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We present a methodology to use a UAV (unmanned aerial vehicle) to perform photogrammetric surveys and detailed geological mapping in mountain areas. This work is specially related to the presented case study with the aim to realize geomorphological maps from UAVs, since they can house different types of sensors and acquire data more rapidly and cheaply than traditional geological surveys directly obtained with field observations. This work explains how UAVs can obtain digital terrain models, orthophotos and 3D models in order to create slope and aspect maps for geological purposes. By integrating data from UAVs with geological surveys made on the field, geological maps can be produced where many of the geological elements are presented. This paper presents the integration of geomatics and geological techniques. Starting from UAV slope map and orthophotos, a new geological map was created in a faster and more detailed way compared to traditional geological survey on the ground. The application of this method regards a sector of the Western Alps (NW Italy), formed by glaciers and deep-seated gravitational slope deformations.

The sequestration of CO 2 into geological formations as a strategy for reducing atmospheric greenhouse gases requires accurate monitoring of CO 2 plume for safe long-term storage. However, imaging CO 2 plume migration in the subsurface is a challenging problem for existing seismic monitoring methods. Here, we present an approach for CO 2 monitoring based on seismic coda waves and apply it to the 3-d period of CO 2 injection in a pilot experiment. We find that velocity reduction is nonlinearly correlated with the cumulative CO 2 mass inside the reservoir, and that coda waves can effectively monitor the spatiotemporal evolution of CO 2 plumes in the subsurface. Our findings suggest approaches for using seismic data in long-term monitoring of subsurface CO 2 plume evolution. Quantifying the dynamics of sequestered CO 2 plumes is critical for safe long-term storage, providing guidance on plume extent, and detecting stratigraphic seal failure. However, existing seismic monitoring methods based on wave reflection or transmission probe a limited rock volume and their sensitivity decreases as CO 2 saturation increases, decreasing their utility in quantitative plume mass estimation. Here we show that seismic scattering coda waves, acquired during continuous borehole monitoring, are able to illuminate details of the CO 2 plume during a 74-h CO 2 injection experiment at the Frio-II well Dayton, TX. Our study reveals a continuous velocity reduction during the dynamic injection of CO 2 , a result that augments and dramatically improves upon prior analyses based on P-wave arrival times. We show that velocity reduction is nonlinearly correlated with the injected cumulative CO 2 mass and attribute this correlation to the fact that coda waves repeatedly sample the heterogeneous distribution of cumulative CO 2 in the reservoir zone. Lastly, because our approach does not depend on P-wave arrival times or require well-constrained wave reflections it can be used with many source–receiver geometries including those external to the reservoir, which reduces the risk introduced by in-reservoir monitoring wells. Our results provide an approach for quantitative CO 2 monitoring and plume evolution that increases safety and long-term planning for CO 2 injection and storage.

This work presents the development and evaluation of a low-cost and low-power IoT system for monitoring slope instabilities, rockfalls, and landslides using LoRa communication. The prototype integrates commercial ESP32-based hardware with an SX1276 transceiver, a triaxial MEMS accelerometer, and a GPS module for real-time tilt and location measurements. A tilt-estimation expression was derived from accelerometer data, enabling adaptation to different terrain inclinations. Laboratory tests were performed to validate the stability and accuracy of the inclination measurement, followed by outdoor LoRa range tests under mixed line-of-sight conditions. A lightweight dashboard was implemented for real-time visualization of GPS position, signal quality, and tilt data. The results show reliable tilt detection, consistent long-range communication, and low power consumption, highlighting the potential of the proposed prototype as a scalable and energy-efficient tool for geotechnical monitoring.

Surface and underground stretched deformation is one of the most important physical measurement quantities for geological-disaster monitoring. In this study, a parallel helical sensing cable (PHSC) based on the time–domain reflectometry (TDR) technique is proposed and used to monitor large ground stretched deformation. First, the PHSC structure and manufacturing process are introduced, and then, distributed capacitance, distributed inductance, and characteristic impedance were derived based on the proposed stretched-structure model. Next, the relationship between characteristic impedance and stretched deformation was found, and the principle of distributed deformation measurement based on the TDR technique and PHSC characteristic impedance was analyzed in detail. The function of the stretched deformation and characteristic impedance was obtained by curve fitting based on the theoretically calculated results. A laboratory calibration test was carried out by the designed tensile test platform. The results of multi-point positioning and the amount of stretched deformation are presented by the tensile test platform, multi-point positioning measurement absolute errors were less than 0.01 m, and the amount of stretched deformation measurement absolute errors were less than 3 mm, respectively. The measured results are in good agreement with the theoretically calculated results, which verify the correctness of theoretical derivation and show that a PHSC is very suitable for the distributed measurement of the ground stretched deformation.

Quantifying the dynamics of sequestered CO₂ plumes is critical for safe long-term storage, providing guidance on plume extent, and detecting stratigraphic seal failure. However, existing seismic monitoring methods based on wave reflection or transmission probe a limited rock volume and their sensitivity decreases as CO₂ saturation increases, decreasing their utility in quantitative plume mass estimation. Here we show that seismic scattering coda waves, acquired during continuous borehole monitoring, are able to illuminate details of the CO₂ plume during a 74-h CO₂ injection experiment at the Frio-II well Dayton, TX. Our study reveals a continuous velocity reduction during the dynamic injection of CO₂, a result that augments and dramatically improves upon prior analyses based on P-wave arrival times. We show that velocity reduction is nonlinearly correlated with the injected cumulative CO₂ mass and attribute this correlation to the fact that coda waves repeatedly sample the heterogeneous distribution of cumulative CO₂ in the reservoir zone. Lastly, because our approach does not depend on P-wave arrival times or require well-constrained wave reflections it can be used with many source–receiver geometries including those external to the reservoir, which reduces the risk introduced by inreservoir monitoring wells. Our results provide an approach for quantitative CO₂ monitoring and plume evolution that increases safety and long-term planning for CO₂ injection and storage.

The author introduces the technical principles of elastic wave CT method and seismic imaging method, taking the detection results of a dangerous road in southern Shaanxi as a research example. The application effect of comprehensive geophysical methods in solving engineering exploration problems was analyzed and studied, and the two methods were mutually verified, improving the accuracy of interpretation. The results show that the elastic wave CT method and seismic imaging have high recognition and resolution ability in the detection of dangerous roads in goaf collapse areas, and are effective technical methods to solve such geophysical exploration problems.

In this study, we investigated the morphology, chemical composition and pH measurement performance of MoOx electrodes prepared via thermal oxidation and submitted to hydration in milliQ water. Surface analysis using SEM-EDS and XPS revealed that the hydrated MoOx film is composed of different oxidation states of Mo (Mo (IV), Mo (V) and Mo (VI)), influencing its electrochemical behavior. A hydration period of 45 days was required for the electrode to achieve a response approaching the Nernstian model (−58 mV/pH), while extended hydration of up to 70 days enhanced its stability and sensitivity. The electrode’s performance was assessed under various conditions, including in the presence and absence of oxygen and in anaerobic conditions with the presence of sulfides. Oxygen absence increased sensitivity and lowered the experimental standard potential (E0Exp) due to the effect of oxygen vacancies. Low sulfide concentrations had minimal impact on electrode performance, although higher concentrations may slightly decrease the electron transfer efficiency due to the complex formation. The pH sensing mechanisms of MoOx electrodes are also discussed.

The surveying and mapping administrative competent departments in 31 provinces (autonomous regions and municipalities) have built provincial-level satellite navigation and positioning reference stations and data centers, and provided CORS services. This provides a good condition for exploring the application of geological hazard monitoring and early warning using Virtual Reference Station (VRS) service based on CORS. At present, the layout mode of \"one point one reference station\" is usually adopted, when GNSS is used for geological disaster monitoring and early warning. However, the high deployment cost of this plan limits its largescale promotion and application. Using the existing CORS service resources of natural resource system, this paper carried out the application experiment of virtual reference station in geological hazard monitoring application at Huanglongya geological hazard monitoring site in Shaanxi Province, and assessed the virtual reference station data quality, comparative analyzed the precision of static baseline processing results and GNSS real-time deformation monitoring results. The experimental results show that the overall quality of virtual reference station data is better than that of the monitoring station, and the accuracy of the static baseline calculation results is better than 1.0cm in the X direction, and better than 2.0cm in the Y direction and Z direction, which is similar to the static baseline calculation results formed by the physical reference station. The accuracy of the baseline results of real-time observation data calculation is better than 5mm in horizontal RMS and 15mm in vertical RMS. Therefore, it can be seen that the virtual reference station is feasible to be used as the reference station for geological disaster monitoring. In addition, the application experiment of network RTK real-time dynamic single epoch positioning mode is also carried out in geological hazard monitoring. The experimental results show that the RMS values of all three directions are ±3.7mm, ±9.2mm and ±5.0mm respectively, which meet the precision requirements of GNSS disaster monitoring. Therefore, it is also a feasible scheme for geological disaster monitoring and early warning.

Geological disasters, characterized by their destructive nature, pose significant threats to both human life and ecological environments. The advent of remote sensing technology has rendered hyperspectral remote sensing images an integral data source in monitoring and predicting these phenomena. However, it is noted that minor variations and detailed nuances within the images are often overlooked by traditional computer vision and deep learning techniques. Furthermore, data imbalances during the training of deep learning models have been identified as a potential hindrance to optimal performance. Recognizing these issues and the inherent unpredictability of geological disasters, an innovative approach has been developed. This approach encapsulates an optical flow-based method for enhancing the edges of geological remote sensing images, an improved geological disaster monitoring model leveraging the Isolation Forest algorithm, and an efficient implementation strategy. The suggested methods present numerous advantages, including the acceleration of computations to augment real-time monitoring of geological disasters, an enhanced capacity for handling extensive data, an improved system stability and fault tolerance, and the preservation of fundamental strengths such as linear computational complexity, unsupervised learning, and non-parametric methodologies. By synthesizing these methodological improvements and advantages, a swift, efficient, and flexible strategy for enhancing the Isolation Forest model is put forth. This research supports the development of geological disaster monitoring and early warning systems grounded in computer vision and deep learning, presenting substantial technical aid for related tasks.

Geological hazard monitoring is essential to the prevention and control of geological hazards, yet conventional monitoring is often conducted for local geological hazards, and the relation between monitored results and geological hazards remains poorly understood. In this study, a regional load deformation field model was constructed using data from 26 Continuously Operating Reference Stations (CORS) and 8 gravity stations in the Three Gorges area. The relation between load-induced changes and geological hazards, as the regular characteristics (RCS) in this paper, is obtained by comparing the geological hazards with the impact of the total load change in the whole region of the Three Gorges area and the entire process from 2011 to the beginning of 2015. Geological hazards are more prone to occurring when there are one or more RCS, especially abnormal dynamic environment appears at the same time, such as solid high tide and heavy rainfall. The RCS included the ground geodesy height change rate increasing, the ground gravity change rate decreasing, the ground vertical deviation diverging, the ground geodesy height gradient growing larger and the ground gravity gradient growing larger. Using all of the 18 geological hazards from May to July 2013 to verify the RCS, it was found that the comprehensive observations of CORS and gravity stations can effectively monitor the RCS of the load-induced changes. The results of this study provide more insights associated with the geological hazards monitoring and analysis methods as well as effective support for geological hazard forecasting.