Settlement Prediction of Reclaimed Coastal Airports with InSAR Observation: A Case Study of the Xiamen Xiang’an International Airport, China

Xiong, Zhiqiang; Deng, Kan; Feng, Guangcai; Lü, Miao; Li, Kaifeng; He, Chulu; He, Yuanrong

doi:10.3390/rs14133081

Cited by 11 publications

(3 citation statements)

References 37 publications

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“…Xiong (2022) calculated the deformation of the tailings pond in Salt Lake County, Utah, based on the multi-temporal InSAR method to calculate the deformation of the reclaimed land area of Xiamen Xiang’an International Airport, using only Sentinel-1 data without the help of other SAR data and hydrological data. After comparing the fitted curves calculated by the hyperbolic model, Poisson model, and exponential model, it was found that the exponential curve model and the Asaoka method could better predict the final settlement and the consolidation time [ 34 , 82 ].…”

Section: Discussionmentioning

confidence: 99%

SBAS-InSAR Based Deformation Monitoring of Tailings Dam: The Case Study of the Dexing Copper Mine No.4 Tailings Dam

Xie,

Wu,

Gao

et al. 2023

Sensors

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The No.4 tailings pond of the Dexing Copper Mine is the second largest in Asia. The tailing pond is a dangerous source of man-made debris flow with high potential energy. In view of the lack of effective and low-cost global safety monitoring means in this region, in this paper, the time-series InSAR technology is innovatively introduced to monitor the deformation of tailings dam and significant key findings are obtained. First, the surface deformation information of the tailings pond and its surrounding areas was extracted by using SBAS-InSAR technology and Sentinel-1A data. Second, the cause of deformation is explored by analyzing the deformation rate, deformation accumulation, and three typical deformation rate profiles of the representative observation points on the dam body. Finally, the power function model is used to predict the typical deformation observation points. The results of this paper indicated that: (1) the surface deformation of the tailings dam can be categorized into two directions: the upper portion of the dam moving away from the satellite along the Line of Sight (LOS) at a rate of −40 mm/yr, whereas the bottom portion approaching the satellite along the LOS at a rate of 8 mm/yr; (2) the deformation of the dam body is mainly affected by the inventory deposits and the construction materials of the dam body; (3) according to the current trend, deformation of two typical observation points in the LOS direction will reach the cumulative deformation of 80 mm and −360 mm respectively. The research results can provide data support for safety management of No.4 tailings dam in the Dexing Copper Mine, and provide a method reference for monitoring other similar tailings dams.

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Section: Discussionmentioning

confidence: 99%

SBAS-InSAR Based Deformation Monitoring of Tailings Dam: The Case Study of the Dexing Copper Mine No.4 Tailings Dam

Xie,

Wu,

Gao

et al. 2023

Sensors

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“…Yang Zhengrong 7 used the glacier deformation field and gray correlation analysis obtained by InSAR technology and revealed the relationship between glacier deformation and various factors such as temperature, precipitation, and slope. Xiong Zhiqiang 8 used the statistical properties of curve fitting to select the best curve model from several candidate curve models to predict the subsidence time series. Shi Xianlin 9 used the regenerative settlement information combined with InSAR technology and Terzaghi theory and the corresponding geological parameters of the artificial airport to successfully deduce the predicted settlement curve of the offshore artificial island airport.…”

Section: Introductionmentioning

confidence: 99%

Land subsidence analysis along high-speed railway based on EEMD-Prophet method

Dongwei,

Yuci,

Yuzheng

et al. 2024

Sci Rep

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Environmental changes and ground subsidence along railway lines are serious concerns during high-speed railway operations. It is worth noting that AutoRegressive Integrated Moving Average (ARMA), Long Short-Term Memory (LSTM), and other prediction methods may present limitations when applied to predict InSAR time series results. To address this issue, this study proposes a prediction method that decomposes the nonlinear settlement time series of feature points obtained through InSAR technology using Ensemble Empirical Mode Decomposition (EEMD). Subsequently, multiple Intrinsic Mode Functions (IMFs) are generated, and each IMF is individually predicted using the Prophet forecasting model. Finally, we employ an equal-weight superimposition method to combine the results, resulting in the prediction of the InSAR settlement time series. The predicted values of each component are subsequently weighted equally and combined to derive the final prediction outcome. This paper selects InSAR monitoring data along a high-speed railway in inland China and uses the proposed method and ARMA and Prophet models to carry out comparative experiments. The experimental results show that compared with the ARMA and Prophet models, the method in this paper improves the root mean square error by 58.01% and 32.3%, and increases the mean absolute error by 62.69% and 33.78%, respectively. The predicted settlement values generated by our method exhibit better agreement with the actual InSAR monitoring values.

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“…A comprehensive analysis and prediction of bad reclamation impacts must be held to prevent any further disadvantages that will also happen to society themselves (Li, 2014;Xiong et al, 2022). Thus, modeling and simulation can be chosen to be the most effective and efficient methods to achieve that goal.…”

Section: Introductionmentioning

confidence: 99%

The Rate of Modelling the Change of Hydrodynamic Components and Ecosystem Degradation due to the Existence of Coastal Reclamation Research in 2012-2022

Subiyanto

2024

IJRCS

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Reclamation is defined as an action made to increase the use of land resources while considering environmental and socioeconomic factors, such as landfilling and land drainage. Unfortunately, as man-made structures in the waters, coastal reclamation has the potential to significantly caused a disruption towards nature processes. This research aims to examine the pace of inquiry into the negative effects of coastal reclamation. The search was conducted using Publish or Perish Software, which was used to choose data sources in the form of Google Scholar from 2012-2022, and we applied a systematic Literature Review method. Identification and evaluation were carried out using two types of software such as Publish or Perish and VOSviewer. This research showed that China and India are the most frequent countries to be chosen as the area of interest related to this topic due to their experiences in handling a lot of coastal reclamations in their territorial. Mean-while, other countries such as Indonesia, Singapore, Malaysia, Philippines and some Europe Countries counted as the low rate areas for this type of publication even though they had a huge number of similar projects.

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Settlement Prediction of Reclaimed Coastal Airports with InSAR Observation: A Case Study of the Xiamen Xiang’an International Airport, China

Cited by 11 publications

References 37 publications

SBAS-InSAR Based Deformation Monitoring of Tailings Dam: The Case Study of the Dexing Copper Mine No.4 Tailings Dam

SBAS-InSAR Based Deformation Monitoring of Tailings Dam: The Case Study of the Dexing Copper Mine No.4 Tailings Dam

Land subsidence analysis along high-speed railway based on EEMD-Prophet method

The Rate of Modelling the Change of Hydrodynamic Components and Ecosystem Degradation due to the Existence of Coastal Reclamation Research in 2012-2022

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