Geological Engineering Commons^™

Satellite-Based Detection And Preliminary Flux Estimation Of The 2024 Boysun Methane Blowout Event In Uzbekistan, Shomurod Bakhtiyor Ugli Turaev, Dilbar Shamurodovna Fazilova, Aziz Nigmanovich Kazakov

Technical science and innovation

Estimating accidental methane emissions from gas fields remains a difficult task, especially in remote mountainous areas where continuous ground-based observations are not available. This study examines the uncontrolled gas blowout that occurred in 2024 at the “Mustaqillikning 25-yilligi” gas-condensate field in Boysun district, Uzbekistan. Changes in methane content were analyzed using Sentinel-5P TROPOMI data for August–November 2024, processed in Google Earth Engine (GEE). The location of the accident site was refined using Sentinel-2 optical imagery, while ERA5 wind speed and direction data were applied for the preliminary calculation of methane flux. Based on the XCH₄ time series, four stages of …

A Remote Sensing Approach To Identifying Zones Of Instability In Mine Tailings Impoundments Using Multi-Sensor Satellite Data, Arden K. Pierce

Honors Theses

Mine tailings impoundments are structures built to contain the chemical and sedimentary byproducts generated by ore extraction activities. In this common method of mining waste storage, the tailings can be pumped into containment ponds and held behind earthen embankments to prevent the release of hazardous substances into the surrounding environment. Monitoring environmental factors that influence the structural integrity of these impoundments is essential for identifying areas vulnerable to instability and failure. Soil moisture is a factor that can affect the stability of mine tailings impoundment structures. This study evaluates the relationship between satellite-derived soil moisture and surface deformation at mine …

Remote Sensing Of Dynamic Ground Motion Via A Moiré-Based Apparatus, Adrian Ali Moazzam, Nontawat Srisapan, Gregory Waite, Durdu Guney, Roohollah Askari

Michigan Tech Publications

Highlights: What are the main findings? A Moiré-based optical apparatus enables long-range, non-contact ground displacement measurement in hazardous environments. Controlled indoor and outdoor experiments demonstrate reliable detection of dynamic and seismic-like ground motions with sub-millimeter resolution. What are the implications of the main findings? System performance is evaluated under atmospheric turbulence and wind, revealing key limits and mitigation strategies for field deployment. The proposed approach provides a low-cost, scalable complement to traditional seismic and geodetic monitoring techniques. Ground-based remote sensing of seismic and geophysical displacements remains a major challenge due to environmental hazards, signal attenuation, and practical deployment limitations of …

Improving The Methodology Of Complex Organization Of Rural Areas Based On Gis Technologies, Anvarjon Pardaboyev

Technical science and innovation

In the world, scientific research is being conducted aimed at improving the efficiency of complex organization of rural areas by utilizing modern geographic information systems (GIS) and remote sensing data. These studies focus on shaping the land allocated to these areas, organizing their activities, and forming the basis of cartographic information. Additionally, the use of modern GIS and remote sensing data has become widespread in the complex organization of rural areas in many countries. This method stands out for its effectiveness in organizing regions today.

In our republic, comprehensive measures are being implemented to consistently develop production through structural, institutional, …

Remote Sensing Of Seismic Signals Via Enhanced Moiré-Based Apparatus Integrated With Active Convolved Illumination, Adrian A. Moazzam, Anindya Ghoshroy, Durdu Güney, Roohollah Askari

Michigan Tech Publications

The remote sensing of seismic waves in challenging and hazardous environments, such as active volcanic regions, remains a critical yet unresolved challenge. Conventional methods, including laser Doppler interferometry, InSAR, and stereo vision, are often hindered by atmospheric turbulence or necessitate access to observation sites, significantly limiting their applicability. To overcome these constraints, this study introduces a Moiré-based apparatus augmented with active convolved illumination (ACI). The system leverages the displacement-magnifying properties of Moiré patterns to achieve high precision in detecting subtle ground movements. Additionally, ACI effectively mitigates atmospheric fluctuations, reducing the distortion and alteration of measurement signals caused by these fluctuations. …

Rapid Saline Permafrost Thaw Below A Shallow Thermokarst Lake In Arctic Alaska, Benjamin M. Jones, Mikhail Z. Kanevskiy, Andrew D. Parsekian, Helena Bergstedt, Melissa K. Ward Jones, Rodrigo C. Rangel, Kenneth M Hinkel, Yuri Shur

Michigan Tech Publications

Permafrost warming and degradation is well documented across the Arctic. However, observation- and model-based studies typically consider thaw to occur at 0°C, neglecting the widespread occurrence of saline permafrost in coastal plain regions. In this study, we document rapid saline permafrost thaw below a shallow arctic lake. Over the 15-year period, the lakebed subsided by 0.6 m as ice-rich, saline permafrost thawed. Repeat transient electromagnetic measurements show that near-surface bulk sediment electrical conductivity increased by 198% between 2016 and 2022. Analysis of wintertime Synthetic Aperture Radar satellite imagery indicates a transition from a bedfast to a floating ice lake with …

Terrain Characterization Via Machine Vs. Deep Learning Using Remote Sensing, Jordan Ewing, Thomas Oommen, Jobin Thomas, Anush Kasaragod, Richard Dobson, Colin Brooks, Paramsothy Jayakumar, Michael Cole, Tulga Ersal

Michigan Tech Publications, Part 1

Terrain traversability is critical for developing Go/No-Go maps for ground vehicles, which significantly impact a mission’s success. To predict the mobility of terrain, one must understand the soil characteristics. In-situ measurements performed in the field are the current method of collecting this information, which is time-consuming, costly, and can be lethal for military operations. This paper investigates an alternative approach using thermal, multispectral, and hyperspectral remote sensing from an unmanned aerial vehicle (UAV) platform. Remotely sensed data combined with machine learning (linear, ridge, lasso, partial least squares (PLS), support vector machines (SVM), and k nearest neighbors (KNN)) and deep learning …

Developing A Regional Scale Landslide Early Warning System In A Data-Sparse Region Using Remote Sensing, Geostatistics, And Google Earth Engine, Vishnu Chakrapani Lekha

Dissertations, Master's Theses and Master's Reports

The Landslide Early Warning System (LEWS) is a non-structural approach to mitigate landslide risk by alerting vulnerable communities at an early stage. This study aimed to develop a regional LEWS for rain-induced shallow landslides in Idukki, a mountainous district in India with sparse rainfall data. The landslide model consists of a rainfall component and a slope stability component. Satellite precipitation data can be used in data-sparse regions, but they must be calibrated because they tend to underestimate rainfall. To improve the accuracy of satellite data, this study used a geostatistics-based multi-criteria approach to identify optimal locations to install new rain …

Challenges Of Modeling Rainfall Triggered Landslides In A Data-Sparse Region: A Case Study From The Western Ghats, India, C. L. Vishnu, T. Oommen, Snehamoy Chatterjee, K. S. Sajinkumar

Michigan Tech Publications, Part 1

Accurate rainfall estimates are required to forecast the spatio-temporal distribution of rain-triggered landslides. In this study, a comparison between rain gauge and satellite rainfall data for assessing landslide distribution in a data-sparse region, the mountainous district of Idukki, along the Western Ghats of southwestern India, is carried out. Global Precipitation Mission Integrated Multi-satellitE Retrievals for GPM-Late (GPM IMERG-L) rainfall products were compared with rain gauge measurements, and it was found that the satellite rainfall observations were underpredicting the actual rainfall. A conditional merging algorithm was applied to develop a product that combines the accuracy of rain gauges and the spatial …

Temporal Lidar Scanning In Quantifying Cumulative Rockfall Volume And Hazard Assessment: A Case Study At Southwestern Saudi Arabia, Abdullah A. Alotaibi, Norbert H. Maerz, Kenneth J. Boyko, Ahmed M. Youssef, Biswajeet Pradhan

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Rockfalls and unstable slopes pose a serious threat to people and property along roads/highways in the southwestern mountainous regions of Saudi Arabia. In this study, the application of terrestrial light detection and ranging (LiDAR) technology was applied aiming to propose a strategy to analyze and accurately depict the detection of rockfall changes, calculation of rockfall volume, and evaluate rockfall hazards along the Habs Road, Jazan Region, Saudi Arabia. A series of temporal LiDAR scans were acquired at three selected sites. Our results show that these three sites have different degrees of hazard due to their geological differences. The mean volume …

Development And Application Of A 1d Compaction Model To Understand 65 Years Of Subsidence In The San Joaquin Valley, Matthew Lees, Rosemary Knight, Ryan G. Smith

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

High rates of land subsidence, caused by groundwater overdraft, are resulting in millions of dollars of infrastructure damage in California's San Joaquin Valley (SJV). In recent years, the use of interferometric synthetic aperture radar (InSAR) has enabled us to substantially improve our understanding of this subsidence. However, only very occasionally have the InSAR data been integrated with a physical model of subsurface compaction. Here, we have used InSAR and other data to parameterize and calibrate a 1D compaction model. We applied our model to a study area in the SJV where we had access to the necessary information on hydraulic …

Groundwater Withdrawal Estimation Using Integrated Remote Sensing Products And Machine Learning, Sayantan Majumdar

Doctoral Dissertations

"The rising demands for water, food, and energy primarily driven by the increasing global population constitute a pressing issue worldwide. Therefore, the water-food-energy nexus plays a substantial role in developing globally applicable sustainable solutions. Recent technological advancements, including the earth observation programs using spaceborne remote sensing platforms, have enabled us to monitor various critical components affecting the globe. Groundwater, which comprises the world's 30% freshwater, is one such key component of the global water resources and supplies nearly half of the global drinking water.

Despite groundwater overdraft in many parts of the world, including the United States (US), there are …

Integrating Remote Sensing And Model-Based Datasets In A Machine Learning Model To Map Global Subsidence Associated With Groundwater Withdrawal, Md Fahim Hasan

Masters Theses

"Quantifying groundwater storage loss is becoming increasingly essential globally due limited availability of this major hydrologic component and its long recharge time. Groundwater overdraft gives rises to multiple adverse impacts including land subsidence and permanent groundwater storage loss. In absence of spatially dense monitoring network, publicly available in-situ data, and uniform monitoring strategies, it is challenging to assess the sustained losses from overexploitation of this resource. Remote sensing based techniques have the capacity to fill this gap to increase our groundwater monitoring capacities. Exploring the interrelation between groundwater pumping and land subsidence using remote sensing datasets can be a very …

Characterizing Soil Stiffness Using Thermal Remote Sensing And Machine Learning, Jordan Ewing, T. Oommen, Paramsothy Jayakumar, Russell Alger

Michigan Tech Publications, Part 1

Soil strength characterization is essential for any problem that deals with geomechanics, including terramechanics/terrain mobility. Presently, the primary method of collecting soil strength parameters through in situ measurements but sending a team of people out to a site to collect data this has significant cost implications and accessing the location with the necessary equipment can be difficult. Remote sensing provides an alternate approach to in situ measurements. In this lab study, we compare the use of Apparent Thermal Inertia (ATI) against a GeoGauge for the direct testing of soil stiffness. ATI correlates with stiffness, so it allows one to predict …

Application Of Remote Sensing For Permafrost Monitoring In Alaska, Iuliia V. Tcibulnikova

Dissertations, Master's Theses and Master's Reports

Permafrost covers about 85% of the state of Alaska; it is a fragile cryogenic phenomenon prone to degradation under thermal and mechanical (natural and anthropogenic) influences. This research analyzes the application of remote sensing for permafrost monitoring in the Prudhoe Bay area, Alaska. Thawing thermokarst lakes are assessed as the signs of permafrost degradation. Normalized Difference Water Index (NDWI) was used to detect thaw lakes in Landsat-8 satellite imagery within the 529-km² study area in 2013 and 2020. The lakes were then mapped according to their size and growth rate. Lakes do not grow uniformly; some lakes grow while …

Rain Generated Lahars Prior To The 2018 Catastrophic Eruption Of Fuego Volcano, Guatemala, Claudia Buondonno

Dissertations, Master's Theses and Master's Reports

Fuego volcano is one of the most active and hazardous volcanoes in the world. It is located in the northern part of the Central American Volcanic Arc in Guatemala and its activity can be characterized by long term, low-level background activity, and sporadic larger explosive eruptions. Its historical observations of eruptions date back to 1531, but it has been erupting vigorously since 2002 with major activity throughout 2018, producing three main eruptions in February, June and November. Its almost persistent activity generates major ashfalls, pyroclastic flows, lava flows; when heavy rains mobilize its deposits, they can form damaging lahars. Phenomena, …

Suitability Assessment For Integrated Urban Development In Makkah City Of Saudi Arabia, Mislat Alotaibi

Graduate Theses and Dissertations

Makkah – the third most populated city in Saudi Arabia with a population of 1,684,408 according to the 2010 demographic survey conducted by the Saudi General Authority for Statistics – is experiencing urban sprawl, which can be defined as an unplanned urban expansion that might degrade the environment and diminish the aesthetic view. This is a persisting problem in Makkah driven by multitude of processes involving the random expansion in its undeveloped land and the removal of its historic mountains surrounding Al-Masjid Al-Haram (the Holy Mosque) in an attempt to push the city limit of urban capacity within its administrative …

Evidence Of Instability In Previously-Mapped Landslides As Measured Using Gps, Optical, And Sar Data Between 2007 And 2017: A Case Study In The Portuguese Bend Landslide Complex, California, El Hachemi Y. Bouali, Thomas Oommen, Rüdiger Escobar-Wolf

Michigan Tech Publications, Part 1

Velocity dictates the destructive potential of a landslide. A combination of synthetic aperture radar (SAR), optical, and GPS data were used to maximize spatial and temporal coverage to monitor continuously-moving portions of the Portuguese Bend landslide complex on the Palos Verdes Peninsula in Southern California. Forty SAR images from the COSMO-SkyMed satellite, acquired between 19 July 2012 and 27 September 2014, were processed using Persistent Scatterer Interferometry (PSI). Eight optical images from the WorldView-2 satellite, acquired between 20 February 2011 and 16 February 2016, were processed using the Co-registration of Optically Sensed Images and Correlation (COSI-Corr) technique. Displacement measurements were …

Application Of Remote Sensing And Machine Learning Modeling To Post-Wildfire Debris Flow Risks, Priscilla Addison

Dissertations, Master's Theses and Master's Reports

Historically, post-fire debris flows (DFs) have been mostly more deadly than the fires that preceded them. Fires can transform a location that had no history of DFs to one that is primed for it. Studies have found that the higher the severity of the fire, the higher the probability of DF occurrence. Due to high fatalities associated with these events, several statistical models have been developed for use as emergency decision support tools. These previous models used linear modeling approaches that produced subpar results. Our study therefore investigated the application of nonlinear machine learning modeling as an alternative. Existing models …

Utilizing Vegetation Indices As A Proxy To Characterize The Stability Of A Railway Embankment In A Permafrost Region, Priscilla Addison, Pasi T. Lautala, Thomas Oommen

Michigan Tech Publications, Part 1

Degrading permafrost conditions around the world are posing stability issues for infrastructure constructed on them. Railway lines have exceptionally low tolerances for differential settlements associated with permafrost degradation due to the potential for train derailments. Railway owners with tracks in permafrost regions therefore make it a priority to identify potential settlement locations so that proper maintenance or embankment stabilization measures can be applied to ensure smooth and safe operations. The extensive discontinuous permafrost zone along the Hudson Bay Railway (HBR) in Northern Manitoba, Canada, has been experiencing accelerated deterioration, resulting in differential settlements that necessitate continuous annual maintenance to avoid …