Ground Movement Detection Research Articles

Utilization of the Accelerometer Sensor in Android Smartphones Development of Ground Movement Detection Tools in Areas Landslide Prone Based on the Internet of Things

The result of this research is an Internet of Things (IoT) program that utilizes the accelerometer sensor on Android smartphones as a tool for detecting ground movement in landslide-prone areas. If the sensor indicates a change in its coordinates, it will be used as an indication of ground movement on the accelerometer sensor. Meanwhile, the gyroscope sensor detects vibrations, and the program will send notifications as a sign of ground movement. Overall, the development of this landslide movement detection device in landslide-prone areas employs the Research and Development (R&D) methodology. The Research and Development method aims to produce specific products and test the effectiveness of these products. The development method for the ground movement system utilizes a prototype method to observe and comprehend how the application functions. The results of this research demonstrate that the accelerometer sensor on Android smartphones can produce sufficiently accurate data for detecting ground movement. Integration with IoT technology opens opportunities for developing an early warning system that is effective and responsive to the potential landslide disasters. It is hoped that this research can provide a significant contribution to the development of more advanced ground movement detection systems in the future.

Regional Ground Movement Detection by Analysis and Modeling PSI Observations

Any changes to the Earth’s surface should be monitored in order to maintain and update the spatial reference system. To establish a global model of ground movements for a large area, it is important to have consistent and reliable measurements. However, in dealing with mass data, outliers may occur and robust analysis of data is indispensable. In particular, this paper will analyse Synthetic Aperture Radar (SAR) data for detecting the regional ground movements (RGM) in the area of Hanover, Germany. The relevant data sets have been provided by the Federal Institute for Geo-sciences and Natural Resources (BGR) for the period of 2014 to 2018. In this paper, we propose a data adoptive outlier detection algorithm to preprocess the observations. The algorithm is tested with different reference data sets and as a binary classifier performs with 0.99 accuracy and obtains a 0.95 F1-score in detecting the outliers. The RGMs that are observed as height velocities are mathematically modeled as a surface based on a hierarchical B-splines (HB-splines) method. For the approximated surface, a 95% confidence interval is estimated based on a bootstrapping approach. In the end, the user is enabled to predict RGM at any point and is provided with a measure of quality for the prediction.

Internet of Things Geosensor Network for Cost-Effective Landslide Early Warning Systems.

Worldwide, cities with mountainous areas struggle with an increasing landslide risk as a consequence of global warming and population growth, especially in low-income informal settlements. Landslide Early Warning Systems (LEWS) are an effective measure to quickly reduce these risks until long-term risk mitigation measures can be realized. To date however, LEWS have only rarely been implemented in informal settlements due to their high costs and complex operation. Based on modern Internet of Things (IoT) technologies such as micro-electro-mechanical systems (MEMS) sensors and the LoRa (Long Range) communication protocol, the Inform@Risk research project is developing a cost-effective geosensor network specifically designed for use in a LEWS for informal settlements. It is currently being implemented in an informal settlement in the outskirts of Medellin, Colombia for the first time. The system, whose hardware and firmware is open source and can be replicated freely, consists of versatile LoRa sensor nodes which have a set of MEMS sensors (e.g., tilt sensor) on board and can be connected to various different sensors including a newly developed low cost subsurface sensor probe for the detection of ground movements and groundwater level measurements. Complemented with further innovative measurement systems such as the Continuous Shear Monitor (CSM) and a flexible data management and analysis system, the newly developed LEWS offers a good benefit-cost ratio and in the future can hopefully find application in other parts of the world.

Assuring Integrity of CO2 Storage Sites Through Ground Surface Monitoring (SENSE)

Monitoring of geological CO2 storage is crucial for large-scale injection to gain public acceptance. Monitoring plans for large-scale operations need to include both the injection and post-injection phases to assure CO2 is safely stored permanently. The SENSE project aims to develop reliable, continuous, and cost-efficient monitoring based on ground movement detection combined with geomechanical modeling and inversion, utilizing new technology developments, data processing optimization, and interpretation algorithms. The proposed research activities include: • demonstration of continuous monitoring of surface deformation and subsurface pressure distribution using satellite data, water pressure sensors and fiber optics; • quantitative characterization of critical geomechanical and hydraulic parameters and automatization routine for data processing and interpretation; • optimization of sampling arrays in order to offer storage site operators a cost-effective monitoring option as part of an effective site assurance program. The SENSE project brings together experts from 14 international institutions of nine different countries to solve challenges in CO2 storage site monitoring and to provide solutions for safe and successful injection and post-closure phases of site operation. The project is organized in five Work Packages (WPs); WP1: Quantification of ground movement, WP2: Geomechanical modeling and rock strain assessment, WP3: History matching inversion and coupled flow-mechanics, WP4: Integration of results for cost-effective monitoring and WP5: Project management. The ultimate goal of SENSE is to offer storage site operators a cost-effective monitoring option that can form part of an effective site assurance/monitoring program and feed into workflows for an early alert system to detect unexpected changes in the subsurface. The SENSE project has four demonstration sites for monitoring technologies and developing concepts and procedures. These sites are both onshore and offshore. The onshore sites include In Salah (Algeria) and Hotfield Moors (UK). For these sites, the project will use satellite data to explore the response of the surface to pressure changes in the subsurface. Algorithms for automatic satellite data processing to facilitate quick access to ground elevation data for site operators are under development at the British Geological Survey (BGS) and Norwegian Geotechnical Institute (NGI). The offshore sites include Bay of Mecklenburg (Germany) and the Gulf of Mexico (USA). In addition, the SENSE partners have requested access to data from the Troll Gas Field, the North Sea, to study its subsidence due to production-related pressure reduction. The Troll Gas Field is located next to the storage site considered for the Norwegian Long Ship project, and its data will provide a good understanding of the geomechanics of the area. In this paper, we present the work on the In Salah and the Bay of Mecklenburg sites. New InSAR data from the In Salah are used to evaluate the ground movement during the post-injection period and thus to assess the behaviour of the storage site after completion of the injection phase. Bay of Mecklenburg is an offshore site for field experiment to inject a gas underground, build-up pressure, uplift the seafloor and measure the resulted uplift. The first field campaign at the Bay of Mecklenburg was completed in late 2019. It provided both gravity cores from the seabed and geophysical data acquisition for characterizing the shallow subsurface layers. The gravity cores were characterized for physical and mechanical properties. The material properties were used for simulating injection and response of the seafloor to induced pressure. Geomechanical 2D and 3D simulations show that the reservoir may sustain very low overpressure before it fails. Hence, this magnitude of overpressure may create a seafloor uplift of about a few millimeters to a couple of centimeters. The monitoring techniques are therefore being designed to capture uplift in this order of magnitude during the injection operation.

VARIATIONS OF SEA LEVEL AND SEA SURFACE TEMPERATURE IN THE CALDERA OF SANTORINI ISLAND , SOUTHERN AEGEAN SEA

Analyses of sea level records within the Caldera of Santorini Island revealed the significance of both océanographie and atmospheric forcing on the observed signals. Sea level (msl) and sea surface temperature (sst) data were obtained from the four stations of the REMOS monitoring network. Out of the four stations Gialos station is located on the caldera whereas the remaining three (Erinia, Taxiarhis and Agios Nikolaos) are located on the young volcanic islands of Palaia and Nea Kameni. The record of sea level data contained a number of gaps. When possible, (i.e. small gaps) missing values were estimated with linear interpolation. Harmonic analysis on continuous parts of the record revealed a mixed type of tide with similar Nf values for the four stations, a result of their locations being close to each other. No co-oscillation phenomena were found within the caldera. Sea level at Taxiarhis station is affected more by atmospheric forcing and shallow water effects in contrast with Gialos station where mean sea level displays significant correlation (r=0.62) with sea surface temperature at lags 2-6 days. The annual cycle of mean sea level (amplitude=5.74cm) responds to seasonal variations in the thermal structure of the waters, and together with the semiannual cycle explains 9.02% of the variance in the annual frequency band. Existing data are not sufficiently long to develop a model, which will reconstruct sea level variability resulting from océanographie and meteorological forcing and will be used for the detection of ground movements from future volcanic eruptions.

Satellite Remote Sensing in Seismology. A Review

A wide range of satellite methods is applied now in seismology. The first applications of satellite data for earthquake exploration were initiated in the ‘70s, when active faults were mapped on satellite images. It was a pure and simple extrapolation of airphoto geological interpretation methods into space. The modern embodiment of this method is alignment analysis. Time series of alignments on the Earth's surface are investigated before and after the earthquake. A further application of satellite data in seismology is related with geophysical methods. Electromagnetic methods have about the same long history of application for seismology. Stable statistical estimations of ionosphere-lithosphere relation were obtained based on satellite ionozonds. The most successful current project "DEMETER" shows impressive results. Satellite thermal infra-red data were applied for earthquake research in the next step. Numerous results have confirmed previous observations of thermal anomalies on the Earth's surface prior to earthquakes. A modern trend is the application of the outgoing long-wave radiation for earthquake research. In ‘80s a new technology—satellite radar interferometry—opened a new page. Spectacular pictures of co-seismic deformations were presented. Current researches are moving in the direction of pre-earthquake deformation detection. GPS technology is also widely used in seismology both for ionosphere sounding and for ground movement detection. Satellite gravimetry has demonstrated its first very impressive results on the example of the catastrophic Indonesian earthquake in 2004. Relatively new applications of remote sensing for seismology as atmospheric sounding, gas observations, and cloud analysis are considered as possible candidates for applications.

Geological Interpretation of PSInSAR Data at Regional Scale.

Results of a PSInSAR™ project carried out by the Regional Agency for Environmental Protection (ARPA) in Piemonte Region (Northern Italy) are presented and discussed. A methodology is proposed for the interpretation of the PSInSAR™ data at the regional scale, easy to use by the public administrations and by civil protection authorities. Potential and limitations of the PSInSAR™ technique for ground movement detection on a regional scale and monitoring are then estimated in relationship with different geological processes and various geological environments.

The Southeastern Sicily GPS network

The area located between Catania and Syracuse (Southeastern Sicily), characterised by the presence of the Simeto-Scordia-Lentini graben, was affected in the past by a strong seismicity as proved by the occurrence of seismic events strong enough to reach the XI degree of the MCS scale. In particular the January 11 th, 1693 (l = XI MCS) earthquake with a magnitude over 7.5 (estimated), caused huge damage and a great loss of human lives. Following the last seismic event which occurred on December 13th, 1990 (Ml = 5.4) which caused heavy damage and many victims in the Catania-Syracuse area, a geodetic Global Positioning System network (GPS) was set up with the aim of monitoring ground movements in one of the Italian areas subjected to high seismic risk, This "pace geodesy technique supplies high precision measurements and represent, a powerful new tool for investigating both regional stress fields and the evolution of local tectonic areas. The GPS network will allow the detection of ground movements with a centimetric accuracy through repeated surveys in time. The results obtained in two surveys carried out il1 1991 al1d 1993, are described in this paper.