected 585 Sentinel-1A images based on the composite index model using the multitrack time-series interferometry synthetic aperture radar (MTS-InSAR) method to retrieve the surface deformation over a 3.15 × 105 km2 area along the QTR. Meanwhile, a new method for permafrost distribution mapping based on InSAR time series deformation was proposed. Finally, the seasonal deformation map and a new map of permafrost distribution along the QTR from Golmud to Lhasa were obtained. The results showed that the estimated seasonal deformation range of the 10 km buffer zone along the QTR was −50–10 mm, and the LOS deformation rate ranged from −30 to 15 mm/yr. In addition, the deformation results were validated by leveling measurements, and the range of absolute error was between 0.1 and 4.62 mm. Most of the QTR was relatively stable. Some geohazard-prone sections were detected and analyzed along the QTR. The permafrost distribution results were mostly consistent with the simulated results of Zou’s method, based on the temperature at the top of permafrost (TTOP) model. This study reveals recent deformation characteristics of the QTR, and has significant scientific implications and applicational value for ensuring the safe operation of the QTR. Moreover, our method, based on InSAR results, provides new insights for permafrost classification on the Qinghai-Tibet Plateau (QTP).

scholarly journals SURFACE DEFORMATION MONITORING IN PERMAFROST REGIONS OF TIBETAN PLATEAU BASED ON ALOS PALSAR DATA

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 1509-1512
Author(s):  
L. M. Chen ◽  
G. Qiao ◽  
P. Lu
Keyword(s):  
Structural Damage ◽  
Large Scale ◽  
Surface Deformation ◽  
Deformation Monitoring ◽  
Frozen Soil ◽  
Tibet Plateau ◽  
Temperature Deformation ◽  
Deformation Pattern ◽  
Permafrost Region ◽  
Freeze Thaw

The permafrost region of Qinghai-Tibet Plateau is widely distributed with the freeze/thaw processes that cause surface structural damage. The differential interferometry synthetic aperture radar (DInSAR) can detect large scale surface deformation with high precision, thus can be used to monitor the freeze/thaw processes of frozen soil area. In this paper, the surface deformation pattern of Qinghai-Tibet railway was analyzed by using the PALSAR 1.0 raw data of the ALOS satellite (L band) and 90m resolution SRTM DEM data, with the help of two-pass DInSAR method in GAMMA software, and the differential interferograms and deformation maps were obtained accordingly. Besides, the influence of temperature, topography and other factors on deformation of frozen soil were also studied. The following conclusions were obtained: there is a negative correlation between deformation and temperature, and there is a delay between the deformation change and that of temperature; deformation and elevation are positively correlated; the permafrost deformation is also affected by solar radiation that could form variable amplitude variation.

scholarly journals Permafrost Soil Moisture Monitoring Using Multi-Temporal TerraSAR-X Data in Beiluhe of Northern Tibet, China

2018 ◽  
Vol 10 (10) ◽  
pp. 1577 ◽  
Author(s):  
Chao Wang ◽  
Zhengjia Zhang ◽  
Simonetta Paloscia ◽  
Hong Zhang ◽  
Fan Wu ◽  
...  
Keyword(s):  
Time Series ◽  
Soil Moisture ◽  
Winter Season ◽  
Tibet Plateau ◽  
Permafrost Soil ◽  
Permafrost Region ◽  
Backscattering Coefficient ◽  
Sar Images ◽  
Northern Tibet ◽  
Variation Patterns

Global change has significant impact on permafrost region in the Tibet Plateau. Soil moisture (SM) of permafrost is one of the most important factors influencing the energy flux, ecosystem, and hydrologic process. The objectives of this paper are to retrieve the permafrost SM using time-series SAR images, without the need of auxiliary survey data, and reveal its variation patterns. After analyzing the characteristics of time-series radar backscattering coefficients of different landcover types, a two-component SM retrieval model is proposed. For the alpine meadow area, a linear retrieving model is proposed using the TerraSAR-X time-series images based on the assumption that the lowest backscattering coefficient is measured when the soil moisture is at its wilting point and the highest backscattering coefficient represents the water-saturated soil state. For the alpine desert area, the surface roughness contribution is eliminated using the dual SAR images acquired in the winter season with different incidence angles when retrieving soil moisture from the radar signal. Before the model implementation, landcover types are classified based on their backscattering features. 22 TerraSAR-X images are used to derive the soil moisture in Beiluhe, Northern Tibet with different incidence angles. The results obtained from the proposed method have been validated using in-situ soil moisture measurements, thus obtaining RMSE and Bias of 0.062 cm3/cm3 and 4.7%, respectively. The retrieved time-series SM maps of the study area point out the spatial and temporal SM variation patterns of various landcover types.

scholarly journals LiCSBAS: An Open-Source InSAR Time Series Analysis Package Integrated with the LiCSAR Automated Sentinel-1 InSAR Processor

2020 ◽  
Vol 12 (3) ◽  
pp. 424 ◽  
Author(s):  
Yu Morishita ◽  
Milan Lazecky ◽  
Tim Wright ◽  
Jonathan Weiss ◽  
John Elliott ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Open Source ◽  
Large Scale ◽  
Surface Deformation ◽  
Atmospheric Correction ◽  
Sar Interferometry ◽  
Processing Scheme ◽  
Series Analysis ◽  
Analysis Package

For the past five years, the 2-satellite Sentinel-1 constellation has provided abundant and useful Synthetic Aperture Radar (SAR) data, which have the potential to reveal global ground surface deformation at high spatial and temporal resolutions. However, for most users, fully exploiting the large amount of associated data is challenging, especially over wide areas. To help address this challenge, we have developed LiCSBAS, an open-source SAR interferometry (InSAR) time series analysis package that integrates with the automated Sentinel-1 InSAR processor (LiCSAR). LiCSBAS utilizes freely available LiCSAR products, and users can save processing time and disk space while obtaining the results of InSAR time series analysis. In the LiCSBAS processing scheme, interferograms with many unwrapping errors are automatically identified by loop closure and removed. Reliable time series and velocities are derived with the aid of masking using several noise indices. The easy implementation of atmospheric corrections to reduce noise is achieved with the Generic Atmospheric Correction Online Service for InSAR (GACOS). Using case studies in southern Tohoku and the Echigo Plain, Japan, we demonstrate that LiCSBAS applied to LiCSAR products can detect both large-scale (>100 km) and localized (~km) relative displacements with an accuracy of <1 cm/epoch and ~2 mm/yr. We detect displacements with different temporal characteristics, including linear, periodic, and episodic, in Niigata, Ojiya, and Sanjo City, respectively. LiCSBAS and LiCSAR products facilitate greater exploitation of globally available and abundant SAR datasets and enhance their applications for scientific research and societal benefit.

scholarly journals Surface Deformation Monitoring of a Section of Gongyu Expressway Based on SBAS-InSAR Technology

2021 ◽  
Vol 233 ◽  
pp. 01149
Author(s):  
Ying Yang ◽  
Yifang Sun ◽  
Shihong Wu ◽  
Xuegang Dong ◽  
Hanyao Huang ◽  
...  
Keyword(s):  
Time Series ◽  
Surface Deformation ◽  
Deformation Monitoring ◽  
Tibet Plateau ◽  
Seasonal Effect ◽  
Climate Conditions ◽  
Sar Data ◽  
Sbas Insar

It is difficult to monitor the surface deformation along the expressway for the critical climate conditions in Tibet plateau. In this paper, based on sentinel-1A SAR data, the surface deformation along the Gongyu expressway was tried to evaluate using time-series SBAS-InSAR method. The results indicate that the surface deformation in most regions is within the safe acquirement of the expressway. Moreover, the surface deformation indicates a strong seasonal effect. Finally, two special spots with dangerous surface deformation are identified along the expressway.

scholarly journals Deriving Centimeter-Level Coseismic Deformation and Fault Geometries of Small-To-Moderate Earthquakes From Time-Series Sentinel-1 SAR Images

2021 ◽  
Vol 9 ◽  
Author(s):  
Heng Luo ◽  
Teng Wang ◽  
Shengji Wei ◽  
Mingsheng Liao ◽  
Jianya Gong
Keyword(s):  
Time Series ◽  
Surface Deformation ◽  
Active Tectonics ◽  
Tibet Plateau ◽  
Coseismic Deformation ◽  
Earthquake Catalog ◽  
Sar Images ◽  
Weak Surface ◽  
Phase Screens ◽  
Atmospheric Delays

Small-to-moderate earthquakes (e.g. ≤Mw5.5) occur much more frequently than large ones (e.g. &gt;Mw6.0), yet are difficult to study with InSAR due to their weak surface deformation that are severely contaminated by atmospheric delays. Here we propose a stacking method using time-series SAR images that can effectively suppress atmospheric phase screens and extract weak coseismic deformation in centimeter to sub-centimeter level. Using this method, we successfully derive coseismic surface deformations for three small-to-moderate (Mw∼5) earthquakes in Tibet Plateau and Tienshan region from time-series Sentinel-1 SAR images, with peak line-of-sight deformation ranging from 5–6 mm to 13 mm. We also propose a strategy to downsample interferograms with weak deformation signal based on quadtree mesh obtained from preliminary slip model. With the downsampled datasets, we invert for the centroid locations, fault geometries and slips of these events. Our results demonstrate the potential of using time-series InSAR images to enrich earthquake catalog with geodetic observations for further study of earthquake cycle and active tectonics.

scholarly journals Surface deformation detected by the space-observed small baseline SAR interferometry over permafrost environment in Tibet Plateau, China

2012 ◽  
Vol 6 (5) ◽  
pp. 4071-4099 ◽  
Author(s):  
F. Chen ◽  
H. Lin
Keyword(s):  
Climate Change ◽  
Active Layer ◽  
Surface Deformation ◽  
Anthropogenic Activities ◽  
Sar Interferometry ◽  
Tibet Plateau ◽  
Alos Palsar ◽  
Permafrost Environment ◽  
Water Level Variations ◽  
Small Baseline

Abstract. The evolution of permafrost and the active layer is highly related to climate change because of its feedback effects involving water and carbon storage. In this study, we firstly examined the relationship of regional water balance, geomorphological process and anthropogenic activities by means of Small Baseline Synthetic Aperture Radar Interferometry (SB-InSAR) to monitor the surface movements overlaid on the permafrost of Tibet Plateau (TP), China, using 3.5-yr observation span of L-band ALOS PALSAR data (June, 2007 to December, 2010). The estimated displacements (primarily in the range of −30 mm yr−1 to 30 mm yr−1) and time-series implied evolutions of the active layer and permafrost beneath. The motion trend along slopes was complicated, and thus interdisciplinary interpretations were required. Water level variations of inland lakes were then detected, although further investigations were required for validation. Anthropogenic influences on this frail permafrost environment were significant, proved by the remarkable surface settlement along the embankment of Qinghai-Tibet Railway. Consequently, it is crucial and necessary to monitor this arid and cold plateau owing to the combination of climate change, geo-hazards prediction as well as the regional sustainable development.

scholarly journals ACTIVE LAYER THICKNESS RETRIEVAL OVER THE QINGHAI-TIBET PLATEAU FROM 2000 TO 2020 BASED ON INSAR-MEASURED SUBSIDENCE AND MULTI-LAYER SOIL MOISTURE

2021 ◽  
Vol XLIII-B3-2021 ◽  
pp. 437-442
Author(s):  
T. Chang ◽  
J. Han ◽  
Z. Li ◽  
Y. Wen ◽  
T. Hao ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Layer Thickness ◽  
Active Layer ◽  
Surface Deformation ◽  
Tibet Plateau ◽  
Active Layer Thickness ◽  
Permafrost Region ◽  
Radar Images ◽  
Soil Moisture Data ◽  
Qinghai Tibet Plateau

Abstract. Active layer thickness (ALT) is an important index to reflect the stability of permafrost. The retrieval of ALT based on Interferometric Synthetic Aperture Radar (InSAR) technology has been investigated recently in permafrost research. However, most of such studies are carried out in a limited extend and relatively short temporal coverage. The combination of temporal-spatial multi-layer soil moisture data and multi-temporal InSAR is a promising approach for the large-scale characterization of ALT. In this study, we employed Small Baseline Subset Interferometry (SBAS-InSAR) technology to obtain the seasonal surface deformation from radar images of Envisat and Sentinel-1 in a permafrost region of Qinghai-Tibet Plateau (QTP). We attempt to verify and calibrate the temporal-spatial multi-layer soil moisture product in combination with the in-situ data. Based on the land subsidence data and the temporal-spatial multi-layer soil moisture data, we further improve method to retrieve the ALT information. This paper describes the progress so far and point out the future work.

scholarly journals Seasonal InSAR Displacements Documenting the Active Layer Freeze and Thaw Progression in Central-Western Spitsbergen, Svalbard

2021 ◽  
Vol 13 (15) ◽  
pp. 2977
Author(s):  
Line Rouyet ◽  
Lin Liu ◽  
Sarah Marie Strand ◽  
Hanne Hvidtfeldt Christiansen ◽  
Tom Rune Lauknes ◽  
...  
Keyword(s):  
Time Series ◽  
Active Layer ◽  
Composite Index ◽  
Ground Surface ◽  
Western Coast ◽  
Thermal Dynamics ◽  
Index Model ◽  
Synthetic Aperture Radar Interferometry ◽  
Freeze And Thaw ◽  
Ground Conditions

In permafrost areas, the active layer undergoes seasonal frost heave and thaw subsidence caused by ice formation and melting. The amplitude and timing of the ground displacement cycles depend on the climatic and ground conditions. Here we used Sentinel-1 Synthetic Aperture Radar Interferometry (InSAR) to document the seasonal displacement progression in three regions of Svalbard. We retrieved June–November 2017 time series and identified thaw subsidence maxima and their timing. InSAR measurements were compared with a composite index model based on ground surface temperature. Cyclic seasonal patterns are identified in all areas, but the timing of the displacement progression varies. The subsidence maxima occurred later on the warm western coast (Kapp Linné and Ny-Ålesund) compared to the colder interior (Adventdalen). The composite index model is generally able to explain the observed patterns. In Adventdalen, the model matches the InSAR time series at the location of the borehole. In Kapp Linné and Ny-Ålesund, larger deviations are found at the pixel-scale, but km or regional averaging improves the fit. The study highlights the potential for further development of regional InSAR products to represent the cyclic displacements in permafrost areas and infer the active layer thermal dynamics.

scholarly journals Early Identifying and Monitoring Landslides in Guizhou Province with InSAR and Optical Remote Sensing

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Genger Li ◽  
Bo Hu ◽  
Hui Li ◽  
Feng Lu
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Large Scale ◽  
Surface Deformation ◽  
Satellite Image ◽  
Deformation Monitoring ◽  
Guizhou Province ◽  
Landslide Monitoring ◽  
Optical Remote Sensing ◽  
Monitoring Method

The topography and landforms of Guizhou Province in China are complicated, and the climatic conditions of heavy precipitation make landslide disasters in Guizhou Province occur frequently. To avoid damage to people’s lives and economic property caused by disasters, a reliable early landslide identification method and landslide monitoring method are urgently needed. Traditional landslide identification and monitoring methods have limitations. InSAR technology has unique advantages in large-scale landslide identification and monitoring, but landslide identification results based on a single deformation value are one-sided. Therefore, this paper uses Sentinel-1A radar satellite image data and uses InSAR technology and optical remote sensing technology to carry out large-scale surface deformation monitoring and identification of dangerous deformation areas in Liupanshui City, Tongren City, Guiyang City and other regions in Guizhou Province. The potential landslide identification methods based on the time series normalized difference vegetation index and landslide development environment elements are combined to investigate hidden landslide hazards in the study area. In this paper, time series InSAR technology is used to monitor three key landslides in Jichang Town, Yujiaying and Fana, to grasp the movement status of the landslide in time. The method of landslide identification and monitoring in this paper is of great significance for disaster prevention and management in Guizhou Province.

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