Differential Interferometric Synthetic Aperture Radar Research Articles

ADVANCED ANALYSIS TOOLS FOR THE EUROPEAN GROUND MOTION SERVICE DATA

Abstract. This paper is focused on Advanced Differential Interferometric SAR (A-DInSAR). In the first part, the paper describes the European Ground Motion Service (EGMS), a new service of the Copernicus Land Monitoring Service. The EGMS provides consistent, regular, standardized, harmonized and reliable information regarding natural and anthropogenic ground motion over Europe. It is derived from A-DInSAR analysis of Copernicus Sentinel-1 data. The EGMS includes three main products: Basic, i.e. basic deformation maps delivered for individual and consistent frames of image stacks; Calibrated, i.e. deformation map integrated into a reference Global Navigation Satellite System network; and Ortho, which includes the East-West and Up-Down deformation, obtained by combining the ascending and descending results. The second part of the paper describes examples of data analysis. The first one is a clustering of PSI results, which highlights the so-called Active Deformation Areas (ADAs). The second one is an automatic classification of the ADAs. The third analysis concerns the differential deformation maps, which are useful to highlight areas where high deformation gradients occur. Such gradients are often associated to damages in buildings and infrastructures.

Co-seismic surface displacement of the June 21, 2022 MW6 Khōst, Afghanistan earthquake from InSAR observations

A robust estimation of the earthquake location, seismic moment, and fault geometry is essential for objective seismic hazard assessment. Seismic events in a remote location, specifically in the absence of seismic and GNSS networks, can be investigated effectively using the InSAR-based technique. This study adopts the Differential Interferometric SAR (DInSAR) technique to quantify the co-seismic surface displacement caused by the June 21, 2022, Khōst MW6 earthquake that occurred along the western plate boundary between the Indian and Eurasian plate. The interferograms show that the maximum surface deformation occurred on the northwest and southwest of the fault line. From coherence, the Line of Sight (LOS) displacement, and the co-seismic surface displacement analysis, it has been observed that surface deformation was most pronounced in the southwest region of the fault line, and the surface has moved to the opposite direction along the fault line, which indicates a sinistral slightly oblique strike-slip movement. This InSAR-based observation appears consistent with the seismic waveforms derived from co-seismic surface displacements. Further, it has been argued that the slip deficit accumulated during the period of the last about 48 years along the frontal region of the northward extension of the Suleiman range and associated fault zone is qualitatively estimated at about 1.5 m, which is consistent with the seismic waveforms derived finite slip model.

Reconnaissance to characterisation of land subsidence due to groundwater overdraft and oil extraction in and around Mehsana City, Gujarat, India by long-term hybrid differential interferometric SAR technique

We present a framework for studying reconnaissance to characterisation of land subsidence in the slowly subsiding city of Mehsana, Gujarat, India, due to groundwater overdraft and oil extraction. Considering interferometric synthetic aperture radar (InSAR) data availability constraints, we first conducted a long-term conventional Differential InSAR (DInSAR) investigation followed by time-series advanced DInSAR analyses by Persistent Scatterer InSAR (PSInSAR). We identified land subsidence in different parts of the study area, with subsidence rates ranging from ≤ -1 cm/yr to ≥ -3 cm/yr. During the entire observation period (2004–2019), the core urban area has been consistently subsiding with differential subsidence rates of −1.7 to −2.1 cm/yr during 2004–2006, −1.6 to −1.7 cm/yr during 2007–2011 and −2.6 to −2.9 cm/yr during 2016–2018 in conventional DInSAR and −2.5 to −3.2 cm/yr in advanced DInSAR. The subsidence measurements by collateral DInSAR observations in multifrequency and/or multi-imaging modes during 2016–2017 agree well in terms of the spatial extent of subsiding areas and the rates of subsidence. We characterised land subsidence in four type areas due to the diverse causes based on the temporal behaviour of land subsidence: (a) densely-populated city centre, (b) dairy plants and other industries in urban/peri-urban areas, (c) emerging urban clusters in peri-urban/rural areas, and (d) oilfields with agri-horticulture farms in the rural areas. We found a consistently increasing land subsidence trend in ‘a’, reducing land subsidence in ‘b’, newly emerging and rapidly growing land subsidence in ‘c’, and spatially-extensive subtle land subsidence in ‘d’. From the temporal nature of groundwater level (GWL) decline and land subsidence, we inferred that the land subsidence has been occurring primarily due to groundwater overdraft associated with urban growth, industry and agri-horticultural farms and secondarily due to oil extraction in the southeastern part of the study area. A comparison of annual rainfall difference from the long-term average vs GWL change vs land subsidence shows that the rainfall deficit during 2–3 consecutive years and groundwater overdraft are primarily related to land subsidence in the study area.

A Comprehensive Review on Mining Subsidence and its Geo-environmental Impact

Over the course of several decades, subsidence has exerted a notable impact on the mining sector. The preponderance of subsidence occurrences is evident within coal mines. Remote sensing and Geographic Information Systems (GIS) have emerged as principal instruments for the evaluation and characterization of subsidence phenomena. The manifestation of mininginduced subsidence engenders concerns encompassing roof collapse, infrastructural damage, and the formidable challenge of preserving human lives. The repercussions of mining-related subsidence extend to indigenous flora and subterranean water reservoirs. This phenomenon critically impedes the sustainable advancement of mining zones, precipitates the depletion of natural reservoirs, and engenders a host of ecological and environmental predicaments that cast an adverse influence on socio-economic dynamics. Within mining contexts, subsidence manifests as both vertical and horizontal ground displacement, presenting as fissures, depressions, troughs, and sinkholes. The present article furnishes a comparative discourse on diverse methodologies harnessed for the assessment of mining-induced subsidence. The scholarly community has employed a repertoire of eight predominant techniques, as delineated in the conclusive remarks of this study. Over the bygone two decades, considerable strides have been taken, enabling the deployment of sophisticated paradigms, such as remote sensing and GIS, Light Detection and Ranging (LiDAR), and Differential Interferometric Synthetic Aperture Radar (DiNSAR), for the identification and quantification of land subsidence phenomena.

LOS Deformation Correction Method for DInSAR in Mining Areas by Fusing Ground Data without Control Points

The traditional leveling, total station, and global navigation satellite system (GNSS) and the new differential interferometric synthetic aperture radar (DInSAR) and terrestrial laser scanning (TLS) systems have their own advantages and limitations in the deformation monitoring of mining areas. It is difficult to obtain accurate deformation information only using single-source measurement data. In this study, we propose an LOS deformation correction method for DInSAR in mining areas by fusing ground data without control points. Based on free space data, small deformations at the edges of mining influence areas accurately obtained using DInSAR. By combining leveling/GNSS and TLS methods, it was possible to obtain large deformations in central areas without the need for control points located outside the mining influence range. For overcoming the non-uniform coordinates of the “space–ground” data and the limited overlap of the effective measurement ranges, the subsidence prediction model was employed to assist in its fusion. In addition, in LOS deformation correction, we retained the non-full cycle phase of DInSAR and replaced the full cycle phase with the one from the data fusion. Engineering experiments have shown that the correction results preserve the differences in the LOS deformations at the edge areas of the mine influence range, and they recover the lost LOS deformations at the center areas. Using the difference in the LOS deformation before and after correction as the verification indicator, the maximum absolute value of the errors after correction was 143 mm, which was approximately 6.4% of the maximum LOS deformation. In addition, there were still two errors that were large (−112 mm and −89 mm, respectively), and the absolute values of errors were not more than 75 mm. For all errors, the mean absolute value was 36 mm. Compared with 399 mm before correction, the error was reduced by 91%. This study provides technical support and theoretical reference for deformation monitoring and control in mining areas.

Analysis of Vertical Deformation and Potential Formation of New Faults Cause by Earthquake Using the DInSAR Method (Case Study: 2022 Cianjur Earthquake)

In this study, we focus on the repetitive nature of earthquakes along known fault lines and their potential to create new fault segments. Our primary aim is to enhance our understanding of fault patterns and distribution, facilitating more efficient and accurate earthquake disaster mitigation efforts. Our research specifically targets the vertical deformation resulting from the 2022 Cianjur Earthquake. To achieve this, we employed a sophisticated technique involving data processing from the Sentinel 1A satellites using the Differential Interferometric Synthetic Aperture Radar (DInSAR) method. This method allowed us to derive earthquake-induced displacement values in meters with an impressive level of accuracy, down to the centimeter scale. Our analysis revealed a conspicuous fringe pattern in the interferogram phase data, which did not align with the nearby Cimandiri Fault. This discrepancy led us to suspect the emergence of a new fault or fault segment. By comparing Sentinel 1A satellite images before and after the earthquake, we observed phase differences ranging from -3.112 to 3.117 phases. These recurring phase differences clustered at coordinates 6?48'48" South Latitude and 107?06'05" East Longitude, pinpointing the epicenter of the Cianjur earthquake on November 21, 2022. Furthermore, we calculated line-of-sight (LoS) displacement values ranging from 0 to minus 102 millimeters, indicating vertical subsidence in the vicinity of the 2022 Cianjur earthquake. In conclusion, our research underscores the utility of the DInSAR method for assessing Earth's surface deformation patterns, making it a valuable tool for various earthquake-related analyses.

Identification of Vulnerability Due to the Pasaman M6.2 Earthquake on 25 February 2022 Using Satellite-Based Methods and Field Surveys

The Pasaman earthquake which occurred on 25 February 2022, with a magnitude of 6.2, caused casualties and infrastructure damage. Vulnerability identification determines the potential extent to which a system or unit tends to be damaged. Vulnerability identification in this study was carried out based on four vulnerability indicators, namely: rate of soil movement from satellite image processing, soil type classification based on Vs30, corrected isoseismal shakemap, and residential area maps. Each indicator, with their respective weightage, is then scored and summed to evaluate the vulnerability of areas in the vicinity of Pasaman earthquake. The processing of Sentinel-1 SLC satellite data using the advanced Differential Interferometric Synthetic Aperture Radar (DInSAR) produces a deformation rate around area of epicenter. Areas that have high vulnerability generally have a value of ground movement rate in the form of subsidence above 5 cm/year. These areas were predominantly residential and experienced significant damage during the earthquake. The soil type in these regions was classified as medium soil, and the intensity of shocks during the earthquake was categorized as VI MMI or higher. This study was conducted in the area near the epicenter of the Pasaman earthquake, such as in the district Pasaman, Bonjol, Pasaman, Palembaya, and Lubuk Basung. A study of disaster vulnerability identification is carried out to reduce the losses and minimizing the exposure of the population to disasters. The results of vulnerability identification can be used as part of education and literacy to reduce the risk of earthquake disasters.

The 2023 Mw 7.8 and 7.6 Earthquake Doublet in Southeast Türkiye: Coseismic and Early Postseismic Deformation, Faulting Model, and Potential Seismic Hazard

Abstract On 6 February 2023, Mw 7.8 and 7.6 earthquakes struck southeast Türkiye and northwest Syria. They are the largest earthquakes in Türkiye in over 80 yr, causing significant damage and fatalities. We used Advanced Land Observation Satellite-2 and Sentinel-1 Synthetic Aperture Radar images to obtain near-field coseismic displacements by Differential Interferometric Synthetic Aperture Radar (DInSAR) and pixel offset tracking (POT). Discontinuities of the surface deformation suggest that the Mw 7.8 event ruptured ∼320 km along the East Anatolian fault, and the Mw 7.6 event ruptured ∼150 km near Elbistan, southern Türkiye. We inverted these earthquakes' fault geometry and slip distribution based on Global Navigation Satellite Systems, DInSAR, and POT displacements. The estimated fault slip model shows that the first Mw 7.8 event ruptured a steeply southeast-dipping fault, and the seismogenic fault of the second Mw 7.6 event is north-dipping with complex geometry. The dip angle of subfaults of the Mw 7.6 earthquake decreases from east to west. Faults responsible for the two earthquakes are dominated by left-lateral strike-slip motion, with the maximum slip of ∼9.1 m. Early postseismic deformation within two months exhibits displacement discontinuities in the Amanos and Pazarcık segments and the Çardak fault, suggesting that the afterslip partially compensated the coseismic slip deficit at the shallow depths. Furthermore, static Coulomb failure stress changes induced by the two earthquakes indicate that the southwestern Pütürge segment of the East Anatolian fault has a high risk of future rupture.

The Stability Analysis of Mt. Gongga Glaciers Affected by the 2022 Luding MS 6.8 Earthquake Based on LuTan-1 and Sentinel-1 Data

On 5 September 2022, an MS 6.8 earthquake occurred in Luding county, Sichuan province, China, with the epicenter located approximately 20 km from the main peak of Mount (Mt.) Gongga. The dynamic situation of Mt. Gongga glaciers has received widespread attention. In this study, Mt. Gongga was selected as the study area, and L-band LuTan-1 (LT-1) satellite data were used for differential interferometric synthetic aperture radar (D-InSAR) processing to obtain the coseismic landform in Luding. Based on Sentinel-1A images, pixel offset tracking (POT) technology was used to obtain the surface movement velocities of the glaciers before, during, and after the earthquake. The results showed that the overall preseismic movement of the glaciers was fast in the area where the ice cascade of the Hailuogou Glacier reached a maximum average deformation rate of 0.94 m/d. Moreover, time-series monitoring of the postseismic glaciers showed that the surface flow velocities of some glaciers in the study area increased after the earthquake. The flow velocity at the main peak of Mt. Gongga and the tongue of the Mozigou Glacier accelerated for a period after the earthquake. The study concluded that the earthquake was one of the direct causes of the increase in glacier flow velocity, which returned to a stable state more than 70 days after the earthquake. The relevant monitoring results and research data can provide a reference for earthquake-triggered glacial hazards and indicate the effectiveness of LT-1 in identifying and monitoring geological hazards.

VALIDATION OF FULL-RESOLUTION DINSAR-DERIVED VERTICAL DISPLACEMENT IN CULTURAL HERITAGE MONITORING: INTEGRATION WITH GEODETIC LEVELLING MEASUREMENTS

Abstract. Towards revealing the potential of satellite Synthetic Aperture Radar (SAR) Interferometry (InSAR) for efficient detection and monitoring of Cultural Heritage (CH) encouraging resilient built CH, this study is devoted to the validation of InSAR-derived vertical displacements with a full-resolution perspective taking advantage of high-precision geodetic levelling measurements. Considering the Cathedral of Como, northern Italy, as the case study, two different Persistent Scatterer Interferometry (PSI) techniques have been applied to Cosmo-SkyMed high-resolution SAR images acquired in both ascending and descending orbit tacks within the time interval of 2010–2012. Besides using the simplified approach for obtaining the vertical displacement velocity from Line of Sight (LOS) velocity, a weighted, localized, multi-track Vertical Displacement Extraction (VDE) approach is proposed and evaluated, which uses the technical outcome of Differential InSAR (DInSAR) and spatial information. The results, using a proper PSI technique, showed that the accuracy level of extracted vertical displacement velocities in a full-resolution application is ca. 0.6 [mm/year] with a dense concentration of InSAR-Levelling absolute errors lower than 0.3 [mm/year] which are reliable and reasonable levels based on the employed validation framework in this study. Also, the weighted localized VDE can significantly decrease the InSAR-Levelling errors, adding to the reliability of the InSAR application for CH monitoring and condition assessment in practice.

Coseismic Source Model of the February 2023 Mw 6.8 Tajikistan Earthquake from Sentinel-1A InSAR Observations and Its Associated Earthquake Hazard

On 23 February 2023, an Mw 6.8 earthquake struck the border of Tajikistan and Xinjiang China, the source mechanism remains controversial according to different seismic inversions. To better comprehend the source characteristics and the surface deformation pattern, we used the ascending and descending orbital Sentinel-1A SAR data to obtain the coseismic deformation of this earthquake based on the traditional two-pass differential interferometric synthetic aperture radar (InSAR). The source model is inverted from the InSAR coseismic deformation results. The possible Coulomb Failure Stress (CFS) transfer is analyzed based on the preferred source model. The results illustrate that the earthquake ruptured a blind left-lateral strike-slip fault of strike 28.1° with a maximum slip of 1.53 m and the total geodetic moment is 1.99 × 1019 N·m (Mw 6.83). The strike direction and the fault characteristics suggest the Seismogenic fault is a secondary fault of the Sarez–Karakul Fault System. The 2015 Mw 7.2 Sarez Earthquake plays a triggering role in the occurrence of the 2023 Tajikistan earthquake. Earthquake hazard on Sarez–Karakul Fault System and Sarez–Murghab Thrust System is enhanced due to the Coulomb stress loaded by the Tajikistan earthquake.

Performance Analysis of Channel Imbalance Control and Azimuth Ambiguity Suppression in Azimuth Dual Receiving Antenna Mode of LT-1 Spaceborne SAR System

The LuTan-1(LT-1), known as the L-band differential interferometric synthetic aperture radar (SAR) satellite system, is an essential piece of civil infrastructure in China, providing extensive applications such as surface deformation monitoring and topographic mapping. To achieve high-resolution and wide-swath (HRWS) observation abilities, the LT-1 takes the dual receiving antenna (DRA) imaging mode as its working mode. However, amplitude and phase errors between channels lead to a mismatch between the reconstruction filter and the multichannel echo signal, worsen the reconstructed azimuth spectrum, and introduce ambiguity targets in the final imaging results, seriously affecting the final imaging quality. In order to better evaluate the channel error and azimuth ambiguity performance of the LT-1 system, this paper proposed an advanced channel consistency correction method and conducted many measured data experiments. The experimental results show that the proposed method is effective, and the LT-1 system has excellent channel error control and azimuth ambiguity performance.

Monitoring the subsidence at different periods in high underground water level coal mine areas using differential interferometric synthetic aperture radar (D-InSAR)

Monitoring the subsidence at different periods in high underground water level coal mine areas can provide a data basis for land reclamation. For the purpose of monitoring subsidence in I working face located in Guotun Coal Mine, 22 Sentinel-1 images were processed by using differential interferometric synthetic aperture radar (D-InSAR). After dividing subsidence periods, the characteristics and monitoring accuracy at different subsidence periods were explored. The results showed that: (1) The formation of single-gradient subsidence funnel is an important sign to identify active period. (2) The root mean square error (RMSE) and mean absolute error (MAE) in central area of subsidence are reduced by 50% and 49%, respectively, compared with those in edge area. (3) The monitoring accuracy is high at different subsidence periods. The coefficient of determination (R2) can reach more than 0.89. Therefore, D-InSAR technique can accurately monitor the subsidence at different periods based on Sentinel-1 data.

The complexity of identifying and quantifying natural and anthropogenic influences on surface movement in coal seam gas producing regions within the Surat Basin, Queensland

Coal seam gas (CSG) production can cause surface movement through the compaction of coal seams and adjacent geological units and may cause subtle changes in the topographic gradients that have been alleged to cause impacts on agriculture. Since surface movement can result from both natural and anthropogenic processes, the determination of which processes, and the magnitudes of their contributions, are important challenges in the management of impacts. Differential interferometric synthetic aperture radar (D-InSAR) is a proven remote sensing technique used to monitor large-scale surface movement via radar satellite imagery. It is currently used by major CSG producers to conduct monitoring over their tenements. As D-InSAR can only deduce total observed movement, integration with other datasets is required to deconvolve the influences within observations. This paper provides an overview of the range of processes that influence surface movement. A case study using a D-InSAR time-series dataset (2016–2022) reveals the surface movement in the Surat Basin. Velocity measurements show that surface movement in the vicinity of CSG wells ranges between −18 and +9 mm/year. Analysis of any correlations between landscape characteristics and surface movement is provided, along with preliminary findings on some key observations. This work aids in refining calculations on what proportion of surface movement may be attributable to gas extraction.

Reservoir Ice Conditions from Multi-Sensor Remote Sensing and ERA5-Land: The Manicouagan Hydroelectric Reservoir Case Study

Reservoir ice can have an important impact on the watershed scale and influence hydraulic operations. On the other hand, hydropower generation can also impact the ice regime. In this study, multi-source satellite and ERA5-land data are used to evaluate ice conditions. Specifically, ice-controlling variables (temperature, water levels), ice regime (cover/deformation, thickness) and their interrelations are assessed for a 5-year period from 2017 to 2021. The methodology is applied to the Manicouagan reservoir, one of the largest hydropower reservoirs in Quebec, Canada. The satellite-based land surface temperatures (LSTs) suggest that winter 2021 was the hottest one. Overall, MODIS and Landsat LSTs agree with the ERA5-land temperatures. Ice backscatter from Sentinel-1 indicates that, in general, the reservoir is completely covered by ice from January to March. A correlation of 0.6 and 0.8 is observed between C- and Ku-band Synthetic Aperture Radar (SAR) signal and ice thickness, respectively. Important ice changes inferred from Differential Interferometric SAR (D-InSAR) occur approximately at the position where the largest ERA5-land ice thickness differences are observed. Winter water levels are also evaluated using satellite altimetric data to verify their influence on the ice dynamics. They show a decreasing tendency as the winter advances.

ASSESSMENT OF LAND DEFORMATION AND LAND USE RELATIONSHIP IN GARMSAR ALLUVIAL FAN USING SENTINEL-1 DATA

Abstract. Differential Synthetic Aperture Radar Interferometry (DInSAR) allows displacements to be detected with millimeter accuracy as well as more advanced methods, such as Persistent Scatterer Interferometry (PSI). Sentinel-1 data have been collected systematically under the COPERNICUS program at a high temporal resolution with global coverage, helping us to build a wide user community and develop miscellaneous SAR-based applications. In the Garmsar alluvial fan, the long-term groundwater overexploitation due to agricultural and urban demands, the utilization of urban space, and erosion have led to land deformation. In this study, the analysis of land subsidence in Garmsar fan was assessed by using the Differential Interferometric Synthetic Aperture Radar (DInSAR) technique based on 20 Sentinel-1 SAR images from January 2019 to June 2022. Distinct variations of land subsidence were found in the study regions however, it can be seen in most land use types. The maximum annual land subsidence rate has occurred in urban areas with an average rate of 95.2 mm/year from 2019 to 2022. Analysis showed that serious land subsidence mainly occurred in the following land use types: urban areas, agricultural lands, and bare lands.

Aseismic creep and gravitational sliding on the lower eastern flank of Mt. Etna: Insights from the 2002 and 2022 fault rupture events between Santa Venerina and Santa Tecla

Fault creep along the lower eastern flank of Mt. Etna volcano has been documented since the end of the 19th century and significantly contributes to the surface faulting hazard in the area. On 29 October 2002, during a seismic swarm related to dyke intrusions, two earthquakes caused extensive damage and surface faulting in an area between the Santa Venerina and Santa Tecla villages. On the same day after the two earthquakes, an episodic aseismic creep occurred along the Scalo Pennisi Fault close to the Santa Tecla coastline. On 8 February 2022, during another aseismic creep event along the Scalo Pennisi Fault, we observed the reopening of the pre-existing 2002 ground ruptures mostly as pure dilational fractures. We mapped the 2002 and 2022 surface ruptures, and collected data on displacement, length, and pattern of ground breaks. Ground ruptures affected structures located along the activated fault segments, including roads, walls and buildings. The 2002 surface faulting propagation can be ascribed to a sliding of the Mt. Etna eastern flank toward the SE, as also suggested by the related shallow seismicity, and InSAR and geodetic data between 2002 and 2005. For the 2022 event, differential InSAR data, acquired in both descending and ascending views, allowed us to decompose Line of Sight (LOS) displacement into horizontal and vertical components. We detect a ∼ 700 m long and ∼ 500 m wide deformation zone with a downward and eastward motion (max displacement ∼1,5 cm) consistent with a normal fault. We inverted the InSAR–detected surface deformation using a uniform-slip fault model and obtained a shallow detachment for the causative fault, located at ∼300 m depth, within the volcanic pile. This is the first in-depth study along the Scalo Pennisi Fault to suggest a shallow faulting that accommodates Mt. Etna E flank gravitational sliding.

An Adaptive Identification Method for Potential Landslide Hazards Based on Multisource Data

The effectiveness of landslide disaster prevention depends largely on the quality of early identification of potential hazards, and how to comprehensively, deeply, and accurately identify such hazards has become a major difficulty in landslide disaster management. Existing deep learning methods for potential landslide hazard identification often use fixed-size window modeling and ignore the different window sizes required by landslides of different scales. To address this problem, we propose an adaptive identification method for potential landslide hazards based on multisource data. Taking Yongping County, China, as the study area, we create a multisource factor dataset based on the landslide disaster background in terms of topography, geology, human activities, hydrology, and vegetation as the sample for the identification model after processing. Moreover, we combine differential interferometric synthetic aperture radar (D-InSAR) and multitemporal InSAR (MT-InSAR) to process the surface deformation of the study area, and we measure the deformation richness based on the average of the pixel deformation difference within the current window of a pixel point in the image. Therefore, convolutional neural networks (CNNs) with different window sizes are adaptively selected. The results show that the precision of adaptive identification of potential landslide hazards in the study area is 85.30%, the recall is 83.03%, and the F1 score is 84.15%. The recognition rate for potential hazards reaches 80%, which is better than the fixed-window modeling result and proves the effectiveness of the proposed method. This method can help to improve intelligent identification systems for potential landslide hazards, and also contribute to the identification of other potential geological hazards, such as mudslides and collapses.

Gangotri glacier dynamics from multi-sensor SAR and optical data

The present study has analyzed dynamics of Gangotri glacier using multiple remote sensing (RS) datasets and ground based observations. Interferometric Synthetic Aperture Radar (InSAR) data pairs from European Remote Sensing satellite (ERS 1/2) tandem pair for spring of 1996, Sentinel-1 SAR pairs and Japanese’s Advance Land Observation System (ALOS) PALSAR-2 SAR data for Spring of 2015 were used to derive glacier-surface velocity at seasonal time scale using Differential InSAR (DInSAR) techniques. Bi-static TanDEM-X (Experimental) data was used for the 1st time to estimate glacier surface elevation changes for a period of 22, 44, 88 days during summer of 2012 using InSAR techniques in this study. Annual glacier velocity was also estimated using temporal panchromatic data of LANDSAT-5 (30 m), LANDSAT-7/8 (15 m), Sentinel-2 (10 m) and Indian Remote Sensing Satellite IRS-1C/1D panchromatic (5 m) data during 1998–2019 with feature tracking approach. This study has estimated glacier surface velocity and surface elevation changes for the major parts of Gangotri glacier and its tributary glaciers using medium to high resolution optical and SAR datasets, at annual and seasonal time scale, which is an improvement over earlier studies, wherein snout based glacier recession or only main glacier velocities were reported. The velocity and slope were used to assess glacier-ice thickness distribution using Glabtop-2, slope dependent and laminar flow based methods over the Gangotri group of glaciers. The estimated ice thickness was estimated in the range of 58–550 m for the complete glacier while few small areas in middle & upper regions carry higher thickness of about 607 m. The estimated glacier-ice thickness was found in the range of 58–67 m at the snout region. The estimation was validated using 2014 field measurements from Terrestrial Laser Scanner (TLS) for the first time and correlation was found to be 0.799 at snout of the glacier.

A Geo-Hazard Risk Assessment Technique for Analyzing Impacts of Surface Subsidence within Onyeama Mine, South East Nigeria

This paper proposes a geo-hazard risk assessment technique to analyze the impacts of surface subsidence monitored in a major coal mine in Nigeria. In many developing countries, disaster risk management schemes have mainly focused on traditional singular hazard assessment, vulnerability assessment, or risk assessment. However, it is difficult to use a singular application to adequately address hazard assessment due to the variation in data requirements, factors associated with the hazards, and the various elements at risk. Most times, hazard assessment schemes heavily rely on data and techniques from different global organizations that collate data on disasters, using various scales and objectives to make informed decisions. Several challenges seemingly arise from total reliance on these kinds of data due to standardization, the exact number of potential victims, and the purpose of the data collection. This makes disaster information collected at the local level unique and assessment schemes more complete; however, the coverage is limited worldwide. The proposed approach combines the spatial relationship between vulnerability assessment and elements at risk to highlight the grave consequences of potential disasters. Thus, the aim is to underscore the importance of integrating local-level inputs in analyzing risk factors and vulnerability indicators for hazard assessment. This study was conducted at the Onyeama coal mine in South East Nigeria. This area has experienced severe negative impacts of subsidence over the years. We exploit data from Sentinel-1 Synthetic Aperture Radar (SAR) Satellites and Small-Baseline Subset Differential Interferometric Synthetic Aperture Radar (SBAS-DInSAR) technique to map the study area. The results generate an elements-at-risk database with a particular focus on population density, road networks, and building networks identified as indices for loss estimation.