ASAR Data Sets Research Articles

Integration of multi-sensor remote sensing, geological and geochemical data for delineation of Pb–Zn bearing carbonates of Middle Aravalli group in Zawar–Dungarpur Belt, NW India

The rocks of the Aravalli Protocontinent of NW India are enriched in lead–zinc bearing deposits amongst which the Zawar mineralized belt is one of the famous for base metal deposits and was mined since ancient times. In the present study, an attempt has been made to identify and map the extension of the mineralized belt and base metal prognostic zones using the integration of multi-sensor remote sensing, geological and geochemical data. Remote Sensing studies were carried out using ASTER, AVIRIS-NG, and ASAR datasets to understand the extension and associated structural features of host rocks (dolomite in the present case) of lead–zinc mineralization from the Middle Aravalli Group. Relative band depth (B6 + B9/B8) was used to delineate the dolomite of the region using the ASTER imagery. Mineral map was derived using the AVIRIS-NG dataset with the help of the MTMF algorithm. Multifrequency and multipolarization ASAR datasets demarcated the structural features in the complexly deformed rocks of the extended belt. The obtained results from remote sensing were validated with the help of geological and geochemical studies. Geological studies (field surveys and petrographic studies) confirmed the presence of dolomites and associative mafics. Mineralogical, major oxides and trace elements data further substantiated the presence of dolomite, associated sulfides such as galena, sphalerite, pyrite, and chalcopyrite, and lead, zinc and copper in the Zawar–Dungarpur Belt. Presence of chromium and nickel were observed through the trace element studies of dolomite belt. The trace elements interpolated maps were superimposed by traced structural maps using ASAR datasets. The densely populated E-W lineaments are considered the suitable zones for base metal accumulation. These lineaments carried the base metal bearing fluid along with a low concentration of Chromium and Nickel. Under the finding of this study, the northern head of Hati Magra and near Keekawat are the suitable zones for Pb–Zn sulfide mineralization.

Adaptive Fusion of Multi-Source Tropospheric Delay Estimates for InSAR Deformation Measurements

Atmospheric propagation delay correction is the key to improving the accuracy of deformation measurement of satellite interferometric synthetic aperture radar (InSAR). The empirical phase-elevation models and external data-based models present uneven performances of atmospheric delay correction for InSAR deformation monitoring. In this study, based on our previous fusion of delays predicted by multiple weather models (FDWM), we propose a new approach of adaptive fusion of multi-source tropospheric delay (AFMTD) estimates derived from multiple models over wide areas, i.e., ERA5, GACOS, WRF, MERRA2, NARR, MODIS, Linear model, and Powerlaw model. The spatially varying scaling algorithm is employed to refine the tropospheric delays predicted by the weather models. Meanwhile, we adopt a multiple-window strategy to cope with the spatially lateral variation of tropospheric delays. The AFMTD not only improves the spatial heterogeneity of tropospheric delay, but also adaptively combines multiple models to achieve a more reliable delay estimation. This AFMTD method is incorporated into the StaMPS-SBAS procedure. We compared the AFMTD with other single models using ENVISAT ASAR and Sentinel-1 datasets over Los Angeles of Southern California. The result of ASAR first demonstrates the effectiveness and reliability of the AFMTD method by referring to the assumed ground truth of simultaneous MERIS observations. The results of Sentinel-1 data show that over 95% of unwrapped interferograms have the minimum root-mean-square values after AFMTD correction for both descending and ascending tracks. The validation against GPS observation presents that the RMSEs of InSAR displacement time series after AFMTD correction decreases at more than 90% of 125 GPS stations. The average reductions of RMSE are 35.79% and 36.28% for descending and ascending data, respectively, and the maximum improvement is more than 70%. Overall, the proposed AFMTD method outperforms any single model for InSAR tropospheric delay correction and provides an open framework to fuse multi-source tropospheric delay estimates.

Estimation of regional surface deformation post the 2001 Bhuj earthquake in the Kachchh region, Western India using RADAR interferometry

The key objective of the present study is to estimate the surface displacement and to understand/monitor the active deformation pattern in the Kachchh region post the 2001 Bhuj Earthquake by implementing the Persistent Scatterer Interferometric Synthetic Aperture Radar (PSI) and Differential Interferometric Synthetic Aperture Radar (DInSAR) techniques. We employed the ENVISAT ASAR (15 images), ALOS PALSAR (6 pairs) and SENTINEL-1A (117 images) data sets acquired during the periods 2003–2005, 2007–2009, and 2016–2020 respectively. The PSI results of the Envisat dataset reveals that the Kachchh mainland region has undergone an average surface deformation of ± 22 mm/yr during 2003–2005. The maximum displacement observed from the ALOS PALSAR data sets (Window-1 to 6) during the period 2007–2009 is ∼ ± 1.2 cm. Further, the ground displacement observed from the Sentinel-1A dataset during the period 2016–2020 is ±16 mm/yr for the west-central region and 6 mm/yr uplift and 8 mm/yr subsidence in the eastern Kachchh mainland region. Surprisingly, high rate of deformation is detected towards the Pachham Island, Banni, Rann and the eastern region of the Kachchh after the 2001 Bhuj event. Correlating the results of different data sets, it is concluded that the deformation is high near the vicinity of the fault zones indicating the tectonically active nature of the faults. From the obtained results, we infer that, post the 2001 Bhuj earthquake, the surface displacement in the Kachchh mainland region is escalated till 2009 which is due to continuous aftershock activity and then started declining because of the ongoing seismic settlement. The acquired deformation rates are correlating well with the GPS derived displacement rates. Further, our results will assist in accurately demarcating the extent of the fault zones and also helps in precisely marking the areas undergoing active deformation, which will aid in micro zonation studies, mitigation planning and also for the preparation of an active tectonic map for the region.

Mapping Complete Three-Dimensional Ice Velocities by Integrating Multi-Baseline and Multi-Aperture InSAR Measurements: A Case Study of the Grove Mountains Area, East Antarctic

The Antarctic is one of the most sensitive areas to climate change, and ice velocity is a fundamental parameter for quantitatively assessing the glacier mass balance. Interferometric synthetic aperture radar (InSAR), a powerful tool for monitoring surface deformation with the advantages of having high precision and wide coverage, has been widely used in determining ice velocity in the Antarctic. However, the mapping of complete three-dimensional (3D) ice velocities is greatly limited by the imaging geometries and digital elevation model (DEM)-induced errors. In this study, we propose the integration of multibaseline and multiaperture InSAR measurements from the ENVISAT ASAR datasets to derive complete 3D ice velocities in the Grove Mountains area of the Antarctic. The results show that the estimated complete 3D ice velocities are in good agreement with MEaSUREs and GPS observations. Compared with the conventional 2D and quasi-3D ice velocities, the complete 3D ice velocities can effectively eliminate the effects of DEM errors and elevation changes and are also capable of retrieving the thickness change of the ice, which provides important information on the origin of mass transition.

THREE-DIMENSIONAL SUBSIDENCE MONITORING OF RECLAMATION AREA BASED ON TS-INSAR TECHNOLOGY

Abstract. This study used the Time Series Interferometric Synthetic Aperture Radar (TS-InSAR) technology and the ENVISAT ASAR dataset obtained between 2007 and 2010 and the Sentinel-1A dataset from 2017 to 2019 to determine the subsidence in the Shenzhen reclamation area, and used ASTER GDEM V2 to remove the phase jump caused by spectral decorrelation between bursts. Based on the time series of land subsidence of the reclamation area, a three-dimensional subsidence model of the reclamation area was established. By comparing and analyzing the subsidence results of two sets of satellite time series in the reclamation area, the temporal and spatial evolution of land subsidence and the cause of land subsidence in the reclamation area were analyzed. The results show that the test results of time series ENVISAT ASAR and Sentinel-1A have good continuity in subsidence spatialtemporal variation: From 2007 to 2010, the land subsidence in most areas of Shenzhen reclamation area is relatively stable, and the area where subsidence occurs is mainly distributed in Baoan District, the maximum subsidence rate in Baoan District is −23.12 mm/year. From 2017 to 2019, land subsidence in the reclamation area showed a tendency to spread and spread from west to east. The subsidence characteristics of Nanshan District are the most obvious, and the maximum subsidence rate is −17.52 mm/year.

Quantifying the contribution of multiple factors to land subsidence in the Beijing Plain, China with machine learning technology

Land subsidence is the ground surface response to underground space development, utilization and evolution. Presently, land subsidence has developed into a global, comprehensive and interdisciplinary complex systems problem. More than half a century has passed since the discovery of subsidence in the Beijing Plain in the 1960s. In this study, we investigate the land subsidence in the Beijing Plain over the period of 2003–2015 using ENVISAT ASAR and RADARSAT-2 interferometric datasets and the small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) technique. Furthermore, we introduced the data field model and index-based built-up index (IBI) to obtain the dynamic and static load information of the Beijing Plain. Then, based on a machine learning method, we selected the gradient lifting decision tree (GBDT) model to quantitatively analyze the contributions of groundwater level change, compressible deposit thickness and dynamic and static loads to land subsidence. The results showed that the maximum land subsidence rate was 122 and 141 mm/year in 2003–2010 and 2010–2015, respectively. Comparisons between the SBAS-InSAR results and leveling measurements showed that the minimum absolute error achieved was only 0.2 mm/year. We suggest that the groundwater exploitation in the third confined aquifer has greater impacts on land subsidence in the Beijing Plain than the other factors. The land subsidence likely occurred in compressible deposit thicknesses exceeding 90 m. Moreover, we found that the compressible thickness and groundwater level contributions to land subsidence exceeded 60%. Our results provide a scientific basis for the regulation and control of regional land subsidence.

Mapping the Yellow River Delta land subsidence with multitemporal SAR interferometry by exploiting both persistent and distributed scatterers

Due to highly compressible soil and a large amount of human activity, the costal deltas are more prone to ground subsidence. Many major costal deltas in the world are facing subsidence and are consequently more susceptible to flooding, salinization and seawater infusion or even permanent submergence. Therefore, ground subsidence has been a significant problem in coastal delta areas worldwide. The Yellow River Delta (YRD) is the second largest river delta in China. On the one hand, the YRD contains a large area of wetlands rich in biodiversity, and on the other hand, industrial activities and urbanization are extensive due to abundant underground resources such as oil, gas and brine. Excessive land use has caused different degrees of ground subsidence in this area. However, a detailed and comprehensive description of the ground subsidence pattern over the YRD has not been provided. Also, widespread non-urban area in Yellow River Delta region, such as wetlands, farmland and coastal tidal areas, hinders the application of persistent scatterer interferometry method (PSI) for comprehensive subsidence measurement over the whole area. In this paper, we developed a multitemporal InSAR method to map ground subsidence over the YRD area by exploiting both persistent scatterers (PS) and distributed scatterers (DS). This method is characterized by employing the coherence-weighted phase-linking algorithm for fast and reliable optimal phase reconstruction of each DS point and a two-tier network of PS and DS for the robust analysis of land subsidence. To extract the detailed and comprehensive ground subsidence over the whole YRD, we apply our method to 30 ENVISAT ASAR images (2007–2010) and 49 Sentinel-1A (S-1A) images (2015–2018) and obtain measurements of the ground subsidence during these two periods. Forty-one Sentinel-1B (S-1B) images (2016–2018) are also exploited for cross-sensor consistency validation with the result derived from the S-1A dataset. Our method shows a great advantage over the PSI method, providing much higher measuring point (MP) density in mapping land subsidence over the YRD, including 15-fold higher density for the ASAR dataset, 5.1-fold for the S-1A dataset and 5.3-fold for the S-1B dataset, which enables a very detailed description of local ground deformation patterns. Cross-track consistency in the derived measurements from the S-1A and S-1B datasets shows a standard deviation of 9.6 mm/yr for the vertical subsidence rate. A quantitative validation of the derived subsidence results compared with leveling measurements suggests an accuracy of 4.58 mm/yr for the standard deviation term. By comparing the ground deformation over the YRD during the periods of 2015–2018 and 2007–2010, we find that the subsidence in this region shows an overall intensification trend and many new and severe subsidence depressions appear along the coastline, with a maximum vertical subsidence rate of 432 mm/yr. Subsequently, the overextraction of underground brine for salt production is identified as the primary factor causing the ground subsidence near the YRD coastal area.

Early Detection of Landslide Hazards in Mountainous Areas of West China Using Time Series SAR Interferometry-A Case Study of Danba, Sichuan

As the most frequent and devastating geohazard next to earthquakes, landslides are widely distributed in mountainous areas of west China, which makes early detection of landslides a vital task for geologic disaster prevention. Although time series SAR interferometry (InSAR) based on repeat-pass satellite SAR observations has shown a great potential in landslide detection, its performance is usually limited by factors such as vegetation coverage, which leads to low reliability of detection results. Aiming at this problem, we carry out a case study by employing the coherent scatterer InSAR (CSI) method to successfully detect 17 unstable slopes in Danba County in the upper reach of Dadu River Basin from archived ALOS PALSAR and ENVISAT ASAR datasets. The effectiveness and advantage of the CSI method are demonstrated by comparisons with other observation data as well as validation against field survey. And, major impact factors for the performance of time series InSAR analysis in landslide investigations and future research topics of high priority are summarized.

Evaluation of tsunami inundation using synthetic aperture radar (SAR) data and numerical modeling

Little Andaman, the fourth largest island in the Andaman group of islands of India, was severely affected by the December 26, 2004, Indian Ocean tsunami generated by massive earthquake of moment magnitude 9.3 Mw which devastated the Andaman and Nicobar group of islands causing heavy damage to life and property. Due to hostile terrain conditions not much information was available on the extent of inundation and run-up along the island except for Hut Bay region. In order to study the vulnerability of the island to tsunami hazard, the inundation in the island due to the 2004 tsunami was studied using TUNAMI N2 numerical model and ENVISAT ASAR datasets. The extent of inundation derived from the SAR imagery was compared using the RTK-GPS field survey points collected in the Hut Bay regions immediately after the 2004 tsunami. The extent of inundation obtained from SAR images for the entire island was compared with inundation obtained from model. It was observed that the inundation obtained from the model matched well with inundation extent from SAR imagery for nearshore regions, while for low-lying areas and creeks large deviations were observed. In the absence of field datasets, the inundation derived from SAR imagery would be effective in providing ground data to validate the numerical models which can then be run for multiple scenarios for disaster mitigation and planning operation in areas that have hostile terrain conditions.

A multiscale subpixel mixture analysis applied for melt detection using passive microwave and radar scatterometer image time series of the Antarctic Peninsula (1999–2009)

ABSTRACTThis paper reports a comparative analysis performed on a fraction-image time series of the Antarctic Peninsula from the period 1999–2009 generated by multiresolution remote-sensing images (SSM/I and SSMI/S with 25 km and QuikSCAT with 2.225 km spatial resolutions) for snow-melt detection. Our method is based on the (a) preprocessing of multitemporal remote-sensing data, (b) subpixel mixture analysis of SSMI and QuikSCAT image time series, and (c) evaluation of subpixel analysis, including an assessment of fraction images of wet snow using an independent ASAR dataset and sensitivity analysis on the melt metrics measured by these images. The temporal dynamics of the melt indices derived from the wet-snow fraction images presented a more realistic pattern than the traditional melt metrics measured by Boolean snow-melt detection approaches. Because the snow melt actually occurs at the pixel fractions, the multiscale analysis that was performed suggests an overestimation of the melt metrics calculated using Boolean approaches (which assume that the entire area of the detected pixel shows snow melt). The melt metrics measurements show an overestimation according to the decrease in spatial resolution related to the multiplicative effect of a larger pixel area.

Fusion of space-borne multi-baseline and multi-frequency interferometric results based on extended Kalman filter to generate high quality DEMs

Repeat-pass Interferometric Synthetic Aperture Radar (InSAR) is a technique that can be used to generate DEMs. But the accuracy of InSAR is greatly limited by geometrical distortions, atmospheric effect, and decorrelations, particularly in mountainous areas, such as western China where no high quality DEM has so far been accomplished. Since each of InSAR DEMs generated using data of different frequencies and baselines has their own advantages and disadvantages, it is therefore very potential to overcome some of the limitations of InSAR by fusing Multi-baseline and Multi-frequency Interferometric Results (MMIRs). This paper proposed a fusion method based on Extended Kalman Filter (EKF), which takes the InSAR-derived DEMs as states in prediction step and the flattened interferograms as observations in control step to generate the final fused DEM. Before the fusion, detection of layover and shadow regions, low-coherence regions and regions with large height error is carried out because MMIRs in these regions are believed to be unreliable and thereafter are excluded. The whole processing flow is tested with TerraSAR-X and Envisat ASAR datasets. Finally, the fused DEM is validated with ASTER GDEM and national standard DEM of China. The results demonstrate that the proposed method is effective even in low coherence areas.

Monitoring of reclamation-induced ground subsidence in Macao (China) using PSInSAR technique

The long-term reclamation-induced ground subsidence in Macao, a coastal city of southern China was investigated. Persistent scatterer interferometry (PSI) technique was applied to retrieve the deformation rate in Macao during the period from April 2003 to August 2010 with a total of 41 scenes of descending ASAR data sets. The PSI-retrieved results show a relatively stable pattern in Macao Peninsula, Taipa Island and Coloane Island, with an average subsidence velocity of −3 mm/a. In contrast, relatively large subsidence rates are highlighted in Cotai area, a new reclamation land in 1990s, in which an average subsidence velocity is about −10 mm/a. A consistent relationship between the PSI results and the leveling measurements indicate that this PSI technique is an effective tool to monitor the reclamation-induced ground subsidence with a high accuracy and adequate spatial details. Accordingly, the valuable ground subsidence results generated by PSI can be used not only for early detection and remedial activities of potential settlement of building, but also for helping the local government to formulate regional sustainable development planning and decision-making in disaster prevention and mitigation.

훈련 자료의 임의 선택과 다중 분류자를 이용한 원격탐사 자료의 분류

이 논문에서는 원격탐사 자료의 분류를 목적으로 서로 다른 훈련 집단들과 분류자들로부터 생성된 분류 결과들을 결합하는 분류 틀을 제안하였다. 제안 분류 틀의 핵심 부분은 서로 다른 훈련 집단과 분류자들을 이용함으로써 분류 결과 사이의 다양성을 증가시켜서 결과적으로 분류 정확도를 향상시키는데 있다. 제안 분류 틀에서는 우선 서로 다른 샘플링 밀도를 가지는 서로 다른 훈련 집단들을 생성한 후에, 이들을 서로 다른 구분 능력을 나타내는 분류자들의 입력 훈련 자료로 사용한다. 그리고 초기 분류 결과들에 다수결 규칙을 적용하여 최종 분류 결과를 얻게 된다. 다중 시기 ENVISAT ASAR 자료를 이용한 토지 피복 분류사례 연구를 통해 제안 방법론의 적용 가능성을 검토하였다. 사례 연구에서 3개의 훈련 집단과 최대우도 분류자, 다층 퍼셉트론 분류자, support vector machine 등과 같은 3개의 분류자를 이용한 9개의 분류 결과를 결합하였다. 사례 연구 결과, 제안 분류 틀 안에서 토지 피복 구분에 관한 상호 보완적인 정보의 이용이 가능해져서 가장 높은 분류 정확도를 나타내었다. 서로 다른 결합들을 비교하였을 때, 다양성이 크지 않은 분류 결과들을 결합한 경우에는 분류 정확도의 향상이 나타나지 않았다. 따라서 다중 분류 시스템의 설계시 분류자들의 다양성을 확보하는 것이 중요함을 확인할 수 있었다. In this paper, a classifier ensemble framework for remote sensing data classification is presented that combines classification results generated from both different training sets and different classifiers. A core part of the presented framework is to increase a diversity between classification results by using both different training sets and classifiers to improve classification accuracy. First, different training sets that have different sampling densities are generated and used as inputs for supervised classification using different classifiers that show different discrimination capabilities. Then several preliminary classification results are combined via a majority voting scheme to generate a final classification result. A case study of land-cover classification using multi-temporal ENVISAT ASAR data sets is carried out to illustrate the potential of the presented classification framework. In the case study, nine classification results were combined that were generated by using three different training sets and three different classifiers including maximum likelihood classifier, multi-layer perceptron classifier, and support vector machine. The case study results showed that complementary information on the discrimination of land-cover classes of interest would be extracted within the proposed framework and the best classification accuracy was obtained. When comparing different combinations, to combine any classification results where the diversity of the classifiers is not great didn't show an improvement of classification accuracy. Thus, it is recommended to ensure the greater diversity between classifiers in the design of multiple classifier systems.

Surface deformation caused by April 6th 2009 earthquake in L’Aquila (Italy): A comparative analysis from ENVISAT ASAR, ALOS PALSAR and ASTER

Surface deformations in L’Aquila (centre of Italy) caused by the April 6th, 2009 earthquake were studied from space geodesy and remote sensing points of view using Synthetic Aperture Radar Interferometry (InSAR) and Sub-pixel Correlation Technique (SCT). InSAR was used to measure ground surface deformation in the satellite line of sight (LOS) direction and the deformation was determined using two separate interferometric pairs of ENVISAT ASAR and ALOS PALSAR data sets. Furthermore, SCT was employed to investigate the horizontal displacements in the area. Two separate pairs of ENVISAT ASAR and ASTER optical image data sets were employed, and horizontal displacements in Range/Azimuth and in west–east/south–north directions were investigated, respectively.Maximum 28.1cm subsidence in LOS direction was observed on the descending interferogram of the ENVISAT ASAR data set, to the north-west of Onna village. The initial coseismic surface deformation started from the north of the main event epicentre. Most of the post-seismic relaxation occurred after April 7th, toward the south and south-east of the main shock epicentre, and results from SCT showed that the horizontal displacement was not significant on the surface (not more than a few centimetres).

Spatial and temporal deformation characteristics of marine alluvial deposits due to land reclamation: implications from InSAR observation and geotechnical estimate

AbstractGround deformation of reclaimed land is a key issue for reclamation design, construction and sustainable development in coastal areas as this consolidation process of the underlying compressible marine sediment sequences over very long‐time periods could lead to damage of both ground constructions and underground facilities. In this case study, we have investigated the spatial and temporal characteristics of residual reclamation settlement of Chek Lap Kok Airport, Hong Kong, one of the largest land reclamation projects worldwide. A total of 25 time series ENVISAT ASAR datasets, acquired between December 2003 and October 2008, were used to retrieve settlement rates and deformation history at high resolution and accuracy by means of advanced Synthetic Aperture Radar Interferometry (InSAR). The InSAR‐derived results show a fairly homogenous and stable pattern in the sectors of the airport site corresponding to the two original islands of Chek Lap Kok and Lam Chau. In contrast, a relatively high spatial settlement variability, ranging from moderate (3–7?mm/yr) to strong (>10?mm/yr) settlement rates, was discovered within the majority of the reclaimed portion of the airport. A joint analysis of InSAR observations and geological materials indicates that the variability of the recorded residual settlement was highly correlated with the variations of thickness and pre‐consolidation state of alluvial deposits below the reclamation. A quantitative comparison analysis also has been carried out between time series InSAR observations and theoretical estimates of residual settlement modelled by geotechnical investigations. The results imply that a primary consolidation process in alluvial deposits below the reclamation might be delayed with respect to the predicted results and may still have been occurring in most reclaimed areas during the investigation period (2003–2008); the time to complete it could stretch to decades depending on hydraulic conductivity and natural drainage conditions. Copyright © 2010 John Wiley & Sons, Ltd.

Integrated analysis of SAR interferometric and geological data for investigating long-term reclamation settlement of Chek Lap Kok Airport, Hong Kong

We investigated the long-term reclamation settlement of Chek Lap Kok Airport, Hong Kong, one of the largest reclamation projects worldwide. An advanced InSAR technique was applied to two independent ASAR data sets along ascending (25 scenes) and descending (22 scenes) orbits acquired between 2003 and 2008, and allowed us to generate deformation velocity maps and displacement time series for the investigated area. Intercomparison of deformation velocity results from the two ASAR data sets and their validation against leveling survey measurements were carried out in order to assess accuracy and reliability of the InSAR observations. The intercomparison and validation results demonstrated the potential of elaborate InSAR processes on local-scale areas to monitor and detect a long-term residual settlement in such complex reclamation area. The InSAR-derived deformation velocity maps showed a fair stability in areas of the two original rocky islands of Chek Lap Kok and Lam Chau, and on most of the buildings at the site due to foundation on piles reaching the granite bedrock, whereas a generally moderate (3–7 mm/year) to strong (> 10 mm/year) and spatially variable settlement trend was detected in the majority of reclamation areas of the airport. The consistent relationship we found between the observed settlement pattern and the underlying geological conditions suggested that this recoded differential settlement was mainly related to the variations in thickness and soil properties of both the fill materials and the alluvial deposits below the reclamation. A geological and geotechnical interpretation of the lithostratigraphy of the alluvial deposits beneath the reclamation implied that the relatively large settlement rate measured up to 2008 was resulted from a still active primary consolidation process.