Inferring subsidence characteristics in Wuhan (China) through multitemporal InSAR and hydrogeological analysis

Wuhan (China) is facing severe consolidation subsidence of soft soil and karst collapse hazards. To quantitatively explore the extent and causes of land subsidence in Wuhan, we performed multitemporal interferometry (MTI) analysis using synthetic aperture radar (SAR) data from the TerraSAR-X satellite from 2013 to 2017 and the Sentinel-1A satellite from 2015 to 2017. MTI results reveal four major subsidence zones in Wuhan, namely, Hankou (exceeding −6 cm/yr), Xudong-Qingshan (−3 cm/yr), Baishazhou-Jiangdi (−3 cm/yr), and Jianshe-Yangluo (−2 cm/yr). Accuracy assessment using 106 levelling benchmarks and cross-validation between the two InSAR-based results indicate an overall root-mean-square error (RMSE) of 2.5 and 3.1 mm/yr, respectively. Geophysical and geological analyses suggest that among the four major subsiding zones, Hankou, Xudong-Qingshan, and Jianshe-Yangluo are located in non-karstic soft soil areas, where shallow groundwater (< 30 m) declines driven by engineering dewatering and industrial water depletion contribute directly to soft soil compaction. Subsidence in the Baishazhou-Jiangdi zone develops in the karst terrain with abundant underground caves and fissures, which are major natural factors for gradual subsidence and karst collapse. Spatial variation analysis of the geological conditions indicates that the stage of karst development plays the most important role in influencing kart subsidence, followed by municipal construction, proximity to major rivers, and overlying soil structure. Moreover, land subsidence in this zone is affected more via coupling effects from multiple factors. Risk zoning analysis integrating subsidence horizontal gradient, InSAR deformation rates, and municipal construction density show that the high-risk areas in Wuhan are mainly distributed in the Tianxingzhou and Baishazhou-Jiangdi zone, and generally spread along the metro lines. © 202

Urban Deformation Monitoring using Persistent Scatterer Interferometry and SAR tomography

This book focuses on remote sensing for urban deformation monitoring. In particular, it highlights how deformation monitoring in urban areas can be carried out using Persistent Scatterer Interferometry (PSI) and Synthetic Aperture Radar (SAR) Tomography (TomoSAR). Several contributions show the capabilities of Interferometric SAR (InSAR) and PSI techniques for urban deformation monitoring. Some of them show the advantages of TomoSAR in un-mixing multiple scatterers for urban mapping and monitoring. This book is dedicated to the technical and scientific community interested in urban applications. It is useful for choosing the appropriate technique and gaining an assessment of the expected performance. The book will also be useful to researchers, as it provides information on the state-of-the-art and new trends in this fiel

OPAK FAULT DEFORMATION MONITORING USING SENTINEL-1 INSAR DATA FROM 2016-2019 IN YOGYAKARTA INDONESIA

The 2006 Yogyakarta earthquake occurred at 05.55 West Indonesia Time, May 27, 2006 with a magnitude of Mw 5.9. The earthquake had a great trauma effect for the community, because there were many fatalities, around 6,000 people died. Therefore, it is very important to conduct research to determine the deformation that is currently happening around the Opak Fault. In this research, during 2016-2019, we collected products for Sentinel-1 synthetic aperture radar interferometry (InSAR) to measure the current fault deformation. The InSAR data was processed using LiCSBAS, a time series analysis kit of open-source SAR interferometry (InSAR) that integrates with the automated Sentinel-1 InSAR processor (LiCSAR). In the processing scheme for LiCSBAS, interferograms with many unwrapping errors are automatically detected and removed via loop closure. Reliable time series and velocities are extracted using several noise indices with the help of masking. The location of the Opak Fault can be detected clearly in the result because the deformation pattern around the fault is contrary different. The west of Opak Fault shows an uplift movement, while the deformation occurred in east area of the fault shows subsidence movement. Keywords : Opak Fault, Crustal Deformation, Sentinel-1 InSAR Data, LiCSBA

Mapping the 2021 October Flood Event in the Subsiding Taiyuan Basin By Multi-Temporal SAR Data

A flood event induced by heavy rainfall hit the Taiyuan basin in north China in early October of 2021. In this study, we map the flood event process using the multi-temporal synthetic aperture radar (SAR) images acquired by Sentinel-1. First, we develop a spatiotemporal filter based on low-rank tensor approximation (STF-LRTA) for removing the speckle noise in SAR images. Next, we employ the classic log-ratio change indicator and the minimum error threshold algorithm to characterize the flood using the filtered images. Finally, we relate the flood inundation to the land subsidence in the Taiyuan basin by jointly analyzing the multi-temporal SAR change detection results and interferometric SAR (InSAR) time-series measurements (pre-flood). The validation experiments compare the proposed filter with the Refined-Lee filter, Gamma filter, and an SHPS-based multi-temporal SAR filter. The results demonstrate the effectiveness and advantage of the proposed STF-LRTA method in SAR despeckling and detail preservation, and the applicability to change scenes. The joint analyses reveal that land subsidence might be an important contributor to the flood event, and the flood recession process linearly correlates with time and subsidence magnitude.This work was financially supported by the National Natural Science Foundation of China (grant numbers 41904001 and 41774006), the China Postdoctoral Science Foundation (grant number 2018M640733), the National Key Research and Development Program of China (grant number 2019YFC1509201), and the National Postdoctoral Program for Innovative Talents (grant number BX20180220)

Exploiting satellite SAR for archaeological prospection and heritage site protection

Optical and Synthetic Aperture Radar (SAR) remote sensing has a long history of use and reached a good level of maturity in archaeological and cultural heritage applications, yet further advances are viable through the exploitation of novel sensor data and imaging modes, big data and high-performance computing, advanced and automated analysis methods. This paper showcases the main research avenues in this field, with a focus on archaeological prospection and heritage site protection. Six demonstration use-cases with a wealth of heritage asset types (e.g. excavated and still buried archaeological features, standing monuments, natural reserves, burial mounds, paleo-channels) and respective scientific research objectives are presented: the Ostia-Portus area and the wider Province of Rome (Italy), the city of Wuhan and the Jiuzhaigou National Park (China), and the Siberian “Valley of the Kings” (Russia). Input data encompass both archive and newly tasked medium to very high-resolution imagery acquired over the last decade from satellite (e.g. Copernicus Sentinels and ESA Third Party Missions) and aerial (e.g. Unmanned Aerial Vehicles, UAV) platforms, as well as field-based evidence and ground truth, auxiliary topographic data, Digital Elevation Models (DEM), and monitoring data from geodetic campaigns and networks. The novel results achieved for the use-cases contribute to the discussion on the advantages and limitations of optical and SAR-based archaeological and heritage applications aimed to detect buried and sub-surface archaeological assets across rural and semi-vegetated landscapes, identify threats to cultural heritage assets due to ground instability and urban development in large metropolises, and monitor post-disaster impacts in natural reserves

Monitoring active open-pit mine stability in the Rhenish coalfields of Germany using a coherence-based SBAS method

With the recent progress in synthetic aperture radar (SAR) technology, especially the new generation of SAR satellites (Sentinel-1 and TerraSAR-X), our ability to assess slope stability in open-pit mines has significantly improved. The main objective of this work is to map ground displacement and slope instability over three open-pit mines, namely, Hambach, Garzweiler and Inden, in the Rhenish coalfields of Germany to provide long-term monitoring solutions for open-pit mining operations and their surroundings. Three SAR datasets, including Sentinel-1A data in ascending and descending orbits and TerraSAR-X data in a descending orbit, were processed by a modified small baseline subset (SBAS) algorithm, called coherence-based SBAS, to retrieve ground displacement related to the three open-pit mines and their surroundings. Despite the continuously changing topography over these active open-pit mines, the small perpendicular baselines of both Sentinel-1A and TerraSAR-X data were not affected by DEM errors and hence could yield accurate estimates of surface displacement. Significant land subsidence was observed over reclaimed areas, with rates exceeding 500 mm/yr, 380 mm/yr, and 310 mm/yr for the Hambach, Garzweiler and Inden mine, respectively. The compaction process of waste materials is the main contributor to land subsidence. Land uplift was found over the areas near the active working parts of the mines, which was probably due to excavation activities. Horizontal displacement retrieved from the combination of ascending and descending data was analysed, revealing an eastward movement with a maximum rate of ∼120 mm/yr on the western flank and a westward movement with a maximum rate of ∼ 60 mm/yr on the eastern flank of the pit. Former open-pit mines Fortuna-Garsdorf and Berghein in the eastern part of Rhenish coalfields, already reclaimed for agriculture, also show subsidence, at locations reaching 150 mm/yr. The interferometric results were compared, whenever possible, with groundwater information to analyse the possible reasons for ground deformation over the mines and their surroundings

Spatial Variability of Relative Sea-Level Rise in Tianjin, China: Insight from InSAR, GPS, and Tide-Gauge Observations

The Tianjin coastal region in Bohai Bay, Northern China, is increasingly affected by storm-surge flooding which is exacerbated by anthropogenic land subsidence and global sea-level rise (SLR). We use a combination of synthetic aperture radar interferometry (InSAR), continuous GPS (CGPS), and tide-gauge observations to evaluate the spatial variability of relative SLR (RSLR) along the coastline of Tianjin. Land motion obtained by integration of 2 tracks of Sentinel-1 SAR images and 19 CGPS stations shows that the recent land subsidence in Tianjin downtown is less than 8 mm/yr, which has significantly decreased with respect to the last 50 years (up to 110 mm/yr in the 1980s). This might benefit from the South-to-North Water Transfer Project which has provided more than 1.8 billion cubic meters of water for Tianjin city since 2014 and reduced groundwater consumption. However, subsidence centers have shifted to suburbs, especially along the coastline dominated by reclaimed harbors and aquaculture industry, with localized subsidence up to 170 mm/yr. Combining InSAR observations with sea level records from tide-gauge stations reveals spatial variability of RSLR along the coastline. We find that, in the aquaculture zones along the coastline, the rates of land subsidence are as high as 82 mm/yr due to groundwater extraction for fisheries, which subsequently cause local sea levels to rise nearly 30 times faster than the global average. New insights into land subsidence and local SLR could help the country's regulators to make decisions on ensuring the sustainable development of the coastal aquaculture industry

Karst collapse risk zonation and evaluation in Wuhan, China based on analytic hierarchy process, logistic regression, and insar angular distortion approaches

The current study presents a detailed assessment of risk zones related to karst collapse in Wuhan by analytical hierarchy process (AHP) and logistic regression (LR) models. The results showed that the LR model was more accurate with an area under the receiver operating characteristic (ROC) curve of 0.911 compared to 0.812 derived from the AHP model. Both models performed well in identifying high-risk zones with only a 3% discrepancy in area. However, for the medium-and low-risk classes, although the spatial distribution of risk zoning results were similar between two approaches, the spatial extent of the risk areas varied between final models. The reliability of both methods were reduced significantly by excluding the InSAR-based ground subsidence map from the analysis, with the karst collapse presence falling into the high-risk zone being reduced by approximately 14%, and karst collapse absence falling into the karst area being increased by approximately 6.5% on the training samples. To evaluate the practicality of using only results from ground subsidence maps for the risk zonation, the results of AHP and LR are compared with a weighted angular distortion (WAD) method for karst risk zoning in Wuhan. We find that the areas with relatively large subsidence horizontal gradient values within the karst belts are generally spatially consistent with high-risk class areas identified by the AHP-and LR-based approaches. However, the WAD-based approach cannot be used alone as an ideal karst collapse risk assessment model as it does not include geological and natural factors into the risk zonation. © 2021 by the authors. Licensee MDPI, Basel, Switzerland

Ground deformation monitoring over Xinjiang coal fire area by an adaptive ERA5-corrected stacking-InSAR method

Underground coal fire is a global geological disaster that causes the loss of resources as well as environmental pollution. Xinjiang, China, is one of the regions suffering from serious underground coal fires. The accurate monitoring of underground coal fires is critical for management and extinguishment, and many remote sensing-based approaches have been developed for monitoring over large areas. Among them, the multi-temporal interferometric synthetic aperture radar (MT-InSAR) techniques have been recently employed for underground coal fires-related ground deformation monitoring. However, MT-InSAR involves a relatively high computational cost, especially when the monitoring area is large. We propose to use a more cost-efficient Stacking-InSAR technique to monitor ground deformation over underground coal fire areas in this study. Considering the effects of atmosphere on Stacking-InSAR, an ERA5 data-based estimation model is employed to mitigate the atmospheric phase of interferograms before stacking. Thus, an adaptive ERA5-Corrected Stacking-InSAR method is proposed in this study, and it is tested over the Fukang coal fire area in Xinjiang, China. Based on original and corrected interferograms, four groups of ground deformation results were obtained, and the possible coal fire areas were identified. In this paper, the ERA5 atmospheric delay products based on the estimation model along the LOS direction (D-LOS) effectively mitigate the atmospheric phase. The accuracy of ground deformation monitoring over a coal fire area has been improved by the proposed method choosing interferograms adaptively for stacking. The proposed Adaptive ERA5-Corrected Stacking-InSAR method can be used for efficient ground deformation monitoring over large coal fire areas.This research was supported in part by the National Natural Science Foundation of China (Grant No.41874044 and Grant No. 42004011), in part by project G2HOTSPOTS (PID2021-122142OB- I00) from the MCIN /AEI /10.13039 /501100011033 /FEDER, UE and in part by China Postdoctoral Science Foundation (Grant No. 2020M671646). At the same time, the research was also funded by the Construction Program of Space-Air-Ground-Well Cooperative Awareness Spatial Information Project (B20046) and National Key R&D Program of China (Grant No. 2022YFE0102600).Peer ReviewedPostprint (published version

Revealing the time lag between slope stability and reservoir water fluctuation from InSAR observations and wavelet tools— a case study in Maoergai Reservoir (China)

Reservoir water fluctuation in supply and storage cycle have strong triggering effects on landslides on both sides of reservoir banks. Early identification of reservoir landslides and revealing the relationship between slope stability and the triggering factors including reservoir level and rainfall, are of great significance in further protecting nearby residents’ lives and properties. In this paper, based on the small baseline subset time series method (SBAS-InSAR), the potential landslides with active displacements in the river bank of Maoergai hydropower station in Heishui County from 2018 to 2020 were monitored with Sentinel-1 data. As a result, a total of 20 unstable slopes were detected. Subsequently, it was found through a gray correlation analysis that the fluctuation of the reservoir water level is the main triggering factor for the displacement on unstable slopes. This paper applied wavelet tools to quantify the time lag between slope stability and reservoir water fluctuation, revealing that the displacement exhibits a seasonal trend, whose high-frequency signal displacement has an interannual period (1 year). Based on the Cross Wavelet Transform (XWT) analysis, under the interannual scale of one year, the reservoir water fluctuation and nonlinear displacement show a clear common power in wavelet. Additionally, a time lag of 65–120 days between slope stability and reservoir water fluctuations has been found, indicating that the non-linear displacements were behind the water level changes. Among the factors affecting the time lag, the elevation of the points and their distance to the bank shore show Pearson’s correlation coefficients of 0.69 and 0.70, respectively. The observed time lag and correlations could be related to the gradual saturation/drainage processes of the slope and the drainage path. This paper demonstrates the technical support to quantitatively reveal the time lag between slope stability and reservoir water fluctuation by InSAR and wavelet tools, providing strong support for the analysis of the mechanisms of landslides in Maoergai reservoir area.The work was supported by the National Natural Science Foundation of China (Grant No. 41801391), ESA-MOST China DRAGON-5 project (ref. 59339) and the State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Independent Research Project (SKLGP2020Z012) and Sichuan Science Foundation for Outstanding Youth (23NSFJQ0167)