scholarly journals Monitoring Coastal Reclamation Subsidence in Hong Kong with Distributed Scatterer Interferometry

2018 ◽  
Vol 10 (11) ◽  
pp. 1738 ◽  
Author(s):  
Qishi Sun ◽  
Liming Jiang ◽  
Mi Jiang ◽  
Hui Lin ◽  
Peifeng Ma ◽  
...  
Keyword(s):  
Hong Kong ◽  
Land Subsidence ◽  
Computational Efficiency ◽  
Ground Deformation ◽  
Image Data ◽  
Differential Settlement ◽  
Computational Time ◽  
Synthetic Aperture Radar Interferometry ◽  
Phase Optimization ◽  
Computational Time Cost

Land subsidence has been a significant problem in land reclaimed from the sea, and it is usually characterized by a differential settlement pattern due to locally unconsolidated marine sediments and fill materials. Time series Synthetic Aperture Radar Interferometry (InSAR) techniques based on distributed scatterers (DS), which can identify sufficient measurement points (MPs) when point-wise radar targets are lacking, have great potential to measure such differential reclamation settlement. However, the computational time cost has been the main drawback of current distributed scatterer interferometry(DSI) for its applications compared to the standard PSI analysis. In this paper, we adopted an improved DSI processing strategy for a fast and robust analysis of land subsidence in reclaimed regions, which is characterized by an integration of fast statistically homogeneous pixel selection based (FaSHPS-based) DS detection and eigendecomposition phase optimization. We demonstrate the advantages of the proposed DSI strategy in computational efficiency and deformation estimation reliability by applying it to two TerraSAR-X image data stacks from 2008 to 2009 to retrieve land subsidence over two typical reclaimed regions of Hong Kong International Airport (HKIA) and Hong Kong Science Park (HKSP). Compared with the state-of-the-art DSI methods, the proposed strategy significantly improves the computational efficiency, which is enhanced approximately 30 times in DS identification and 20 times in phase optimization. On average, the DSI strategy results in 7.8 and 3.7 times the detected number of MPs for HKIA and HKSP with respect to persistent scatter interferometry (PSI), which enables a very detailed characterization of locally differential settlement patterns. Moreover, the DSI-derived results agree well with the levelling survey measurements at HKIA, with a mean difference of 1.87 mm/yr and a standard deviation of 2.08 mm/yr. The results demonstrate that the proposed DSI strategy is effective at improving target density, accuracy and efficiency in monitoring ground deformation, particularly over reclaimed coastal areas.

Detecting land deformation due to groundwater changes with InSAR observations - the case of the island of Gotland, Sweden

2021 ◽  
Author(s):  
Mehdi Darvishi ◽  
Fernando Jaramillo
Keyword(s):  
Land Subsidence ◽  
Groundwater Level ◽  
Ground Deformation ◽  
Soil Depth ◽  
Ground Surface ◽  
Groundwater Depletion ◽  
Groundwater Levels ◽  
Small Baseline Subset ◽  
Small Baseline ◽  
The Baltic

<p>In the recent years, southern Sweden has experienced drought conditions during the summer with potential risks of groundwater shortages. One of the main physical effects of groundwater depletion is land subsidence, a geohazard that potentially damages urban infrastructure, natural resources and can generate casualties. We here investigate land subsidence induced by groundwater depletion and/or seasonal variations in Gotland, an agricultural island in the Baltic Sea experiencing recent hydrological droughts in the summer. Taking advantage of the multiple monitoring groundwater wells active on the island, we explore the existence of a relationship between groundwater fluctuations and ground deformation, as obtained from Interferometric Synthetic Aperture Radar (InSAR). The aim in the long-term is to develop a high-accuracy map of land subsidence with an appropriate temporal and spatial resolution to understand groundwater changes in the area are recognize hydroclimatic and anthropogenic drivers of change.</p><p>We processed Sentinel-1 (S1) data, covering the time span of 2016-2019, by using the Small BAseline Subset (SBAS) to process 119 S1-A/B data (descending mode). The groundwater level of Nineteen wells distributed over the Gotland island were used to assess the relationship between groundwater depletion and the detected InSAR displacement. In addition to that, the roles of other geological key factors such as soil depth, ground capacity in bed rock, karstification, structure of bedrock and soil type in occurring land subsidence also investigated. The findings showed that the groundwater level in thirteen wells with soil depths of less than 5 meters correlated well with InSAR displacements. The closeness of bedrock to ground surface (small soil depth) was responsible for high coherence values near the wells, and enabled the detection land subsidence. The results demonstrated that InSAR could use as an effective monitoring system for groundwater management and can assist in predicting or estimating low groundwater levels during summer conditions.</p>

scholarly journals Multi-Sensor InSAR Analysis of Progressive Land Subsidence over the Coastal City of Urayasu, Japan

2018 ◽  
Vol 10 (8) ◽  
pp. 1304 ◽  
Author(s):  
Yusupujiang Aimaiti ◽  
Fumio Yamazaki ◽  
Wen Liu
Keyword(s):  
Synthetic Aperture Radar ◽  
Survey Data ◽  
Land Subsidence ◽  
Ground Deformation ◽  
Tohoku Earthquake ◽  
Synthetic Aperture ◽  
Alos Palsar ◽  
The 2011 Tohoku Earthquake ◽  
L Band ◽  
Aperture Radar

In earthquake-prone areas, identifying patterns of ground deformation is important before they become latent risk factors. As one of the severely damaged areas due to the 2011 Tohoku earthquake in Japan, Urayasu City in Chiba Prefecture has been suffering from land subsidence as a part of its land was built by a massive land-fill project. To investigate the long-term land deformation patterns in Urayasu City, three sets of synthetic aperture radar (SAR) data acquired during 1993–2006 from European Remote Sensing satellites (ERS-1/-2 (C-band)), during 2006–2010 from the Phased Array L-band Synthetic Aperture Radar onboard the Advanced Land Observation Satellite (ALOS PALSAR (L-band)) and from 2014–2017 from the ALOS-2 PALSAR-2 (L-band) were processed by using multitemporal interferometric SAR (InSAR) techniques. Leveling survey data were also used to verify the accuracy of the InSAR-derived results. The results from the ERS-1/-2, ALOS PALSAR and ALOS-2 PALSAR-2 data processing showed continuing subsidence in several reclaimed areas of Urayasu City due to the integrated effects of numerous natural and anthropogenic processes. The maximum subsidence rate of the period from 1993 to 2006 was approximately 27 mm/year, while the periods from 2006 to 2010 and from 2014 to 2017 were approximately 30 and 18 mm/year, respectively. The quantitative validation results of the InSAR-derived deformation trend during the three observation periods are consistent with the leveling survey data measured from 1993 to 2017. Our results further demonstrate the advantages of InSAR measurements as an alternative to ground-based measurements for land subsidence monitoring in coastal reclaimed areas.

scholarly journals A Systematic Analysis of Big Image Data Methodologies in Various Applications

2020 ◽  
Vol 9 (5) ◽  
pp. 483-487
Keyword(s):  
Big Data ◽  
Deep Learning ◽  
Large Scale ◽  
Image Data ◽  
Computational Time ◽  
Process Data ◽  
Systematic Analysis ◽  
Large Scale Data ◽  
Learning Techniques ◽  
Effective Performance

Big data is large-scale data collected for knowledge discovery, it has been widely used in various applications. Big data often has image data from the various applications and requires effective technique to process data. In this paper, survey has been done in the big image data researches to analysis the effective performance of the methods. Deep learning techniques provides the effective performance compared to other methods included wavelet based methods. The deep learning techniques has the problem of requiring more computational time, and this can be overcome by lightweight methods.

scholarly journals Land subsidence modelling for decision making on groundwater abstraction under emergency situation

2020 ◽  
Vol 382 ◽  
pp. 403-408
Author(s):  
Masaatsu Aichi
Keyword(s):  
Decision Making ◽  
Monte Carlo ◽  
Uncertainty Analysis ◽  
Real Time ◽  
Land Subsidence ◽  
Null Space ◽  
Emergency Situation ◽  
Computational Time ◽  
Groundwater Abstraction ◽  
Emergency Situations

Abstract. This study presents an inversion scheme with uncertainty analysis for a land subsidence modelling by a Monte Carlo filter in order to contribute to the decision-making on the groundwater abstraction. For real time prediction and uncertainty analysis under the limited computational resources and available information in emergency situations, one dimensional vertical land subsidence simulation was adopted for the forward modelling and the null-space Monte Carlo method was applied for the effective resampling. The proposed scheme was tested with the existing land subsidence monitoring data in Tokyo lowland, Japan. The results demonstrated that the prediction uncertainty converges and the prediction accuracy improves as the observed data increased with time. The computational time was also confirmed to be acceptable range for a real time execution with a laptop.

On Improving Algorithm Efficiency of Gas-Kick Simulations toward Automated Influx Management: A Robertson Differential-Algebraic-Equation Problem Approach

2021 ◽  
pp. 1-24
Author(s):  
Chen Wei ◽  
Yuanhang Chen
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Model Prediction ◽  
Computational Efficiency ◽  
Prediction Accuracy ◽  
Numerical Scheme ◽  
Computational Time ◽  
Numerical Efficiency ◽  
Flow Models ◽  
Gas Kick

Summary Improved numerical efficiency in simulating wellbore gas-influx behaviors is essential for realizing real-time model-prediction-based gas-influx management in wells equipped with managed-pressure-drilling (MPD) systems. Currently, most solution algorithms for high-fidelitymultiphase-flow models are highly time consuming and are not suitable for real-time decision making and control. In the application of model-predictive controllers (MPCs), long calculation time can lead to large overshoots and low control efficiency. This paper presents a drift-flux-model (DFM)-based gas-influx simulator with a novel numerical scheme for improved computational efficiency. The solution algorithm to a Robertson problem as differential algebraic equations (DAEs) was used as the numerical scheme to solve the control equations of the DFM in this study. The numerical stability and computational efficiency of this numerical scheme and the widely used flux-splitting methods are compared and analyzed. Results show that the Robertson DAE problem approach significantly reduces the total number of arithmetic operations and the computational time compared with the hybrid advection-upstream-splitting method (AUSMV) while maintaining the same prediction accuracy. According to the “Big-O notation” analysis, the Robertson DAE approach shows a lower-order growth of computational complexity, proving its good potential in enhancing numerical efficiency, especially when handling simulations with larger scales. The validation of both the numerical schemes for the solution of the DFM was performed using measured data from a test well drilled with water-based mud (WBM). This study offers a novel numerical solution to the DFM that can significantly reduce the computational time required for gas-kick simulation while maintaining high prediction accuracy. This approach enables the application of high-fidelity two-phase-flow models in model-prediction-based decision making and automated influx management with MPD systems.

scholarly journals Application of Strongly Constrained Space Particle Swarm Optimization to Optimal Operation of a Reservoir System

2018 ◽  
Vol 10 (12) ◽  
pp. 4445 ◽  
Author(s):  
Lejun Ma ◽  
Huan Wang ◽  
Baohong Lu ◽  
Changjun Qi
Keyword(s):  
Particle Swarm Optimization ◽  
Computational Efficiency ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Optimal Operation ◽  
Computational Time ◽  
Particle Swarm Algorithm ◽  
Swarm Optimization ◽  
Swarm Algorithm ◽  
Low Efficiency

In view of the low efficiency of the particle swarm algorithm under multiple constraints of reservoir optimal operation, this paper introduces a particle swarm algorithm based on strongly constrained space. In the process of particle optimization, the algorithm eliminates the infeasible region that violates the water balance in order to reduce the influence of the unfeasible region on the particle evolution. In order to verify the effectiveness of the algorithm, it is applied to the calculation of reservoir optimal operation. Finally, this method is compared with the calculation results of the dynamic programming (DP) and particle swarm optimization (PSO) algorithm. The results show that: (1) the average computational time of strongly constrained particle swarm optimization (SCPSO) can be thought of as the same as the PSO algorithm and lesser than the DP algorithm under similar optimal value; and (2) the SCPSO algorithm has good performance in terms of finding near-optimal solutions, computational efficiency, and stability of optimization results. SCPSO not only improves the efficiency of particle evolution, but also avoids excessive improvement and affects the computational efficiency of the algorithm, which provides a convenient way for particle swarm optimization in reservoir optimal operation.

scholarly journals SBAS-InSAR Based Deformation Detection of Urban Land, Created from Mega-Scale Mountain Excavating and Valley Filling in the Loess Plateau: The Case Study of Yan’an City

2019 ◽  
Vol 11 (14) ◽  
pp. 1673 ◽  
Author(s):  
Qiong Wu ◽  
Chunting Jia ◽  
Shengbo Chen ◽  
Hongqing Li
Keyword(s):  
Loess Plateau ◽  
Land Subsidence ◽  
Surface Deformation ◽  
Land Uplift ◽  
Synthetic Aperture Radar Interferometry ◽  
Urban Buildings ◽  
Small Baseline Subset ◽  
Land Deformation ◽  
Small Baseline ◽  
Sbas Insar

Yan’an new district (YND) is one of the largest civil engineering projects for land creation in Loess Plateau, of which the amount of earthwork exceeds 600 million m3, to create 78.5 km2 of flat land. Such mega-scale engineering activities and complex geological characteristics have induced wide land deformation in the region. Small baseline subset synthetic aperture radar interferometry (SBAS-InSAR) method and 55 Sentinel-1A (S-1A) images were utilized in the present work to investigate the urban surface deformation in the Yan’an urban area and Yan’an new airport (YNA) from 2015 to 2019. The results were validated by the ground leveling measurements in the YNA. It is found that significant uneven surface deformation existed in both YND and YNA areas with maximum accumulative subsidence of 300 and 217 mm, respectively. Moreover, the average subsidence rate of the YND and YNA areas ranged from −70 to 30 mm/year and −50 to 25 mm/year, respectively. The present work shows that the land deformation suffered two periods (from 2015 to 2017 and from 2017 to 2019) and expanded from urban center to surrounding resettlement area, which are highly relevant with urban earthwork process. It is found that more than 60% of land subsidence occurs at filled areas, while more than 65% of surface uplifting occurs at excavation areas. The present work shows that the subsidence originates from the earth filling and the load of urban buildings, while the release of stress is the major factor for the land uplift. Moreover, it is found that the collapsibility of loess and concentrated precipitation deteriorates the degree of local land subsidence. The deformation discovered by this paper shows that the city may suffer a long period of subsidence, and huge challenges may exist in the period of urban maintaining buildings and infrastructure facilities.

scholarly journals Geodetic Study of the 2006–2010 Ground Deformation in La Palma (Canary Islands): Observational Results

2020 ◽  
Vol 12 (16) ◽  
pp. 2566
Author(s):  
Joaquín Escayo ◽  
José Fernández ◽  
Juan F. Prieto ◽  
Antonio G. Camacho ◽  
Mimmo Palano ◽  
...  
Keyword(s):  
Canary Islands ◽  
Surface Deformation ◽  
Ground Deformation ◽  
Satellite System ◽  
Point Of View ◽  
Synthetic Aperture Radar Interferometry ◽  
La Palma ◽  
Moderate Seismicity ◽  
Definition Of ◽  
Global Navigation Satellite

La Palma is one of the youngest of the Canary Islands, and historically the most active. The recent activity and unrest in the archipelago, the moderate seismicity observed in 2017 and 2018 and the possibility of catastrophic landslides related to the Cumbre Vieja volcano have made it strongly advisable to ensure a realistic knowledge of the background surface deformation on the island. This will then allow any anomalous deformation related to potential volcanic unrest on the island to be detected by monitoring the surface deformation. We describe here the observation results obtained during the 2006–2010 period using geodetic techniques such as Global Navigation Satellite System (GNSS), Advanced Differential Synthetic Aperture Radar Interferometry (A-DInSAR) and microgravimetry. These results show that, although there are no significant associated variations in gravity, there is a clear surface deformation that is spatially and temporally variable. Our results are discussed from the point of view of the unrest and its implications for the definition of an operational geodetic monitoring system for the island.

Ground deformation associated with the August 2019 eruption of Piton de la Fournaise (La Réunion Island) inferred from DInSAR measurements

2020 ◽  
Author(s):  
Vincenzo De Novellis ◽  
Francesco Casu ◽  
Claudio De Luca ◽  
Mariarosaria Manzo ◽  
Fernando Monterroso ◽  
...  
Keyword(s):  
Ground Deformation ◽  
Coseismic Deformation ◽  
Southeastern Part ◽  
Eruptive Fissure ◽  
Piton De La Fournaise ◽  
Synthetic Aperture Radar Interferometry ◽  
Small Baseline Subset ◽  
Small Baseline ◽  
Deformation Patterns ◽  
Eruptive Fissures

<p>Piton de la Fournaise volcano forms the southeastern part of La Réunion, an oceanic basaltic island in the southernmost part of Mascarene Basin (Indian Ocean). Five eruptions occurred at Piton in 2019, accompanied by seismic activity, lava flow, and lava fountaining. Here below, we focus on the fourth eruption occurred between August 11 and 15 on the southern-southeastern flank of the volcano, inside the Enclos Fouqué caldera. This eruption was characterized by the opening of two eruptive fissures. We retrieve the surface deformations induced by the eruptive activity through space-borne Differential Synthetic Aperture Radar Interferometry (DInSAR) measurements. First, we generated the coseismic deformation maps by applying the DInSAR technique to SAR data collected along ascending and descending orbits by the Sentinel-1 constellation of the European Copernicus Programme. The DInSAR technique allows us to analyze the deformation patterns caused by the 11 August 2019 eruption. We also retrieved the pre-eruptive deformation through the Small BAseline Subset (SBAS) DInSAR approach. Then, we modelled the DInSAR displacements to constrain the geometry and characteristics of the eruptive source. The modelling results suggest that the observed deformation can be attributed to the interaction between a shallow magma reservoir located at ~1.5-2 km depth below the summit, and the intrusion of a dike feeding the eruptive fissure inside the Enclos Fouqué caldera.</p><p><em>This work is supported by: the 2019-2021 IREA-CNR and Italian Civil Protection Department agreement; the EPOS-SP project (GA 871121); and the I-AMICA (PONa3_00363) project.</em></p>

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