Land Subsidence Detection by PSInSARTM Based on TerraSAR-X Images

2011 ◽  
Vol 301-303 ◽  
pp. 641-645 ◽  
Author(s):  
Hong Liang Jia ◽  
Bing Yu ◽  
Rui Zhang ◽  
Ming Zhi Sang
Keyword(s):  
High Resolution ◽  
Land Subsidence ◽  
Large Scale ◽  
Radar Data ◽  
Short Wave ◽  
Persistent Scatterer ◽  
Wave Radar ◽  
Land Deformation ◽  
Tianjin City ◽  
Large Scale Land

Land subsidence in urban area is becoming a severe geological hazard disturbing the urban construction and development. Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) technique has demonstrated a good capability of monitoring the large scale land deformation. High resolution and short wave radar data can help to improve the precision of deformation detection based on PSInSAR. In this paper, 15 scenes of TerraSAR-X SAR data are used to derive the estimation of the subsidence rate in the Wuqing district, Tianjin city in China. The combination of TIN and nearest-connection method (NCM) are first used to establish the differential network model. The results show that high resolution TX image can dramatically increase the valid PSs and improve investigation reliability, especially in linear man-made constructs.

scholarly journals Reservoir-Induced Land Deformation: Case Study from the Grand Ethiopian Renaissance Dam

2021 ◽  
Vol 13 (5) ◽  
pp. 874
Author(s):  
Yu Chen ◽  
Mohamed Ahmed ◽  
Natthachet Tangdamrongsub ◽  
Dorina Murgulet
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Surface Deformation ◽  
Vertical Displacement ◽  
Nile River ◽  
Reservoir Volume ◽  
Novel Approach ◽  
Land Deformation ◽  
Large Scale Land ◽  
The Impact

The Nile River stretches from south to north throughout the Nile River Basin (NRB) in Northeast Africa. Ethiopia, where the Blue Nile originates, has begun the construction of the Grand Ethiopian Renaissance Dam (GERD), which will be used to generate electricity. However, the impact of the GERD on land deformation caused by significant water relocation has not been rigorously considered in the scientific research. In this study, we develop a novel approach for predicting large-scale land deformation induced by the construction of the GERD reservoir. We also investigate the limitations of using the Gravity Recovery and Climate Experiment Follow On (GRACE-FO) mission to detect GERD-induced land deformation. We simulated three land deformation scenarios related to filling the expected reservoir volume, 70 km3, using 5-, 10-, and 15-year filling scenarios. The results indicated: (i) trends in downward vertical displacement estimated at −17.79 ± 0.02, −8.90 ± 0.09, and −5.94 ± 0.05 mm/year, for the 5-, 10-, and 15-year filling scenarios, respectively; (ii) the western (eastern) parts of the GERD reservoir are estimated to move toward the reservoir’s center by +0.98 ± 0.01 (−0.98 ± 0.01), +0.48 ± 0.00 (−0.48 ± 0.00), and +0.33 ± 0.00 (−0.33 ± 0.00) mm/year, under the 5-, 10- and 15-year filling strategies, respectively; (iii) the northern part of the GERD reservoir is moving southward by +1.28 ± 0.02, +0.64 ± 0.01, and +0.43 ± 0.00 mm/year, while the southern part is moving northward by −3.75 ± 0.04, −1.87 ± 0.02, and −1.25 ± 0.01 mm/year, during the three examined scenarios, respectively; and (iv) the GRACE-FO mission can only detect 15% of the large-scale land deformation produced by the GERD reservoir. Methods and results demonstrated in this study provide insights into possible impacts of reservoir impoundment on land surface deformation, which can be adopted into the GERD project or similar future dam construction plans.

Confronting and combining high-resolution simulations (ICON-LEM) with remote sensing observations

2020 ◽  
Author(s):  
Vera Schemann ◽  
Mario Mech
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Large Scale ◽  
General Structure ◽  
Radar Data ◽  
Synoptic Variability ◽  
Lateral Boundary Conditions ◽  
Large Eddy ◽  
Land Surfaces ◽  
Selection Of

<p>The current generation of large-eddy models (e.g. the ICON-LEM) allows us to go beyond idealized simulations and to capture synoptic variability by including heterogeneous land surfaces as well as lateral boundary conditions. This would offer the possibility to compare simulations and observations of clouds on a detailed day-to-day basis. But while LEMs are able to reach resolutions that start to be comparable to state-of-the-art observations (e.g. Radar data), they are still facing the issue of different parameter spaces: either the model output has to be transfered to observable quantities, or the other way around. We will present examples from recent field campaigns (e.g. ACLOUD, EUREC4A), where we combined ICON-LEM simulations with remote sensing observations by applying the Passive and Active Microwave TRAnsfer simulator (PAMTRA). By the selection of examples, we will show the potential of this combination of high-resolution modeling, remote sensing observations and forward simulations at different places under different conditions (Arctic, European and Caribbean). While the general structure of clouds (e.g. timing, type, height) is often already captured quite well, the comparison to the remote sensing observations allows us to also get insights into the composition of clouds and to constrain microphysical parameterizations as well as the influence of the large-scale forcing on a more detailed level.</p>

scholarly journals Sensitivity of 0–12-h Warm-Season Precipitation Forecasts over the Central United States to Model Initialization

2012 ◽  
Vol 27 (4) ◽  
pp. 832-855 ◽  
Author(s):  
Juanzhen Sun ◽  
Stanley B. Trier ◽  
Qingnong Xiao ◽  
Morris L. Weisman ◽  
Hongli Wang ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Case Studies ◽  
Large Scale ◽  
Initial Conditions ◽  
Warm Season ◽  
Radar Data ◽  
Short Wave ◽  
Forecast Skill ◽  
Precipitation Forecast ◽  
Scale Model

Abstract Sensitivity of 0–12-h warm-season precipitation forecasts to atmospheric initial conditions, including those from different large-scale model analyses and from rapid cycled (RC) three-dimensional variational data assimilations (3DVAR) with and without radar data, is investigated for a 6-day period during the International H2O Project. Neighborhood-based precipitation verification is used to compare forecasts made with the Advanced Research core of the Weather Research and Forecasting Model (ARW-WRF). Three significant convective episodes are examined by comparing the precipitation patterns and locations from different forecast experiments. From two of these three case studies, causes for the success and failure of the RC data assimilation in improving forecast skill are shown. Results indicate that the use of higher-resolution analysis in the initialization, rapid update cycling via WRF 3DVAR data assimilation, and the additional assimilation of radar observations each play a role in shortening the period of the initial precipitation spinup as well as in placing storms closer to observations, thus improving precipitation forecast skill by up to 8–9 h. Impacts of data assimilation differ for forecasts initialized at 0000 and 1200 UTC. The case studies show that the pattern and location of the forecasted precipitation were noticeably improved with radar data assimilation for the two late afternoon cases that featured lines of convection driven by surface-based cold pools. In contrast, the RC 3DVAR, both with and without radar data, had negative impacts on convective forecasts for a case of morning elevated convection associated with a midlatitude short-wave trough.

scholarly journals Adjacent-Track InSAR Processing for Large-Scale Land Subsidence Monitoring in the Hebei Plain

2021 ◽  
Vol 13 (4) ◽  
pp. 795
Author(s):  
Xi Li ◽  
Li Yan ◽  
Lijun Lu ◽  
Guoman Huang ◽  
Zheng Zhao ◽  
...  
Keyword(s):  
Time Series ◽  
Synthetic Aperture Radar ◽  
Land Subsidence ◽  
Large Scale ◽  
Synthetic Aperture ◽  
Hebei Plain ◽  
Deformation Velocity ◽  
Large Scale Land ◽  
Subsidence Monitoring ◽  
Aperture Radar

Large-scale land subsidence has threatened the safety of the Hebei Plain in China. For tens of thousands of square kilometers of the Hebei Plain, large-scale subsidence monitoring is still one of the most difficult problems to be solved. In this paper, we employed the small baseline subset (SBAS) and NSBAS technique to monitor the land subsidence in the Hebei Plain (45,000 km2). The 166 Sentinel-1A data of adjacent-track 40 and 142 collected from May 2017 to May 2019 were used to generate the average deformation velocity and deformation time-series. A novel data fusion flow for the generation of land subsidence velocity of adjacent-track is presented and tested, named as the fusion of time-series interferometric synthetic aperture radar (TS-InSAR) results of adjacent-track using synthetic aperture radar amplitude images (FTASA). A cross-comparison analysis between the two tracks results and two TS-InSAR results was carried out. In addition, the deformation results were validated by leveling measurements and benchmarks on bedrock results, reaching a precision 9 mm/year. Twenty-six typical subsidence bowls were identified in Handan, Xingtai, Shijiazhuang, Hengshui, Cangzhou, and Baoding. An average annual subsidence velocity over −79 mm/year was observed in Gaoyang County of Baoding City. Through the cause analysis of the typical subsidence bowls, the results showed that the shallow and deep groundwater funnels, three different land use types over the building construction, industrial area, and dense residential area, and faults had high spatial correlation related to land subsidence bowls.

scholarly journals IoT technology and big data processing for monitoring and analysing land subsidence in Central Taiwan

2020 ◽  
Vol 382 ◽  
pp. 103-109
Author(s):  
Wei-Chia Hung ◽  
Yi-An Chen ◽  
Cheinway Hwang
Keyword(s):  
Land Subsidence ◽  
High Speed ◽  
Large Scale ◽  
Alluvial Fan ◽  
Monitoring Wells ◽  
Multi Temporal ◽  
Multiple Sensor Monitoring ◽  
Large Scale Land ◽  
Central Taiwan ◽  
Subsidence Monitoring

Abstract. Over 1992–2018, groundwater overexploitation had caused large-scale land subsidence in the Choshui River Alluvial Fan (CRAF) in Taiwan. The Taiwan High Speed Railway (THSR) passes through an area of severe subsidence in CRAF, and the subsidence poses a serious threat to its operation. How to effectively monitor land subsidence here has become a major issue in Taiwan. In this paper, we introduce a multiple-sensor monitoring system for land subsidence, including 50 continuous operation reference stations (CORS), multi temporal InSAR (MT-InSAR), a 1000 km levelling network, 34 multi-layer compaction monitoring wells and 116 groundwater monitoring wells. This system can monitor the extent of land subsidence and provide data for studying the mechanism of land subsidence. We use the Internet of Things (IoT) technology to control and manage the sensors and develop a bigdata processing procedure to analyse the monitoring data for the system of sensors. The procedure makes the land subsidence monitoring more efficient and intelligent.

scholarly journals Spatial–temporal characterization of land subsidence induced by large area distribution of recent dredger fill

2020 ◽  
Vol 382 ◽  
pp. 131-135
Author(s):  
Jinxin Lin ◽  
Hanmei Wang ◽  
Tianliang Yang ◽  
Xinlei Huang
Keyword(s):  
Comparative Analysis ◽  
Land Subsidence ◽  
Large Scale ◽  
Soft Soil ◽  
Soil Layer ◽  
Geological Survey ◽  
Dredger Fill ◽  
Large Scale Land ◽  
And Control ◽  
Level Monitoring

Abstract. Large-scale land subsidence often occurs after large-scale land formation caused by dredger fill, which affects the sustainable development of the region. In order to prevent and control land subsidence in the area with dredger fill, the characteristics of land subsidence and its main influencing factors need to be studied. A typical region was examined using geological survey data, land-level monitoring and comparative analysis, to provide insight regarding the variability of dredger-fill characteristics and impacts on land subsidence. The geological survey results provided the information about burial distribution characteristics of dredger fill and its underlying soil layers. The land-level monitoring results were analyzed to characterize the spatial–temporal distribution of land subsidence. The comparative analysis of land subsidence with the formation time, soil properties, thicknesses of dredger fill and the lower soft soil layer provided information about the different impacts. The monitoring results show that the land subsidence of dredger fill areas was substantially larger than that of adjacent areas. The later the filling was formed, the thicker the filling is, and the more clay-rich the soil property and the thicker the soft soil layer is, the larger the land subsidence is. Finally, the future trend of land subsidence in the study area are given and some suggestions on the prevention and control of land subsidence are also given.

scholarly journals Extended D-TomoSAR Displacement Monitoring for Nanjing (China) City Built Structure Using High-Resolution TerraSAR/TanDEM-X and Cosmo SkyMed SAR Data

2019 ◽  
Vol 11 (22) ◽  
pp. 2623
Author(s):  
Fulong Chen ◽  
Wei Zhou ◽  
Caifen Chen ◽  
Peifeng Ma
Keyword(s):  
High Resolution ◽  
Radar Data ◽  
Structural Topology ◽  
Displacement Monitoring ◽  
Unknown Parameters ◽  
Thermal Dynamics ◽  
Persistent Scatterer ◽  
Motion Time ◽  
Nanjing City ◽  
Sar Data

The availability of high-resolution spaceborne synthetic aperture radar (SAR) data coupled with the ongoing refinement of tomographic SAR (TomoSAR) technology has made use of radar data feasible for preventive monitoring and assessment of built structures. In this study, we first applied extended differential TomoSAR (D-TomoSAR) to a set of 26 scenes of TerraSAR/TanDEM-X (TSX/TDX) (2013–2015) and 32 scenes of Cosmo-SkyMed (CSK) (2015–2017) images to estimate motions of skyscrapers, bridges and historical monuments in Nanjing City, China. The calculation and isolation of unknown parameters in the D-TomoSAR model, including linear velocity, thermal dynamics and structural heights, helped to estimate millimetric statistics of motion time series. Then, aforementioned two SAR datasets were tentatively tested using amplitude dispersion and phase stability indicators, highlighting the performance and sensitivity of X-band SAR in structural displacement monitoring. Experimental results demonstrated that motion indexes, e.g., heterogeneities of thermal amplitudes and spatiotemporal displacements, were useful to evaluate the conditions of built structures being monitored, in particular when their structural topology were visible owing to the enhanced density of persistent scatterer (PS) measurements. This study implies the value of high-resolution D-TomoSAR tools in the preventive monitoring and health diagnosis of built structures elsewhere over the world.

scholarly journals Surface Deformation from Sentinel-1A InSAR: Relation to Seasonal Groundwater Extraction and Rainfall in Central Taiwan

2019 ◽  
Vol 11 (23) ◽  
pp. 2817 ◽  
Author(s):  
Yi-Jie Yang ◽  
Cheinway Hwang ◽  
Wei-Chia Hung ◽  
Thomas Fuhrmann ◽  
Yi-An Chen ◽  
...  
Keyword(s):  
Land Subsidence ◽  
High Speed ◽  
Large Scale ◽  
Surface Deformation ◽  
Dry Season ◽  
Severe Drought ◽  
Groundwater Extraction ◽  
Large Scale Land ◽  
Small Baseline ◽  
Central Taiwan

Extracting groundwater for agricultural, aquacultural, and industrial use in central Taiwan has caused large-scale land subsidence that poses a threat to the operation of the Taiwan High Speed Railway near Yunlin County. We detected Yunlin subsidence using the Sentinel-1A Synthetic Aperture Radar (SAR) by the Small BAseline Subset (SBAS) method from April 2016 to April 2017. We calibrated the initial InSAR-derived displacement rates using GPS measurements and reduced the velocity difference between the two sensors from 15.0 to 8.5 mm/a. In Yunlin’s severe subsidence regions, cumulative displacements from InSAR and GPS showed that the dry-season subsidence contributed 60%–74% of the annual subsidence. The InSAR-derived vertical velocities matched the velocities from leveling to better than 10 mm/a. In regions with few leveling measurements, InSAR increased the spatial resolution of the vertical velocity field and identified two previously unknown subsidence spots over an industrial zone and steel factory. Annual significant subsidence areas (subsidence rate > 30 mm/a) from leveling from 2011 to 2017 increased with the declining dry-season rainfalls, suggesting that the dry-season rainfall was the deciding factor for land subsidence. A severe drought in 2015 (an El Niño year) dramatically increased the significant subsidence area to 659 km2. Both InSAR and leveling detected similarly significant subsidence areas in 2017, showing that InSAR was an effective technique for assessing whether a subsidence mitigation measure worked. The newly opened Hushan Reservoir can supply surface water during dry seasons and droughts to counter rain shortage and can thereby potentially reduce land subsidence caused by groundwater extraction.

ScanSAR interferometric processing using existing standard InSAR software for measuring large scale land deformation

2013 ◽  
Vol 51 ◽  
pp. 439-448 ◽  
Author(s):  
Cunren Liang ◽  
Qiming Zeng ◽  
Jianying Jia ◽  
Jian Jiao ◽  
Xi’ai Cui
Keyword(s):  
Large Scale ◽  
Land Deformation ◽  
Large Scale Land
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