Baseline Subset Interferometric Synthetic Aperture Research Articles

An Efficient and Fully Refined Deformation Extraction Method for Deriving Mining-Induced Subsidence by the Joint of Probability Integral Method and SBAS-InSAR

This study proposes a novel approach to derive the mining-induced goaf deformation, named the fully refined deformation extraction method (FRDEM). In this method, the Probability Integral Method (PIM) and the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technique are geographically integrated in a low-cost way to derive the fully refined goaf deformation and therefore to improve the detection ability for mining subsidence with fast deformation rate and large-gradient. To achieve this, we first established a functional relationship model to connect the 3-D parameters of PIM with SBAS-InSAR. Then, an improved genetic algorithm (IGA) was presented for parameter inversion, thus the optimal parameter set for PIM and the predicted displacements of the mining goaf was achieved economically. Afterward, we developed a geographically weighted data fusion model by presenting a data fusion strategy to eliminate the spatial heterogeneity in goaf boundary areas, and the fully refined goaf deformation field for the working face 2302 in the Guotun coal mining area was finally derived. Results demonstrate that FRDEM-derived displacements are highly consistent with field measurements, with RMSE decreasing to 0.053, 0.057, and 0.044 m respectively for the entire goaf, goaf center, and goaf boundary field, compared with those of ~0.092, ~0.095, and ~0.084 m for PIM and ~0.578, ~0.696, and ~0.046 m for SBAS-InSAR, respectively. This implies that the proposed FRDEM has significantly improved detection ability in deriving the mining-induced deformation, and thus can be a very promising tool to forecast and evaluate potential geohazards in the coal mining area.

Land subsidence prediction model based on its influencing factors and machine learning methods

Land subsidence has caused huge economic losses in the Beijing plains (BP) since 1980s. Building land subsidence prediction models that can predict the development of land subsidence is of great significance for improving the safety of cities and reducing economic losses in Eastern Beijing plains. The pattern of evolution of land subsidence is affected by many factors including groundwater level in different aquifers, thicknesses of compressible layers, and static and dynamic loads caused by urban construction. First, we used the small baseline subset Interferometric Synthetic Aperture Radar (SBAS‐InSAR) technology on 47 ENVISAT ASAR images and 48 RADARSAT‐2 images and used Persistent Scatterers Interferometric Aperture Radar (PS-InSAR) technology on 27 Sentinel-1 images to obtain the land subsidence monitoring results from June 2003 to September 2018. Second, the accuracy of the InSAR monitoring results was validated by using leveling benchmark land subsidence monitoring results. Finally, we built land subsidence rate prediction models and land subsidence gradient prediction models by combining land subsidence influencing factors and four machine learning methods including support vector machine (SVM), Gradient Boosting Decision Tree (GBDT), Random forest (RF) and Extremely Randomized Trees (ERT). The findings show: (1) The InSAR monitoring results revealed that the Beijing Plain has experienced serious land subsidence during the 2003–2010, 2011–2015 and 2016–2018 periods. (2): The InSAR monitoring results agreed well with the leveling benchmark monitoring results with the Pearson correlation coefficients of two monitoring results were all greater than 0.95 during the 2003–2010, 2011–2015 and 2016–2018 periods, respectively. (3): We found that the land subsidence prediction based on ERT method is the optimal model among four land subsidence prediction models and that the prediction performance of land subsidence prediction model based on ERT method will be greatly improved when apply this prediction model in sub study areas where the land subsidence mechanism is similar owning to the similar hydrogeological parameters.

Evolution of groundwater salinity and fluoride in the deep confined aquifers of Cangzhou in the North China plain after the South-to-North Water Diversion Project

The South-to-North Water Diversion Project (SNWDP) has greatly improved the water shortage in the North China Plain. However, the impact of the SNWDP on the evolution of groundwater chemistry, especially fluoride and salinity, was still unknown. Cangzhou, one of the recipient cities of SNWDP and suffered from severe land subsidence, was selected to collect the deep confined groundwater samples before and after the SNWDP. The results showed that groundwater fluoride concentration decreased after the SNWDP, with a median value of 4.39 mg/L in 2017 and 3.00 mg/L in 2021, respectively. This trend was more clearly observed in the land subsidence area, which could be related to the reduction of land subsidence, due to the stopping pumping of deep groundwater. The pore water in clayey sediments contains fluoride up to 7.02 mg/L, which can be released into groundwater due to the sediment compaction before the SNWDP. The extensive exploitation during last decades changed the groundwater recharge patterns, resulting in over 60% deep groundwater being recharged by the pore water released from clayey sediment. The results of the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) suggested that land subsidence has slowed down after the SNWDP, especially in the central area of land subsidence, thereby restricting the release of fluoride-rich pore water. However, groundwater salinity increased after the SNWDP, and the number of samples exceeding the drinking standard (TDS <1000 mg/L) increased by 26.4%. The rising groundwater level favors the water-rock interaction, promoting the dissolution of soluble minerals, for instance, halite, which was reflected by the results of inverse and forward modeling using the PHREEQC. Groundwater salinization after the SNWDP potentially induces the fluorite dissolution and causes the elevation of groundwater fluoride concentration. However, the calculated results indicate that the amount of F elevation related to groundwater salinization is significantly lower than the contribution of fluoride-rich pore water from clay sediment compaction. The findings of this study provide a comprehensive assessment of the influence of the SNWDP on the groundwater quality and some new insights for the management of groundwater resources.

Permafrost Early Deformation Signals before the Norilsk Oil Tank Collapse in Russia

Despite the profound roles of surface deformation monitoring techniques in observing permafrost surface stability, predetermining the approximate location and time of possibly occurring severe permafrost degradation before applying these techniques is extremely necessary, but has received little attention. Taking the oil tank collapse accident in the Norilsk region as a case, we explored this concern by analyzing the permafrost deformation mechanisms and determining early surface deformation signals. Regarding this case, we firstly applied the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technique to obtain its permafrost surface deformation rate, then utilized a sine model to decompose its interannual deformation and seasonal deformation, and finally compared the relationship between the topographic slope and deformation rate. Based on experimental results, we reveal that when the annual average temperature continuously increases at a rate of 2 °C/year for 2∼3 consecutive years, permafrost areas with relatively large topographic slopes (&gt;15°) are more prone to severe surface deformation during the summer thaw period. Therefore, this paper suggests that permafrost areas with large topographic slopes (&gt;15°) should be taken as the key surveillance areas, and that the appropriate monitoring time for employing surface deformation monitoring techniques should be the summer thawing period after a continuous increase in annual average temperature at a rate of 2 °C/year for 2∼3 years.

Monitoring Surface Deformation Associated With Soil Erosion in Loess Plateau With an Improved Small Baseline Subset Interferometric Synthetic Aperture Radar Algorithm

As a geomorphic process persistently occurring over the earth’s surface, soil erosion is one of the most serious environmental problems in the world nowadays, seriously threatening agriculture, natural resources, and ecosystem environments. Monitoring surface deformation associated with soil erosion will help to understand the dynamics of erosion process and the erosion mechanism. In this article, an improved small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) technique is proposed to monitor the surface deformation over the wind-water erosion crisscross region in the Loess Plateau, China. In particular, a new deformation model considering both of the internal factors and external factors of soil erosion is introduced into the SBAS-InASR algorithm. The results show that the cumulative deformation is close to −200 mm during the investigated period. The deformation rate caused by precipitation is between −0.03 and 0.02 mm/mm. When the wind erosion factor changes by 1 unit, the deformation range is approximately −0.3–0.2 mm. Also, researchers found that the surface deformation is highly correlated to precipitation and wind. The root mean square errors (RMSEs) of the residual deformations estimated from the proposed model are smaller than those estimated from the conventional linear and period models, demonstrating that the proposed method is more suitable to model and analyze the surface deformation in wind-water erosion crisscross region.

Contribution of ground ice melting to the expansion of Selin Co (lake) on the Tibetan Plateau

Abstract. Selin Co, located within permafrost regions surrounded by glaciers, has exhibited the greatest increase in water storage among all the lakes on the Tibetan Plateau over the last 50 years. Most of the increased lake water volume has been attributed to increased precipitation and the accelerated melting of glacier ice, but these processes are still not sufficient to close the water budget with the expansion of Selin Co. Ground ice meltwater released by thawing permafrost due to continuous climate warming over the past several decades is regarded as another source of lake expansion. This study presents the first attempt to quantify the water contribution of ground ice melting to the expansion of Selin Co by evaluating the ground surface deformation. We monitored the spatial distribution of surface deformation in the Selin Co basin using the small baseline subset (SBAS) interferometric synthetic aperture radar (InSAR) technique and compared the results with the findings of field surveys. Then, the ground ice meltwater volume in the watershed was calculated based on the cumulated settlement. Finally, this volume was compared with the lake volume change during the same period, and the contribution ratio was derived. SBAS-InSAR monitoring during 2017–2020 illustrated widespread and large subsidence in the upstream section of the Zhajiazangbu subbasin, where widespread continuous permafrost is present. The terrain subsidence rate was normally between 5 and 20 mm a−1, indicating rapid ground ice loss in the region. The ground ice meltwater was released at a rate of ∼57×106 m3 a−1, and the rate of increase in lake water storage was ∼485×106 m3 a−1 during the same period, with ground ice meltwater contributing ∼12 % of the lake volume increase. This study contributes to explaining the rapid expansion of Selin Co and equilibrating the water balance at the watershed scale. More importantly, the proposed method can be extended to other watersheds underlain by permafrost and help in understanding the hydrological changes in these watersheds.

Spatiotemporal evolution and surface response of land subsidence over a large-scale land creation area on the Chinese Loess Plateau

• The land-creation area shows exponentially decaying subsidence with fill compaction. • The long-term subsidence trend is primarily controlled by the fill thickness. • The significant ground subsidence zone varies as the land-creation area expands. • Most subsidence in YND will continue for about 7.2 years after InSAR observation. For Yan’an (China) and many other cities on the Loess Plateau, development is limited by a severe lack of available land. To support the city’s sustainable development, the Yan’an New District (YND) was constructed in 2012 through a mountain excavation and city construction (MECC) project. However, rapid land creation and urbanization have caused extensive anthropogenic land subsidence, which may impose new constraints on YND development. This study investigated the spatiotemporal development pattern and long-term temporal response of land subsidence related to land creation in the YND. First, 95 Sentinel-1 images acquired from 2016 to 2019 were analyzed with the small baseline subset (SBAS) interferometric synthetic aperture radar (InSAR) method to reveal the long-term displacement rates and spatiotemporal displacement patterns in the YND region. The interrelationship between the spatiotemporal variations in ground subsidence and the land creation history was also discussed. Then, an exponential model was employed to characterize the InSAR time series to assess the long-term displacement trends and temporal response of the land-subsidence process related to land creation. The results suggest that the observed long-term subsidence patterns in the land creation area showed an exponentially decaying trend with the fill compaction process. The newer and thicker the loess fill foundation was, the greater the subsidence rate and the smaller the decay trend over the same observation time, indicating slower stabilization relative to the compaction of the filling loess. The spatial variation in the significant land subsidence zone gradually shifted toward the newly formed fill area as the land creation area expanded. In addition, the ground displacement response estimates highlighted that most of the Qiaoergou subsidence zone in the YND will continue to sink for approximately 7.2 years following the InSAR observations used here. These findings have important implications for disaster mitigation and urban planning in similar large-scale land creation areas.

Characteristics of Freeze–Thaw Cycles in an Endorheic Basin on the Qinghai-Tibet Plateau Based on SBAS-InSAR Technology

The freeze–thaw (F-T) cycle of the active layer (AL) causes the “frost heave and thaw settlement” deformation of the terrain surface. Accurately identifying its amplitude and time characteristics is important for climate, hydrology, and ecology research in permafrost regions. We used Sentinel-1 SAR data and small baseline subset-interferometric synthetic aperture radar (SBAS-InSAR) technology to obtain the characteristics of F-T cycles in the Zonag Lake-Yanhu Lake permafrost-affected endorheic basin on the Qinghai-Tibet Plateau from 2017 to 2019. The results show that the seasonal deformation amplitude (SDA) in the study area mainly ranges from 0 to 60 mm, with an average value of 19 mm. The date of maximum frost heave (MFH) occurred between November 27th and March 21st of the following year, averaged in date of the year (DOY) 37. The maximum thaw settlement (MTS) occurred between July 25th and September 21st, averaged in DOY 225. The thawing duration is the thawing process lasting about 193 days. The spatial distribution differences in SDA, the date of MFH, and the date of MTS are relatively significant, but there is no apparent spatial difference in thawing duration. Although the SDA in the study area is mainly affected by the thermal state of permafrost, it still has the most apparent relationship with vegetation cover, the soil water content in AL, and active layer thickness. SDA has an apparent negative and positive correlation with the date of MFH and the date of MTS. In addition, due to the influence of soil texture and seasonal rivers, the seasonal deformation characteristics of the alluvial-diluvial area are different from those of the surrounding areas. This study provides a method for analyzing the F-T cycle of the AL using multi-temporal InSAR technology.

Using the SBAS InSAR technique to monitor surface deformation in the Kuqa fold-thrust belt, Tarim Basin, NW China

The Kuqa foreland fold-thrust belt is one of the key areas for gas exploration and a rare region with allochthonous salt outcrops well-preserved. In this study, twenty-eight Sentinel-1A Synthetic Aperture Radar (SAR) images acquired from 2015 to 2017 were utilized to detect and map the surface deformation in the western Kuqa fold-thrust belt (KFTB) based on the Small Baseline Subset (SBAS) Interferometric Synthetic Aperture Radar (InSAR) method. Spatial-temporal statistics analysis and comparison in different structural belts and geomorphology were made based on the inversion results. The results show that the spatial distribution characteristics of the surface deformation detected in subaerial salt structures are highly consistent with the previous studies, but the deformation rate in Daxiagu and Awate namakier increased to 25–35 mm/a. It indicates that the KFTB is still undergoing continuous north–south compression and shortening, which drives the underground salt to keep moving. Combined with the sufficient salt supply, increased activity of subaerial namakier and enhanced surface process in recent years, a variety of spatial–temporal surface deformation patterns are observed in the western KFTB. These varieties are attributed to the differences in structure and geomorphology in different belts, which can provide vital clues for exploring the roles of tectonics and surface processes in the spatial–temporal evolution of surface morphology in active tectonic regions.

Spatio-Temporal Evolution Law of Surface Subsidence Basin with Insufficient Exploitation of Deep Coal Resources in Aeolian Sand Area of Western China

Coal is one of the fundamental fossil energy supporting the world’s economy. The synergistic development between efficient coal mining and ecological environment protection is the inevitable requirement for the preservation of global harmony. As the world’s largest coal producer, China has conducted a strategic shift from east to west in terms of the exploitation of its energy resources, posing a serious threat to the fragile ecological environment of the western region. In particular, the surface subsidence caused by coal mining is the root of the ecological deteriotation and the destruction of ground structures. However, it is difficult to reveal the law of large-scale surface subsidence in western mining areas merely by conventional measurement methods such as leveling, on account of the high intensity of coal seam mining, the weakness of the lithology of overlying rock and the large thickness of wind-blown sand strata. In view of this, small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) technology was used in this study to obtain the time series of surface vertical displacement during the whole mining process of the 2401 working face in the Yingpanhao coal mine, Inner Mongolia. Based on the deformation data, the dynamic evolution characteristics of surface subsidence under high intensity mining in the western mining area were analyzed exhaustively. It was found that the surface subsidence is characterized by an extensive coverage range (48.52 km2) with minimal ground settlement (250 mm) in the study area. Meanwhile, the boundary shape of the subsidence basin followed a “circular-parallelogram-trapezoid” changeable process and the coverage area of the basin experienced three stages: a linear increasing period, a temporary stagnation period, and a re-expansion period. Furthermore, there existed an abnormal uplift phenomenon on the east side of the open-off cut in the 2401 working face. Combined with the structure of overlying strata, this paper carried out a preliminary analysis on the reasons of the abovementioned phenomenon. The research results are of vital realistic significance for ground buildings and ecological environmental protection in the aeolian sand mining area in Western China.

Analysis of the common model error on velocity field under Colored noise model by GPS and InSAR: A case study in the Nepal and everest region

The accuracy of the velocity field will be affected by the noise model and common mode errors through GPS time series analysis. In order to analyze the influence of these two factors on the accuracy of the velocity field, two kinds of data are used, including the three-year observation from 20 permanent GPS stations with high spatial correlation in the Everest, which is about 650 km from north to south and 1068 km from east to west, and three-year 80 ascending images and 141 descending images from sentinel-1A, which are processed by GAMIT/GLOBK software and Small Baseline Subset-Interferometric Synthetic Aperture Radar method (SBAS-InSAR), respectively. The vertical deformation rate is solved by time series analysis through a self-made adaptive algorithm. In the analysis, the linear change rate, period, half period coefficient, and residual sequence of all stations are solved by using James L. Davis periodic model. The noise type of residual sequence is analyzed by the power spectrum model. The spatio-temporal correlated noise, Common Mode Error (CME), is extracted by the Principal Component Analysis (PCA) and Karhunen-Loeve (KLE) methods. The results show that noises can be best described by “flicker noise + white noise” model. After the removal of CME, the R2 estimates of all stations are above 0.8, with RMS value of velocity field decreasing from 1.428 mm/yr to 1.062 mm/yr and 1.063 mm/yr to 0.815 mm/yr, in N and E directions, respectively, indicating that the influence of CME can't be ignored in the extraction of the high-precision velocity field in the Nepal and Everest region.

Inversion of Groundwater Storage Variations Considering Lag Effect in Beijing Plain, from RadarSat-2 with SBAS-InSAR Technology

The long-term over-exploitation of groundwater has not only caused the compaction of aquifer thickness and surface deformation but has also further aggravated the loss of groundwater storage (GWS) in Beijing plain. The South-to-North Water Diversion Project (SNWDP) furnishes a new source of water for Beijing. By reviewing related studies, it was found that there are few studies on the realization of GWS estimation based on InSAR technology considering the lag effect. Therefore, in this study, firstly, the long-time series deformation characteristics of Beijing plain were obtained from 46 RadarSat-2 images using small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) technology. Secondly, the seasonal components of surface deformation and hydraulic head change were extracted by means of multichannel singular spectrum analysis (MSSA), verifying the separation accuracy by means of Monto Carlo-SSA (MC-SSA). Finally, for the hydrodynamic delay (aquifer water supply/drainage) of the complex aquifer system, we introduced the time lag cross-correlation (TLCC) approach to correct the hysteresis response of seasonal deformation relative to the variation of the aquifer system head, so as to realize the estimation of aquifer storage properties and GWS loss, even unrecoverable GWS (UGWS). The results showed that the average annual variation of total GWS (TGWS) in Beijing plain was −6.702 × 107 m3, of which the depletion volume of UGWS was −6.168 × 107 m3, accounting for 92.03% of the TGWS. On a temporal scale, the depletion of UGWS lagged behind the total head change, with about one year of lag time. On a spatial scale, in contrast to the north of Beijing plain, the depletion of UGWS in the south only recovered briefly after 2015 and then continued to decline. This further indicated that the process of the decline of middle-deep confined head and long-term GWS loss caused by over-exploitation of groundwater was irreversible. These findings are of great significance to optimize the allocation of groundwater resources, reduce the harm of land subsidence and protect groundwater resources.

Permafrost Ground Ice Melting and Deformation Time Series Revealed by Sentinel-1 InSAR in the Tanggula Mountain Region on the Tibetan Plateau

In this study, we applied small baseline subset-interferometric synthetic aperture radar (SBAS-InSAR) to monitor the ground surface deformation from 2017 to 2020 in the permafrost region within an ~400 km × 230 km area covering the northern and southern slopes of Mt. Geladandong, Tanggula Mountains on the Tibetan Plateau. During SBAS-InSAR processing, we inverted the network of interferograms into a deformation time series using a weighted least square estimator without a preset deformation model. The deformation curves of various permafrost states in the Tanggula Mountain region were revealed in detail for the first time. The study region undergoes significant subsidence. Over the subsiding terrain, the average subsidence rate was 9.1 mm/a; 68.1% of its area had a subsidence rate between 5 and 20 mm/a, while just 0.7% of its area had a subsidence rate larger than 30 mm/a. The average peak-to-peak seasonal deformation was 19.7 mm. There is a weak positive relationship (~0.3) between seasonal amplitude (water storage in the active layer) and long-term deformation velocity (ground ice melting). By examining the deformation time series of subsiding terrain with different subsidence levels, we also found that thaw subsidence was not restricted to the summer and autumn thawing times but could last until the following winter, and in this circumstance, the winter uplift was greatly weakened. Two import indices for indicating permafrost deformation properties, i.e., long-term deformation trend and seasonal deformation magnitude, were extracted by direct calculation and model approximations of deformation time series and compared with each other. The comparisons showed that the long-term velocity by different calculations was highly consistent, but the intra-annual deformation magnitudes by the model approximations were larger than those of the intra-annual highest-lowest elevation difference. The findings improve the understanding of deformation properties in the degrading permafrost environment.

Time-Varying Surface Deformation Retrieval and Prediction in Closed Mines through Integration of SBAS InSAR Measurements and LSTM Algorithm

After a coal mine is closed, the coal rock mass could undergo weathering deterioration and strength reduction due to factors such as stress and groundwater, which in turn changes the stress and bearing capacity of the fractured rock mass in the abandoned goaf, leading to secondary or multiple surface deformations in the goaf. Currently, the spatiotemporal evolution pattern of the surface deformation of closed mines remains unclear, and there is no integrated monitoring and prediction model for closed mines. Therefore, this study proposed to construct an integrated monitoring and prediction model for closed mines using small baseline subset (SBAS) interferometric synthetic aperture radar (InSAR) and a deep learning-based long short-term memory (LSTM) neural network algorithm to achieve evolution pattern and dynamic prediction of spatiotemporal surface deformation of closed mines. Taking a closed mine in the western part of Xuzhou, China, as an example, based on Sentinel-1A SAR data between 21 December 2015, and 11 January 2021, SBAS InSAR technology was used to obtain the spatiotemporal evolution pattern of the surface during the 5 years after mine closure. The results showed that the ground surface subsided in the early stage of mine closure and then uplifted. In 5 years, the maximum subsidence rate in the study area is −43 mm/a, and the cumulative maximum subsidence is 310 mm; the maximum uplift rate is 29 mm/a, and the cumulative maximum uplift is 135 mm. Moreover, the maximum tilt and curvature are 3.5 mm/m and 0.19 mm/m2, respectively, which are beyond the safety thresholds of buildings; thus, continuous monitoring is necessary. Based on the evolution pattern of surface deformation, the surface deformation prediction model was proposed by integrating SBAS InSAR and an LSTM neural network. The experiment results showed that the LSTM neural network can accurately predict the deformation trend, with a maximum root mean square error (RMSE) of 5.1 mm. Finally, the relationship between the residual surface deformation and time after mine closure was analyzed, and the mechanisms of surface subsidence and uplift were discussed, which provide a theoretical reference for better understanding the surface deformation process of closed mines and the prevention of surface deformation.

Understanding the Slow Motion of the Wangjiashan Landslide in the Baihetan Reservoir Area (China) from Space‐Borne Radar Observations

The analysis of landslide evolution using archived optical remote‐sensing images is common, but it is often limited by the acquisition frequency, cloud cover, and resolution. With the development of space‐borne radar observation technology, small baseline subset interferometric synthetic aperture radar (SAR) technology provides a new technical approach for detecting landslide deformation before disasters. The Sentinel‐1A SAR datasets (20170219–20210330) were used to study the time‐series deformation characteristics of the Wangjiashan landslide in the Baihetan Reservoir area before its impoundment. The time‐series results show that the Wangjiashan landslide was in an initial deformation state in the prior four years, and the deformation first occurred in the middle part and then expanded to the landslide toe and crown retrogressive movement characteristics. Combined with an analysis of field deformation signs, these findings suggest that the upper landslide mass formed a local sliding surface, which caused serious deformation of the road. An analysis of historical rainfall data revealed that the Wangjiashan landslide is sensitive to rainfall, and the deformation is not only significantly correlated with cumulative rainfall but also influenced by concentrated heavy rainfall. The research in this study provides a basis for the monitoring, early warning, and risk management of the Wangjiashan landslide during the impoundment period. This work also provides a useful reference for investigations using space‐borne SAR Earth observations in geological disaster prevention and control.

Time-Series Analysis and Prediction of Surface Deformation in the Jinchuan Mining Area, Gansu Province, by Using InSAR and CNN–PhLSTM Network

Surface deformation poses a great threat to the safety of Jinchuan mining area production activities. At present, the spatio-temporal evolution law and mechanism of surface deformation in the Jinchuan mining area are unclear, and it is difficult to obtain reliable prediction results using the existing spatio-temporal prediction methods due to the lack of model parameters or relevant data. To solve these problems, this study proposes a new unified convolutional neural network with peephole long short-term memory (CNN-PhLSTM). Small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) technology was used to obtain the spatio-temporal evolution characteristics of surface deformation in the period of 2014–2021. Time series InSAR deformation data are merged into a unified network model in series with a time-distributed CNN segmentation and stacked PhLSTM. The InSAR measurement results are shown to be reliable by comparison and verification with the benchmark and InSAR results of different orbits. The proposed CNN-PhLSTM model was evaluated by mean absolute error and structural similarity (SSIM) evaluation indexes, and was compared with support vector regression (SVR), multilayer perceptron (MLP) and CNN-LSTM models. The results show three continuous subsidence areas, namely the Longshou, second western and third eastern mining areas. The cumulative surface deformation continued to increase from 2014 to 2021. Faults and lithology control the spatial distribution of surface deformation in the Jinchuan mining area. The prediction results demonstrate that the surface deformation range will continue to expand and that time-series surface deformation will show a slow deceleration trend in the next two years.

Tropical peat subsidence rates are related to decadal LULC changes: Insights from InSAR analysis

Peatlands in Indonesia are subject to subsidence in recent years, resulting in significant soil organic carbon loss. Their degradation is responsible for several environmental issues; however, understanding the causes of peatland subsidence is of prime concern for implementing mitigation measures. Here, we employed time-series Small BAseline Subset (SBAS) Interferometric Synthetic Aperture Radar (InSAR) using ALOS PALSAR-2 images to assess the relationship between subsidence rates and land use/land cover (LULC) change (including drainage periods) derived from decadal Landsat data (1972–2019). Overall, the study area subsided with a mean rate of −2.646 ± 1.839 cm/year in 2018–2019. The subsidence rates slowed over time, with significant subsidence decreases in peatlands after being drained for 9 years. We found that the long-time persistence of vegetated areas leads to subsidence deceleration. The relatively lower subsidence rates are in areas that changed to rubber/mixed plantations. Further, the potential of subsidence prediction was assessed using Random Forest (RF) regression based on LULC change, distance from peat edge, and elevation. With an R2 of 0.532 (RMSE = 0.594 cm/year), this machine learning method potentially enlarges the spatial coverage of InSAR method for the higher frequency SAR data (such as Sentinel-1) that mainly have limited coverage due to decorrelation in vegetated areas. According to feature importance in the RF model, the contribution of LULC change (including drainage period) to the subsidence model is comparable with distance from peat edge and elevation. Other uncertainties are from unexplained factors related to drainage and peat condition, which need to be accounted for as well. This work shows the significance of decadal LULC change analysis to supplement InSAR measurement in tropical peatland subsidence monitoring programs.

SBAS-InSAR-Based Analysis of Surface Deformation in the Eastern Tianshan Mountains, China

Due to the unique geographical characteristics of cold alpine and high-altitude regions, glaciers, permafrost, ground ice, rock glaciers, and other periglacial geomorphology have developed with fragile habitats, and these areas are often the birthplaces of many river basins and natural hazards. With global warming and the extensive cryogenesis and physical weathering, the thermal state of permafrost and the mass balance of glaciers have been changed, and thus it can be deduced that the surface deformation is of great concern. To obtain ground subsidence or uplift over a large area to understand local surface changes, the small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) technique was applied to process 89-scene of Sentinel-1A images ranging from December 25, 2017 to January 2, 2021 to obtain surface deformation for these 3 years for the eastern Tianshan Mountains, China. The surface deformation characteristics of the area were analyzed to provide a basic dataset for environmental protection policies and mitigation or reduction of natural hazards in this region, and to verify the applicability of SBAS-InSAR technology in alpine and high-altitude areas. The results show that the SBAS-InSAR technique processing with sentinel-1A dataset cannot be effectively used to acquire ground deformation in areas covered by trees, scrub/shrub, glaciers, snow, and ground ice, where the decohered phenomenon is serious. In other regions, SBAS-InSAR can effectively measure surface subsidence or uplift. Surface deformation is significant throughout the study area, with rates ranging from −70.7 to 50.8 mm/a and with an average rate of 1.1 mm/a. There are obvious regions of uplift in the northwest, northeast, and central sections of the study area, with uplift greater than 155.73 mm in 3 years, and three obvious regions of subsidence in the northeast and west sections of the study area, with subsidence of at least −125.20 mm in 3 years. The remaining areas of deformation are scattered, with smaller amounts of settlement and uplift and with an isolated and sporadic distribution. Areas with elevations of 3,150 to 4,275 m.a.s.l., slopes of 15°–50°, and southwest, west, and northwest aspects are geologic disaster-prone regions and should receive more attention and more field monitoring. The results of this study have important implications for local environmental protection and hazard prevention.

Land surface deformation in Nanchang, China 2018–2020 revealed by multi-temporal InSAR

With the influence of rapid urbanization, land subsidence in Nanchang has caused obvious surface cracks in urban roads. It is necessary to use effective deformation monitoring methods to grasp the current situation and causes of land subsidence in the urban area of Nanchang. Multi-temporal C-band Sentinel-1A images were processed by Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS InSAR) technique, and we obtained the land deformation in Nanchang urban area from 2018 to 2020. Deformation rate results show that most of the land in the study area was stable, and about 94% of the monitoring points had a deformation rate of −5 to 5 ​mm/year. However, small-scale subsidence occurred in the west, north, and south of the study area, with the maximum subsidence rate of −30 ​mm/year. Compared with the leveling data, InSAR-derived results reached the centimeter-level accuracy. Time-series deformation analysis reveals that the main factors causing land subsidence were urban constructions, including building construction, vehicle load, and Nanchang Metro operation. The most severe settlement in the study area was caused by vehicle load, which had significant spatial distribution characteristics. In addition, the acute subsidence that occurred in the construction and early operation stages of the metro gradually stabilized in less than two years.

Feasibility of Artificial Slope Hazards Identification in Regional Mountainous Highway Using SBAS-InSAR Technique: A Case Study in Lishui, Zhejiang

Safety status of artificial slopes is significant for the operation and maintenance of highway to mitigate the risk; thus, slope hazard identification is necessary. In order to realize large-area and low-cost application for regional highway, taking the Longqing Highway (length of 55 km) as a case study, the SBAS-InSAR (Small Baseline Subset-Interferometric Synthetic Aperture Radar) technique is adopted to detect the ground deformation and conduct hazard identification based on slope dip, aspect, geological data and historical hazard record. Field survey is carried out to verify the identified potential hazards. Results show that the detected potential hazards are distributed mainly in the areas consisting of granite residual and the Quaternary soil. Six potential hazards identified by the SBAS-InSAR-based method are roughly in accordance with the on-site verification. It is suggested that the SBAS-InSAR technique has the ability to obtain the slope deformation accurately and reveal the safe condition of the slopes. The SBAS-InSAR technique can be suitable for assistance in regional highway slope inspection.