Land Deformation Research Articles

Temporal gravimetry, campaign and permanent GNSS, and interferometric radar techniques: A comparative approach to quantifying land deformation rates in coastal Texas.

Land subsidence and local sea-level rise are well-known on-going hazards that negatively impacting coastal regions, exacerbating coastal flooding, threatening infrastructure stability, accelerating erosion, and amplifying the risks of inundation and property damage. This study used four techniques to quantify land deformation rates in the Texas Coastal Bend region and to investigate the controlling factors on two different spatiotemporal scales: (1) local scale, where biweekly temporal gravity and campaign Global Navigation Satellite System (GNSS) measurements were acquired at six locations over 2 years (October 2020-September 2022); and (2) regional scale, where vertical displacement time series were extracted from the Interferometric Synthetic Aperture Radar (InSAR) and 15 permanent GNSS stations over 5 years (January 2017-November 2021). The observed inconsistency between land deformation rates derived from gravity (range: -33.32 ± 149.30 to +338.68 ± 107.93 mm/yr) and campaign GNSS (range: -17.91 ± 14.90 to +5.69 ± 9.93 mm/yr) surveys could be attributed to the short campaign period and the infrequency of data acquisition. The InSAR-derived deformation rates (range: -12.16 ± 0.12 to +11.70 ± 0.00 mm/yr) were consistent with the permanent GNSS-derived rates (range: -14.0 ± 0.6 to +9.0 ± 3.0 mm/yr); both indicated spatiotemporal variability in land deformation rates across the Texas Coastal Bend. A total of 4 coastal towns (-2.3 ± 3.3 mm/yr), 3 cities (-1.4 ± 2.6 mm/yr), 3 inland towns (-3.6 ± 4.2 mm/yr), and 7 industrial plants (-3.8 ± 5.8 mm/yr) were found to have significant land subsidence rates due to sediment compaction, growth faulting, oil/gas extraction, and groundwater extraction. Results of this study emphasize the advantages and limitations of four different techniques in quantifying land deformation rates; can enhance estimates of local sea-level rise; and offer valuable insights to support coastal communities in mitigating the impacts of land subsidence and improving their resilience.

Groundwater level rise and geological structure influences on land deformation dynamics: insights from managed aquifer recharge operations in Beijing, China

Groundwater level rise and geological structure influences on land deformation dynamics: insights from managed aquifer recharge operations in Beijing, China

Investigating compressed SAR technique efficiency for land deformation analysis along Hwanggang dam

Abstract Monitoring and determining the land deformation in dam reservoirs is very crucial as it is one of the main factors of dam failure around the world. Hwanggang Dam is located at a strategic location near the inter-Korean border. North Korea frequently released water from the Hwanggang Dam, which often triggers floods and landslides in areas near the inter-Korea border in South Korea. Consistent monitoring of the Hwanggang Dam is very crucial to avoid catastrophic loss of infrastructure and life. This research paper exploits the potential of the Compressed SAR (ComSAR) technique for deformation analysis along Hwanggang Dam. A total of 171 Sentinel-1 images of Hwanggang Dam were downloaded from Alaska Satellite Facility in ascending track acquired between 2016 and 2023 to generate a time-series interferogram stack. The generated interferogram stack was exploited by using the ComSAR technique to estimate deformation along Hwanggang Dam. The resultant estimated deformation shows instability along the Hwanggang Dam embarkment.

Zircon Xenocrysts From Easter Island (Rapa Nui) Reveal Hotspot Activity Since the Middle Jurassic

AbstractWe report the finding of mantle‐derived zircon grains retrieved from red soils, regoliths, and beach sands from Easter Island, that are much older than the island volcanism (0–2.5 Ma) and its underlying lithosphere (Pliocene, 3–4.8 Ma). A large population of 0–165 Ma old zircons have coherent oxygen (δ18O 3.8–5.9‰) and hafnium (εHf(t)+3.5–+12.5) mantle isotopic signatures. These results are consistent with the crystallization of zircon from plume‐related melts. In addition, a chemically diverse population with ages from the Paleozoic to the Archean was found. These older populations are enigmatic but they could represent remnants of ancient subducted sediments. Meanwhile, the ∼0–165 Ma population is interpreted as plume‐derived, suggesting that the hotspot started at least ∼165 Ma ago. A spike of ∼164–160 Ma zircons could represent a Large Igneous Province (LIP) stage upon the first arrival of the plume. We use plate reconstructions to show that such a LIP would have formed on the Phoenix Plate and would have subducted below the Antarctic Peninsula around 100–105 Ma. There, LIP subduction would offer a solution for the enigmatic Palmer Land deformation event, previously proposed to result from a collision with an unknown indenter. The here‐reported “ghost” of a prolonged hotspot activity suggests that fragments of the Easter plume and of the ambient sub‐lithospheric mantle stored and re‐sampled zircon xenocrysts due to convective (re)circulation at the scale of the plume head. Our study demonstrates how zircon geochronology and geochemistry provide novel insights into global‐scale geodynamics, offering new perspectives on the dynamics of mantle plumes and hotspot activity.

Using multiple, dynamically linked representations to develop representational competency and conceptual understanding of the earthquake cycle

Using computational methods to produce and interpret multiple scientific representations is now a common practice in many science disciplines. Research has shown students have difficulty in moving across, connecting, and sensemaking from multiple representations. There is a need to develop task-specific representational competencies for students to reason and conduct scientific investigations using multiple representations. In this study, we focus on three representational competencies: 1) linking between representations, 2) disciplinary sensemaking from multiple representations, and 3) conceptualizing domain-relevant content derived from multiple representations. We developed a block code-based computational modeling environment with three different representations and embedded it within an online activity for students to carry out investigations around the earthquake cycle. The three representations include a procedural representation of block codes, a geometric representation of land deformation build-up, and a graphical representation of deformation build-up over time. We examined the extent of students' representational competencies and which competencies are most correlated with students’ future performance in a computationally supported geoscience investigation. Results indicate that a majority of the 431 students showed at least some form of representational competence. However, a relatively small number of students showed sophisticated levels of linking, sensemaking, and conceptualizing from the representations. Five of seven representational competencies, the most prominent being code sensemaking (η2 = 0.053, p < 0.001), were significantly correlated to student performance on a summative geoscience investigation.

Non-linear ground deformation detection and monitoring using time series InSAR along the coastal urban areas of Pakistan.

Conventional geodetic methods rely on point measurements, which have drawbacks for detecting and tracking geologic disasters at specific locations. In this study, the time series Interferometric Synthetic Aperture Radar (InSAR) approach was incorporated to estimate non-linear surface deformation caused by tectonic, shoreline reclamation, and other anthropogenic activities in economically important urban regions of Pakistan's southern coast, which possesses around 270km. The shoreline is extended from the low-populated area on the premises of the Hub River in the west to the highly populated Karachi City and Eastern Industrial Zone, where we collected the Sentinel-1A C-band data from 2017 to 2023 to address urban security and threats to human life and property. The main advantage of opting for the non-linear persistent scatterer interferometric SAR (PSInSAR) approach for this study is that it exposes minute movements without any prior consideration of conventional monitoring techniques, making it valid in continuously varying regions. An average vertical displacement range of - 170 to + 82mm per year was found, which was used to investigate the potential correlation with the most effective causative parameters of deformation. The densely populated areas of the study area experience an annual subsidence of 170mm, and the less populated western region experiences an uplift of 82mm annually. Land deformation varies along the coast of the study area, where the eastern region is highly reclaimed and is affected by erosion. Groundwater table-depleting regions experienced high levels of land subsidence, and tectonic activities controlled vertical displacement in the region. Major variation was detected after an earthquake occurred along fault lines. This study was designed because a non-linear approach is required to address ground movement activities acutely, and it will make it possible to plan surface infrastructure and handle issues brought on by subsidence more effectively.

Mapping of Land Surface Deformation Using Ps-Insar for Disaster Risk Management in the Future

DKI Jakarta is experiencing land subsidence due to overexploitation of its use and the increasing population. It is feared that this decline or deformation will occur in the location of the new national capital. The research objective is "Mapping of Land Surface Deformation using PS-InSAR for Disaster Risk Management in the Future." Quantitative and qualitative research and data collection methods use secondary and primary data. Secondary data in the form of Permanent Scatterers Interferometry Synthetic Aperture Radar (PS-InSAR) Sentinel-1A images to determine soil deformation. Primary data uses a questionnaire to assess disaster risk management. Data analysis uses spatial and statistical analysis. Spatial analysis for land deformation mapping and statistical analysis for risk management. The results showed that the pattern of land deformation before the determination of the location of the capital city of Indonesia was random. On the other hand, after decision-making, it appears to be more systematic and homogeneous in adjacent areas with a decreasing range of about 5 cm per year. Other findings show that disaster risk management carried out by several agencies, especially the problem of land deformation in East Kalimantan, is still far from expectations and very minimal. The findings can be used for future disaster risk management to minimize negative impacts and reduce disaster risk.Keywords: PS-INSAR; Land Deformation; Capital City; Disaster Risk Management

Analysis of Land Deformation using Small Baseline Subset (SBAS) INSAR Technique in Pokhara, Nepal

Pokhara Valley lies in the geographic region rich in karst and the increase in urbanization with natural processes like sinkholes has led to the deformation of land causing socio-economic and physical effects on the people and the geography. Likewise, minimal research using the InSAR approach has been done in the context of the Pokhara Valley. So, this study focuses on the determination of land deformation in Pokhara Metropolitan from 2017 to 2022 using the SBAS technique. Sentinel 1A SLC images were adopted using ascending data acquisition mode. The result shows a cumulative displacement of 1578.97 mm to -1052.65 mm in ascending mode. For validation, SBAS-generated data points of the WRC regions were validated with GNSS value. The Pearson R value was found significant at a 5% significance level and the RMSD value was between 0.8 to 1.73. Thus, the results and the validation process indicate the suitability of SBAS for the determination of land displacement using SBAS.

Analyzing Joshimath’s sinking: causes, consequences, and future prospects with remote sensing techniques

The Himalayas are highly susceptible to various natural disasters, such as the tectonically induced land deformation, earthquakes, landslides, and extreme climatic events. Recently, the Joshimath town witnessed a significantly large land subsidence activity. The phenomenon resulted in the development of large cracks in roads and in over 868 civil structures, posing a significant risk to inhabitants and infrastructure of the area. This study uses a time-series synthetic aperture radar (SAR) interferometry-based PSInSAR approach to monitor land deformation utilizing multi-temporal Sentinel-1 datasets. The line of sight (LOS) land deformation velocity for the Joshimath region, calculated for the year 2022–2023 using a PSInSAR-based approach, varies from − 89.326 to + 94.46 mm/year. The + ve sign indicates the LOS velocity/displacement away from the SAR sensor, whereas − ve sign signifies the earth's movement towards the SAR sensor in the direction of LOS. In addition, the study investigates feature tracking land displacement analysis using multi-temporal high-resolution Planet datasets. The result of this analysis is consistent with the PSInSAR results. The study also estimated the land deformation for the periods 2016–2017, 2018–2019, and 2020–2021 separately. Our results show that the Joshimath region experienced the highest land deformation during the year 2022–2023. During this period, the maximum land subsidence was observed in the north-western part of the town. The maximum LOS land deformation velocity + 60.45 mm/year to + 94.46 mm/year (2022–2023), occurred around Singhdwar, whereas the north and central region of the Joshimath town experienced moderate to high subsidence of the order of + 10.45 mm/year to + 60.45 mm/year (2022–2023), whereas the south-west part experienced an expansion of the order of 84.65 mm/year to − 13.13 mm/year (2022–2023). Towards the south-east, the town experienced rapid land subsidence, − 13.13 mm/year to − 5 mm/year (2022–2023). The study analyzes the causative factors of the observed land deformation in the region. Furthermore, this work assesses the ground conditions of the Joshimath region using UAV datasets acquired in the most critically affected areas such as Singhdhaar, Hotel Mountain View, Malhari Hotel, and Manoharbagh. Finally, the study provides recommendations and future prospects for the development policies that need to be adopted in the critical Himalayan regions susceptible to land deformation. The study suggests that land deformation in the region is primarily attributed to uncontrolled anthropogenic activities, infrastructural development, along with inadequate drainage systems.

Estimation of Land Deformation and Groundwater Storage Dynamics in Shijiazhuang–Baoding–Cangzhou–Hengshui Using Multi-Temporal Interferometric Synthetic Aperture Radar

Groundwater resources are crucial to socio-economic development and the ecosystem, and over-extraction can cause the groundwater level to drop, deplete reserves, and trigger geological hazards like land subsidence. The North China Plain (NCP) has experienced both subsidence and groundwater depletion due to over-extraction in the past 70 years. In this study, we used MT-InSAR technology and ascending C-band Sentinel-1 SAR data from 2017 to 2023 to study land deformation in the junction area of Shijiazhuang–Baoding–Cangzhou–Hengshui. We identified multiple subsidence funnels with a maximum rate exceeding −150 mm/year and a total deformation surpassing 600 mm. Seasonal decomposition methods accurately separated seasonal signals in the time-series deformation and groundwater level data. An exponential function model applied to long-term deformation showed no significant decrease in subsidence in severely affected areas. By modeling seasonal deformation and seasonal groundwater levels, we determined the elastic skeletal storage coefficients (Ske) to be in the range of 1.02 × 10−3~6.53 × 10−3 in subsidence areas. We obtained the spatiotemporal evolution of the total groundwater storage (TGWS), irreversible ground storage (IGWS), and recoverable ground storage (RGWS). The TGWS and IGWS decreased annually while the RGWS increased, which is attributable to the implementation of the South-to-North Water Diversion Project (SNWDP) and the issuance of groundwater withdrawal policies in the NCP.

Land deformation due to earthquake in Cianjur, West Java, Indonesia: A multisensor-multitemporal study

Background The Java Island is located in a seismically active region, which makes it vulnerable to earthquakes. On 21 November 2022, an earthquake of magnitude 5.6 struck Java, with its epicentre located in Cianjur, West Java. The earthquake caused significant damage to the buildings and infrastructure in the region, and several injuries and fatalities. Methods In this study, we used multisensor and multitemporal data to investigate the land deformation. Multi-pairs of Sentinel-1 SAR and aerial orthomosaic photos are used. Sentinel-1 SAR data were acquired from the Copernicus Data Space Ecosystem and the SNAP software was used to do inSAR analysis, while aerial orthomosaic data were acquired using DJI Drone Mavic Pro. Results Our results show that the earthquake caused significant land deformation in the area, with surface displacements of up to 9.8 cm and 11 cm for land uplift and land subsidence, respectively. We also found that deformation was primarily concentrated in the south-eastern and north-western parts of the study area. We identified the possibility of an unmapped fault that could trigger earthquakes in the future. Conclusions Our findings highlight the usefulness of radar and remotely sensed optical data in studying the effects of earthquakes. This data can be used to effectively design future disaster response and recovery efforts.

Submarine landslides and tsunami genesis in Sagami Bay, Japan, caused by the 1923 Great Kanto earthquake

The 1923 Great Kanto earthquake occurred on September 1, in Japan, and caused severe damage mainly in the Kanto region. Tsunamis were observed over wide regions from the east coast of the Izu Peninsula to the west coast of the Boso Peninsula, and particularly, the damage in Atami was devastating. Many earthquake fault models including those of Kanamori (1971) and Ando (1971) were proposed based on the records of land deformation. However, such fault models cannot sufficiently explain the tsunami elevation and its initial sea-level motion on the coasts. Hence, the detailed mechanisms remain elusive. This study examines the possibility that a leading mechanism of the tsunami in the 1923 Great Kanto earthquake was a large-scale submarine landslide that occurred at Sagami Bay and at the mouth of Tokyo Bay based on the records of depth data measured by the Imperial Japanese Navy (1924) before and after the earthquake. We first show that the tsunami calculated by each fault model was inconsistent with the waveform at Yokosuka, the coastal tsunami elevations, and initial sea-level motion. Then, based on statistical analysis of the depth changes at the 1923 Great Kanto earthquake, we found that the seafloor bathymetric changes represented large-scale submarine landslides that may correspond to long-runout submarine liquefied sediment flows. The seafloor gradient over a 40 km flow-out distance was equal to or less than 0.4∘\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^\\circ$$\\end{document}. Through the identification of the submarine landslide source by tsunami backpropagation analysis and utilizing an analytical solution of a high-density gravity flow and a sensitivity analysis, we conducted a range of numerical simulations of the 1923 Great Kanto earthquake tsunamis using a fault model and a submarine landslide tsunami source model due to a high-density liquefied gravity flow. The results quantitatively accounted for the discrepancy between the observed tsunami records with maximum tsunami elevations over 12 m and the fault-model–based simulations with maximum tsunami elevations of 2 to 5 m and explained consistently the maximum tsunami elevation distributions as well as the time-series tsunami waveforms. These results may thus facilitate and deepen our understanding of the earthquake-induced submarine landslide tsunami risk as cascading multi-geohazards.

Sea Level Rise, Land Subsidence, and Flood Disaster Vulnerability Assessment: A Case Study in Medan City, Indonesia

Global sea level rise (SLR) has emerged as a pressing concern because of its impacts, especially increased vulnerability of coastal urban areas flooding. This study addresses the pressing concern of SLR and flood vulnerability in the East Coast of North Sumatra (ECNS) and Medan City. We employ a data-driven approach integrating multicriteria analysis, analytical hierarchy process (AHP)-based weighting, and spatial modeling within a geographic information system framework. The analysis considers crucial factors such as slope, land use, soil type, SLR, and land deformation. The study expands the existing framework by incorporating SLR and land subsidence, acknowledging their significant roles in exacerbating flood vulnerability. Future flood-intensity scenarios are simulated based on SLR projections. Data for spatial analysis primarily originated from multisensor satellite imagery, secondary sources from published literature, and field surveys. We validated the consistency of the variable weightings assigned for vulnerability analysis using a consistency ratio threshold (&lt;0.1). Finally, the established flood vulnerability model was validated by comparing its predictions with recorded flood events in the ECNS and Medan City. The ECNS and Medan City areas were classified as very high and highly vulnerable to flooding, respectively.

Integrating SBAS-InSAR and Random Forest for Identifying and Controlling Land Subsidence and Uplift in a Multi-Layered Porous System of North China Plain

Controlling groundwater table decline could mitigate land subsidence and induced environmental hazards in over-explored areas. Nevertheless, this becomes a challenge in the multi-layered porous system as (in)elastic deformation simultaneously occurs due to vast spatiotemporal variability in the groundwater table. In this study, SBAS-InSAR was used to estimate annual land deformation during 2017–2022 in a specific region of North China Plain, in which aquifers are composed of many layers of fine-grained compressible sediments and the groundwater table has experienced a prolonged decline. The random forest (RF) was applied to establish the nonlinear relationship between accumulated deformation and its potential driving factors, including the depth to the groundwater table (GWD) and its change rate, and the compressible sediment thickness. Results show that the marked subsidence and uplift co-exist in the region even though the groundwater table has risen widely since the South–North Water Diversion Project. The land subsidence is attributed to inelastic compaction of the thick compressible deposits in depression cone centers, where the GWD is over 40 m and 90 m in the shallow and deep aquifers, respectively. In contrast, the marked uplift is primarily attributed to fast rising of the groundwater table (e.g., −2.44 m/a). The RF predictions suggest that, to control the subsidence, the GWD should be less than 20 and 70 m in the shallow and deep aquifers, respectively, and the rising rate of the GWD should increase to 2–5 times of current rates in the depression cones. To mitigate the marked uplift, the rising rate of the GWD should reduce to 1/2–1/5 of the current rates in the shallow aquifers. The uneven deformations of sediments in the depression cone centers and uplift in their boundaries may exacerbate geohazards. Therefore, it is vital to implement appropriate governance of groundwater recovery in the multi-layered porous system.

Spatial-Temporal Dynamic Evolution of Land Deformation Driven by Hydrological Signals around Chaohu Lake.

The frequent occurrence of extreme climate events has a significant impact on people's lives. Heavy rainfall can lead to an increase of regional Terrestrial Water Storage (TWS), which will cause land subsidence due to the influence of hydrological load. At present, regional TWS is mostly obtained from Gravity Recovery and Climate Experiment (GRACE) data, but the method has limitations for small areas. This paper used water level and flow data as hydrological signals to study the land subsidence caused by heavy rainfall in the Chaohu Lake area of East China (June 2016-August 2016). Pearson's correlation coefficient was used to study the interconnection between water resource changes and Global Navigation Satellites System (GNSS) vertical displacement. Meanwhile, to address the reliability of the research results, combined with the Coefficient of determination method, the research findings were validated by using different institutional models. The results showed that: (1) During heavy rainfall, the vertical displacement caused by atmospheric load was larger than non-tidal oceanic load, and the influence trends of the two were opposite. (2) The rapidly increasing hydrologic load in the Chaohu Lake area resulted in greater subsidence displacement at the closer CORS station (CHCH station) than the more distant CORS station (LALA station). The Pearson correlation coefficients between the vertical displacement and water level were as high as -0.80 and -0.64, respectively. The phenomenon confirmed the elastic deformation principle of disc load. (3) Although there was a systematic bias between the different environmental load deformation models, the deformation trends were generally consistent with the GNSS monitoring results. The average Coefficients of determination between the different models and the GNSS results were 0.63 and 0.77, respectively. The results demonstrated the effectiveness of GNSS in monitoring short-term hydrological load. This study reveals the spatial-temporal evolution of land deformation during heavy rainfall around Chaohu Lake, which is of reference significance for water resource management and infrastructure maintenance in this area.

Safeguarding Our Heritage—The TRIQUETRA Project Approach

Cultural heritage (CH) sites are frequently exposed to natural elements, and their exposure becomes particularly precarious with the onset of climate change. This increased vulnerability places these sites at risk of deterioration or complete destruction. Risks such as land deformation, floods, acid rain, and erosion significantly threaten historic monuments, while water-related hazards, significantly influenced by both climate change and human activities, present a particularly grave risk to these invaluable sites. Considerable research efforts have focused on safeguarding CH sites. However, there remains a deficiency in systemic approaches towards identifying and mitigating risks for CH sites. The TRIQUETRA project proposes a technological toolbox and a methodological framework for tackling climate change risks and natural hazards threatening CH in the most efficient way possible. It aims at creating an evidence-based assessment platform allowing precise risk stratification as well as a database of available mitigation measures and strategies, acting as a Decision Support System (DSS) towards efficient risk mitigation and site remediation. TRIQUETRA is a European project that brings together a diverse group of researchers with varied expertise, encompassing university research groups, research institutes, public entities, as well as small and medium-sized enterprises. In this article, TRIQUETRAs overall methodology is presented, and preliminary results concerning risk identification, TRIQUETRAs knowledge base, as well as novel sensors and coatings, are discussed.

Advancements in geodesy techniques for Arctic region monitoring

The Arctic region is undergoing unprecedented environmental changes due to global climate change, necessitating robust monitoring and research efforts. Geodesy, the science of accurately measuring Earth's shape, orientation, and gravitational field, plays a critical role in understanding these changes. This article explores the applications, challenges, and future directions of geodesy in the Arctic. Satellite-based techniques such as GNSS, SAR, and satellite altimetry are utilized to monitor ice mass loss, sea level rise, and land deformation with high precision. Challenges in Arctic geodesy include harsh environmental conditions, data accuracy, and the integration of multi-source data. Despite these challenges, ongoing advancements in satellite technology, data processing algorithms, and collaboration initiatives hold promise for addressing these issues and improving our understanding of Arctic environmental dynamics. By leveraging geodesy techniques and emerging technologies, researchers can contribute to the sustainable management of the Arctic environment and its broader implications for global climate change mitigation and adaptation.

From EGMS Data to a Differential Deformation Map For Buildings at Continent Level

The European Ground Motion Service (EGMS) uses Sentinel-1 data to monitor and measure land displacement on a European scale, providing accurate and consistent data on ground motion phenomena. Since 2022, three types of EGMS products have been made available to all users in a free and open-access manner via the Copernicus platform. As a result, analysis of spatial gradients of displacements is achievable by using reliable and annually updated information on ground motion, particularly in urban areas.The Geomatics research unit of the Center Tecnològic de Telecomunicacions de Catalunya (CTTC) is working on a project with the main purpose of computing the spatial gradient of land deformation and generating a wide-area Differential Deformation map that allows identifying buildings and urban structures that could potentially be vulnerable to damage. The final output of the project will be made available to the public through a web server. The project involves configuring a self-hosted, low-cost web server using open-source tools; developing software pipelines to compute the spatial gradient of deformation and convert deformation data; and setting up a tailored web visor to display the results. Because the project must manage a large volume of data with millions of Measurement Points (MP) and extensive processing times, automation is critical to its success. The obtained information is not only beneficial for monitoring anthropogenic phenomena, but it is also vital for urban management and risk mitigation planning.

DEFORMATION MONITORING AND TIME-SERIES &amp; DISASTER POTENTIALITY ANALYSIS OF GAS PIPELINE USING SENTINEL DATA

Abstract. Synthetic aperture radar interferometry (InSAR) measurement technology is a new remote sensing technology that can effectively monitor slight land deformation. Compared with traditional monitoring technology, InSAR technology has the advantages of wide coverage, all-weather and low cost, providing a technical means of high-resolution, high-precision and low-cost for hidden geological hazard identification and deformation monitoring along pipelines. For purpose of this paper, we performed deformation time-series comprehensive processing and analysis on gas pipeline based on Sentinel-1 image data through small baseline data processing, and extracted pipeline deformation quantities from 2020 to 2022. The land deformation rate of the ascending track data during this period ranges from −43 mm/year to 25 mm/year, and that of the descending track data from −66 mm/year to 33 mm/year. The results show that the area along the gas pipeline is in stable condition on the whole, deformation mainly occurred along a section in the northwest of Haidian District, and a large quantity of deformation occurred since January of 2020 until December of 2021, with the maximum deformation quantity of −70mm, This result provided a reliable reference for safety monitoring and repair &amp;amp; maintenance of the gas pipeline.

Impact assessment of unsustainable airport development in the Himalayas using remote sensing: A case study of Pakyong Airport, Sikkim, India

Ground deformation is a widespread phenomenon that accelerates due to anthropogenic land development. Thus reclaimed/created land is more vulnerable to deformation and subsidence, especially in mountain areas. Advanced Differential Synthetic Aperture Radar Interferometry (A-DInSAR) can be used to monitor such projects. The Pakyong Airport is an engineering feat, constructed by cutting a mountain and converting it into a tabletop in a landslide-prone zone and seismically active region of the Sikkim Himalayas. The cutting of hill slopes for airport construction and other anthropogenic activities has increased slope instability in the region. This paper studies the slow-moving landslides in the airport neighbourhood using A-DInSAR on Sentinel-1 time series data consisting of 64 images of ascending track and 82 images of the descending track. The time period of monitoring was from October 2014 to April 2018 (43 months). The images have been connected using the Minimum Spanning Tree graph for interferogram generation for estimating deformation. The atmospheric noise was removed, and the results enabled the identification of deformation (in line-of-sight) on the airstrip as well as in the neighbouring area, both the upslope and downslope of the airport. The deformation rates estimated were up to ±90 mm/year in Pakyong from both tracks. We could successfully capture such land movement associated with the Pakyong Airport construction and help assess the impacts of infrastructure construction on the slope stability of the area. The controlling factors such as precipitation, seismicity, geology and others were analysed with respect to the deformation obtained. This study helps in assessing the land deformation after construction (cutting and filling of the slope) in the area. The deformation detected in this study needs to be addressed for the safety of the residents as well as for the infrastructure present in the area.