Collection Of Geophysical Data Research Articles

GENERALIZED DATASET OF GEOLOGICAL AND GEOPHYSICAL INFORMATION ON THE EASTERN SECTOR OF THE RUSSIAN ARCTIC FOR MACHINE LEARNING – BASED ANALYSIS

The article presents a practical approach to the geological and geophysical spatial data collection and preliminary processing to use in machine learning models for geophysical applications. According to the established principles for estimating efforts in data analysis, which are confirmed by the results of surveys among specialists, this stage is viewed as major time and resource-consuming, amounting up to 80% in total volume of data analysis for a hypothesis testing project. The paper focuses on creating a consistent data set that integrates geological and geophysical information on a given region. We consider problems of different sources in the geodata representation to be related to their format (vector/raster), scale, type of attribute information (quantitative/qualitative) and their availability. The algorithm formalization and synthesis for combining geospatial data and converting them into quantitative vectors is a critical aspect. Combining various data draws on the concept of neighborhood fitting in with the data selection techniques and data consolidation strategy. The paper presents the general architecture of the software and hardware complex which includes a module for data collection and transformation in Python using the Pandas library, a data storage system based on the PostgreSQL DBMS (Database Management System) with the PostGIS extension. It is shown that for the considered class of problems in geophysics, it is sufficient to use a relational DBMS for data storing and processing. If the problem dimension increases, it is proposed to use the Big Data technology based on Apache Hadoop for scaling the system. A practical application of the proposed approach is demonstrated as results of data collection for the Caucasus region and eastern sector of the Russian Arctic. Based on the prepared data, experiments were carried out using machine learning models for recognition of locations of potential strong earthquakes and for sensitivity estimation of several geophysical features of these regions. The article presents the experimental results and evaluation of their efficiency.

Utilizing Data Mining Techniques in Geophysical and Biological Analysis for Assessing Environmental Risks

This study aimed to assess environmental risks using data extraction techniques. It focused on geophysical and biological factors and addressed the urgent need for effective risk management strategies to reduce soil erosion, water pollution, and air quality deterioration. A comprehensive dataset was created through the systematic collection of geophysical and biological data including temperature, soil composition, and biological abundance index. It used equipment such as satellite sensors and mountain transmitting stations. Various statistical tools used include decision trees and random forest algorithms. They were used to analyze data and identify important environmental risk factors. The results showed some interesting insights, revealing that the Neural Network has an accuracy of 95.5%, and the Random Forest algorithm predicts risk with an accuracy of 92.0%. It analyzed the classification of environmental hazard zones and identified high-risk zones, such as Zone A, which contains 10,000 people affected by erosion and Zone D, 20,000 people who were at risk from soil contamination. The study concludes that social media can significantly improve understanding and management of environmental risks. Additionally, it provides a useful framework for decision-makers and stakeholders to promote sustainable environmental practices.

Theoretical foundations of developing a software-hardware complex for monitoring and managing the geophysical state of regions in Ukraine

This article explores the essence and important aspects of the software and hardware complex for monitoring and managing the geophysical condition of a region. Various structural schemes of the complex are analyzed in the article, including linear sequential, modular, hierarchical, matrix, and integrated. The choice of an optimal scheme determines the efficiency of the monitoring system. Next, the importance of the database structure for effective collection and analysis of geophysical data is discussed. Based on the collected information, a hierarchical structure for monitoring and managing large territories, such as Ukraine, is proposed, providing centralized management, regional subsystems, and local monitoring. Conclusions and recommendations for creating a state program, including the development of a strategic plan, definition of technical requirements, fundraising, and collaboration with partners, are provided. Through these steps, it is possible to create a comprehensive and well-organized system for monitoring and managing the geophysical condition of the region, ensuring the safety, stability, and prosperity of citizens. The presented aspects take into account important requirements and needs for the implementation of similar projects for better management of natural risks and events.

MEASUREMENT AND ENHANCEMENT OF GRAVITY DATA FOR GEOPHYSICAL INVESTIGATIONS IN ABUJA, NIGERIA

The availability of gravity data is useful to individuals, governments and organizations that wish to carry out a geophysical investigation in Abuja. The data provides an accurate model for environmental monitoring and disaster studies. This research was aimed at measurement and prediction of gravity data in Abuja, Nigeria. The aim was achieved by observation of terrestrial gravity data at forty (40) gravity stations around the federal capital territory Abuja, prediction of the gravity data at other points and the evaluation of the predicted data. Gravity reduction was carried out on the measured data to account for drift correction, free air correction, bouguer correction latitude correction and terrain correction. The data was further enhanced by interpolation using the Kriging method. A total of 59 points were predicted from the 40 measured stations. The predicted gravity anomalies were validated by comparing with their corresponding gravity anomalies obtained from the Earth Gravity Model 2008 (EGM08) because of their well-established reliability. For the number of observations, n = 59, the RMSE and SE were computed as 4.797mGal (4.787x10-5 ms-2) and 4.880mGal (4.880 x10-5 ms-2) respectively. Also, the correlation value obtained was 0.991 which is significant at 0.01 level. This shows a strong relationship signifying a perfect possible agreement in the values obtained. It was therefore concluded that Kriging is a good interpolator that provides an estimate with high reliability and dependency. In this regard, considering the high cost of geophysical data collection, gravity prediction can make geophysical data collection more efficient and cost-effective.

Feature-based Bathymetric Matching of Autonomous Underwater Vehicle Transects using Robust Gaussian Processes

Autonomous underwater vehicles have become essential tools for the collection of high-resolution bathymetric and geophysical data. An inertial navigation system, aided by a Doppler velocity log and a surface-mounted ultrashort baseline acoustic positioning system, is generally capable of providing sufficient accuracy at conventional survey scales. However, the accuracy decreases with depth, and the resulting relative positioning across different transects may not be sufficient to resolve features of interest at fine scales. This work presents a method for accurate coregistration of the position of adjacent transects. The approach is based on detecting and matching local features in overlapping multibeam echosounder swaths. The navigational errors for the transects are taken to be described by latent Gaussian processes, observed through these matches. The hyperparameters of the Gaussian process are learned from the data themselves and do neither require tuning of filter parameters nor intimate knowledge of the autonomous system or its sensor configuration. The proposed method is robust to outliers by considering a non-Gaussian observation model. The approach is demonstrated on a data set collected at the Arctic Mid-Ocean Ridge (AMOR). The method can be used to construct high-resolution bathymetric models from repeated passes over the same area or to accurately coregister other sensors such as cameras, subbottom profilers, and magnetometers. The primary contribution of this work is the application of feature-based matching of bathymetry with a robust Gaussian process.

The tsunamigenic potential of landslide-generated tsunamis on the Vavilov seamount

The investigation of submarine volcanoes and the tsunamigenic potential of possible movements on their flanks is arduous. In most cases, the lack of specific information about the eruptions' history and their consequences does not allow a comprehensive analysis in terms of hazard. Nevertheless, useful clues on the possible occurrence of mass movements on seamounts can be obtained from a series of research fields. These account for morphological studies, observations of hydrothermal activity, collection of geophysical data (for example, detailed DEM, seismic profiles, magnetic data), etc. In this context, this study presents new bathymetric data of the Vavilov submarine volcano (Tyrrhenian Sea, Italy) and a detailed morphological analysis of the structure. The latter allows the identification of zones potentially prone to mass movements and the development of numerical scenarios to investigate the tsunami potential associated to these movements on the Vavilov flanks. Results prove that the waves generated by the mass displacements in the proposed scenarios (involving sliding volumes between 0.32 km3 and 1.7 km3) reach maximum values in the order of centimetres, not considering dispersive effects. Eventually, a scenario involving the partial collapse of the west flank of the Vavilov Seamount is simulated, although the occurrence of such an event in the past is still debated due to the uncertainties related to the origin and development of the volcano dome. In this scenario, water elevation as high as 10 m are found in large portions of the Tyrrhenian coasts: waves are large enough to emplace sizeable tsunami deposits onshore, that could have been preserved until today in some specific stretches of the coast and could be detected by a finalised geological search. This study belongs to a series of works devoted to the submarine structures of the Tyrrhenian Sea aiming to disclose the tsunamigenic potential of submarine mass movements on their flanks.

Global-scale parameters for ecological models

This paper presents a collection of environmental, geophysical, and other marine-related data for marine ecological models and ecological-niche models. It consists of 2132 raster data for 58 distinct parameters at regional and global scales in the ESRI-GRID ASCII format. Most data originally belonged to open data owned by the authors of this article but residing on heterogeneous repositories with different formats and resolutions. Other data were specifically created for the present publication. The collection includes 565 data with global scale range; 154 at 0.5° resolution and 411 at 0.1° resolution; 196 data with annual temporal aggregation over ~10 key years between 1950 and 2100; 369 data with monthly aggregation at 0.1° resolution from January 2017 to ~May 2021 continuously. Data were also cut out on 8 European marine regions. The collection also includes forecasts for different future scenarios such as the Representative Concentration Pathways 2.6 (63 data), 4.5 (162 data), and 8.5 (162 data), and the A2 scenario of the Intergovernmental Panel on Climate Change (180 data).

BitTorrent is Apt for Geophysical Data Collection and Distribution

This article covers a nouveau idea of a way to collect and handle geophysical data with a peer-to-peer network in near real-time. The text covers a brief introduction to the cause, the technology, and the particular case of collecting data from Global Navigation Satellite System (GNSS) stations. We describe the proof-of-concept implementation that has been tested. The test was conducted with an experimental GNSS station and a data aggregation facility. In the test, original raw GNSS signal measurements were transferred to the data aggregation center and subsequently to the consumer. Our implementation utilized the BitTorrent protocol to communicate and transfer data. The solution could be used to enable the majority of data aggregation centers for fast, reliable, and transparent real-time data handling experience for the benefit of the scientific community.

Feasibility assessment on use of proximal geophysical sensors to support precision management

AbstractA study was conducted at three sites in North Dakota to strengthen understanding of the usefulness of different proximal geophysical data types in agricultural contexts of varying pedology. This study hypothesizes that electromagnetic induction (EMI), gamma‐ray sensor (GRS), cosmic‐ray neutron sensor (CRNS), and elevation data layers are all useful in multiple linear regression (MLR) predictions of soil properties that meet expert criteria at three agricultural sites. In addition to geophysical data collection with vehicle‐mounted sensors, 15 soil samples were collected at each site and analyzed for nine soil properties of interest. A set of model training data was compiled by pairing the sampled soil property measurements with the nearest geophysical data. Eleven models passed expert‐defined uncertainty criteria at Site 1, 16 passed at Site 2, and 14 passed at Site 3. Electrical conductivity (EC), organic matter (OM), available water holding capacity, silt, and clay were predicted at Site 1 with an R‐squared of prediction > .50 and acceptable root mean square error of prediction (RMSEP). Bulk density (BD), OM, available water capacity, silt, and clay were predicted with > .50 and acceptable RMSEP at Site 2. At Site 3, no soil properties were predicted with acceptable RMSEP and an > .50. These results confirm feasibility of our method, and the authors recommend the prioritization of EMI data collection if geophysical data collection is limited to a single mapping effort and calibration soil samples are few.

Skyfall: Signal Fusion from a Smartphone Falling from the Stratosphere

A smartphone plummeted from a stratospheric height of 36 km, providing a near-real-time record of its rapid descent and ground impact. An app recorded and streamed useful internal multi-sensor data at high sample rates. Signal fusion with external and internal sensor systems permitted a more detailed reconstruction of the Skyfall chronology, including its descent speed, rotation rate, and impact deceleration. Our results reinforce the potential of smartphones as an agile and versatile geophysical data collection system for environmental and disaster monitoring IoT applications. We discuss mobile environmental sensing capabilities and present a flexible data model to record and stream signals of interest. The Skyfall case study can be used as a guide to smartphone signal processing methods that are transportable to other hardware platforms and operating systems.

Developing Data-Rich Video of Surface Water-Groundwater Interactions for Public Engagement.

Communication of hydrologic data to the public can be improved by connecting data to the places they represent. In our example of data communication, we coupled hydrologic data with simultaneously collected video as both a scientific and public engagement tool. This note presents a method for collecting spatially and temporally dense datasets of water-quality and geophysical data on small streams and lakes, and for displaying the data in a user-friendly format using commercially available software. With this method, multiple instruments are mounted on a canoe and a controlled survey float is carried out to collect data. The data stream is georeferenced and logged using an Arduino microcontroller to provide detailed information about spatial variability. We employed these continuous data-collection methods at small streams and lakes across Wisconsin, USA. Comparison of stream-float sensor data to lab reported data, data collected by alternative sensors, and previously collected data in our study areas indicates that the low-cost temperature, electrical conductivity, pH, and dissolved oxygen sensors performed well. GoPro cameras recorded video throughout the duration of data collection. Our established water-quality and geophysical data collection methods are inexpensive, fast, and reliable, which qualify them as excellent tools for fine-scale spatial understanding of stream and lake habitats' health. Data-rich video connects point measurements of water properties to the appearance of the native environment. This method helps improve our understanding of groundwater and surface water interactions in complex hydrogeologic systems, enhance communication amongst stakeholders, and provide context when monitoring and managing sensitive habitats.

Development of Predictive Geoarchaeological Models to Locate and Assess the Preservation Potential of Submerged Prehistoric Sites Using Remote Sensing, Palaeoenvironmental Analysis, and GIS

Using the Mesolithic site of Tudse Hage in the Great Belt of Denmark, this paper proposes a generic stepwise process to create geoarchaeological models that output seamless morphology maps in a GIS. This was achieved using remote sensing databases and the collection of marine geophysical data, above and below the seabed. On the basis of these data, key areas, with sediment sequences representative of the postglacial transgression surfaces, were identified. Core samples were taken for palaeoenvironmental analysis and dating that enabled a reconstruction of the relative sea-level changes. Using this information, palaeogeographic coastline maps of the Kongemose, late Kongemose, Ertebølle, and Neolithic periods in the Tudse Hage area were prepared, and potential hotspots for archaeological sites were proposed. Since their inundation, submerged prehistoric archaeological sites have been, and are, dynamic, with anthropogenic and natural processes affecting their stability and preservation. With the advocation of in situ preservation as a means of managing underwater cultural heritage, predicting where sites have survived these processes, and where they can be found, in advance of subsea development or other anthropogenic exploitation, is essential. Future natural threats to sites preserved in situ were determined through the modelling of seabed currents and sediment erosion.

Combined Magnetic, Transient Electromagnetic, and Magnetotelluric Methods to Detect a BIF-Type Concealed Iron Ore Body: A Case Study in Gongchangling Iron Ore Concentration Area, Southern Liaoning Province, China

The detection and evaluation of concealed mineral resources deep in metallic mines and in the surrounding areas remain technically difficult. In particular, due to the complex topographic and geomorphic conditions on the surface, the detection environments in these areas limit the choices of detection equipment and data collection devices. In this study, based on metallogenic theory and the metallogenic geological characteristics of banded iron formation (BIF)-type iron ores, equipment for surface geophysical surveys (i.e., the high-precision ground magnetic survey method, the transient electromagnetic method, and the magnetotelluric method) and data collection devices capable of taking single-point continuous measurements were employed to detect the concealed iron ore bodies in the transition zone CID-1 between the Hejia and Dumu iron deposits in the Gongchangling iron ore concentration area in the Anshan-Benxi area (Liaoyang, China), a representative area of BIF-type iron ores. The results showed that an optimal combination of these geophysical survey methods accurately determined the anomalous planar spatial locations and anomalous profile morphologies of the concealed iron ore bodies. On this basis, we determined their locations, burial depths, and scales. Two anomalous zones induced by concealed iron ore bodies, YC-1 and YC-2, were discovered in zone CID-1. Two concealed iron-bearing zones, one shallow (0–150 m) and one deep (300–450 m), were found in YC-1. A 100 m scale drilling test showed that the cumulative thickness of the shallow iron-bearing zone was over 23.6 m.

A review on the hydrodynamic characteristics of autonomous underwater vehicles

Autonomous underwater vehicles play an essential role in geophysical data collection, deep water mining, seafloor mapping, ocean exploration, and in many other related activities starting from military to scientific applications. A detailed understanding of hydrodynamic characteristics will lead to better design, better control, and optimal path planning of autonomous underwater vehicles in the deepest corner of oceans. This article will provide a detailed review of the hydrodynamic characteristics of autonomous underwater vehicles, starting from different experimental techniques used in the analysis of hydrodynamic parameters, methods used for fixing the autonomous underwater vehicles in towing tank, instruments used for measurement of the hydrodynamic parameters. Furthermore, numerical methods employed in performing computational analysis, hydrodynamics-based shape optimization, studies on drag reduction, and finally a detailed list of turbulence models used in the computational fluid dynamics–related numerical simulations. The hydrodynamics-based optimal shape of the autonomous underwater vehicles, the best technique to predict the hydrodynamic parameters, and the best turbulence model for the computational fluid dynamics–based prediction of hydrodynamic parameters will be recommended. At last, the hydrodynamic characteristics of different bio-inspired autonomous underwater vehicles are discussed.

Geophysical characterisation of active thermogenic oil seeps in the salt province of the lower Congo basin part I: Detailed study of one oil-seeping site

Abstract We report the geophysical characterisation of natural oil seep sites through a combination of sea surface evidence of oil leakage from spatial imagery with a large collection of seafloor and subsurface geophysical data. This paper provides a detailed characterisation of one selected active seep site and identifies possible specific feature of oil seep sites. The oil seep is a complex-shaped feature on the seafloor consisting of a cluster of heterometric pockmarks inside a main depression area and peripheral metre-scale seafloor mounds. A strong deformation related to salt tectonics controls the location of the seafloor source by fracturing the overburden. The associated thermal anomaly induces a vertical modification position of the base of the gas hydrate stability zone (BGHSZ) that is used as a fluid migration route towards the crest of the diapir. The combination of local depressions and seafloor amplitude anomalies linked with vertical high-amplitude pipes rooted on the BGHSZ suggests a focused fluid flow towards the seafloor. In peripheral areas, the seafloor mounds are linked by shallow faults to buried high amplitude patches on sub-bottom profiler sections. The combination of restricted-size seafloor mounds with a progressive deepening of the high amplitude from the seafloor suggests a substantial decrease of the hydrocarbon flow towards peripheral areas. The proximity of actively oil-supplying seafloor depressions and seafloor mounds shows that the hydrocarbon flow rapidly decreases laterally. The thermogenic seep site is affected by two consistent and sub-parallel reflections with negative polarity. The first is interpreted as the methane-related BGHSZ, the second could correspond to the base of a thermogenic BGHSZ produced by a mixture of heavier gas. The seafloor roughness and double BSR appear to be specific features of oil seep sites. The geophysical features revealed at a localised study area will be extrapolated towards a larger province for relevance validation.

A Regional Scale Hydrostratigraphy Generated from Geophysical Data of Varying Age, Type, and Quality

In the present study, we show how persistent management and collection of hydrological and geophysical data at a national scale can be combined with innovative analysis methods to generate decision support tools for groundwater and surface water managers. This is exemplified by setting up a regional scale groundwater model in an area with geophysical data of varying age, type, and quality. The structure for the regional model is derived from a newly developed resistivity clay-fraction cluster analysis. This modelling strategy can be used in combination with local detailed geological modelling thus utilizing the detailed expertise locally, while securing a cost-effective (price vs. performance) solution to the numerical simulations of the regional scale water balance. In this way we avoid unwanted boundary effects on the local model simulations due to the presence of artificial numerical boundaries located proximate to the areas of interest. In this application, it is particularly important that boundary conditions are remote, due to the presence of a dense network of buried valley structures. Simulated impacts of groundwater abstraction from two existing well-fields spread through the valley system far beyond the local focus areas of the study.

KESESUAIAN EKOWISATA MANGROVE DITINJAU DARI ASPEK BIOGEOFISIK KAWASAN PANTAI GONDA DI DESA LALIKO KECAMATAN CAMPALAGIAN KABUPATEN POLEWALI MANDAR

Ecotourism is a nature-based tourism activity that includes aspects of education and interpretation of the natural environment and community culture with ecological sustainability management. This study aims to determine the bioecological aspects of mangrove ecosystem as an object of ecotourism and to know the geophysical aspects of Gonda Beach as a supporter of mangrove ecotourism suitability on Gonda Beach. This research was conducted in November 2016 in Laliko Village, Campalagian Sub-district, Polewali Mandar Regency, including mangrove bioecological data collection including thickness, density, species and biota associated with mangrove and coastal geophysical data collection covering wide coastal measurement, coastal slope, depth, tidal, current, wave and substrate of waters. Result of research show potential of mangrove ecosystem to become ecotourism area with good condition of mangrove vegetation. The mangrove species in the ecosystem of the gonda mangroves are Bruguiera gymnorrhiza, Rhizophora stylosa, Rhizophora apiculata, Ceriops tagal, Sonneratia alba, Avicennia alba, Avicennia marina, Xylocarpus granatum and Xylocarpus moluccensis, and diverse biota such as fish, reptiles, birds and crabs as a tourist attraction . Gonda mangrove ecosystem area is a very suitable area to become a mangrove ecotourism area.Keywords: ecotourism, mangrove, conformity analysis, tourism object

Indications of correlation between gravity measurements and isoseismal maps. A case study of Athens basin (Greece)

In this paper, we discuss the correlation between isoseismal contour maps and gravity residual anomaly maps and how it might contribute to the characterization of vulnerable areas to earthquake damage, especially in urban areas, where the geophysical data collection is difficult. More specifically, we compare a couple of isoseismal maps that have been produced and published after the catastrophic earthquake of 7th September 1999 (5.9R) in Athens, the metropolis of Greece, with the residual map produced from the processing and data reduction of a gravity survey that has been carried out in the Athens basin recently. The geologic and tectonic regime of the Athens basin is quite complicated and it is still being updated with new elements. Basically it is comprised of four different geotectonic units, one of them considered as the autochthon. During the gravity investigation, 807 gravity stations were collected, based on a grid plan with spacing almost 1km, covering the entire basin and supported by a newly established gravity base network comprised by thirteen bases. Differential DGPS technique was used for the accurate measurement of all the gravity stations and bases coordinates. After the appropriate data reduction and the construction of the Complete Bouguer Anomaly map, we applied FFT filtering in order to remove the regional component and produce the Residual Anomaly Map. The comparison of the Residual Anomaly Map with the isoseismal contours revealed that the areas with the most damage because of the earthquake were located in the areas with the minimum values of the Residual Anomaly Map.

Offshore Somalia: crustal structure and implications on thermal maturity

T he crustal structure along the passive margin of offshore Somalia has remained largely unknown, due to limited geological and geophysical data collection during the long period of political instability and civil war. The extent of geological information in the area has for many years been restricted to regional-scale features defined from poor quality legacy seismic data (Bunce and Molnar, 1977) and potential field data (Coffin and Rabinowitz, 1987; Rapolla et al., 1995). These observations allowed the development of early plate reconstruction models for Africa and Madagascar. However, since 2012 the region has experienced a period of relative political stability following the inauguration of the Federal Government of Somalia. Two 2D seismic acquisition programmes were undertaken in 2014 and 2016. The newly acquired seismic data have facilitated the development of new theories and understanding of the evolution of the Somalian passive margin (Kearns et al., 2016). In this study, we integrate newly acquired long offset seismic data with wells and regional satellite gravity and magnetic data, to critically assess the structural configuration, and map the continental to oceanic crust transition. We use gravity modelling techniques to support our observations. We also discuss the possible implications of our findings on source rock thermal maturity.

Virtual private network technologies in real-time geophysical data collection systems

Some results of designing a system for online collection of data from terrestrial recorders of global satellite navigation systems are presented. The specific features of applying VPN technologies in geophysical data collection systems in real-time mode are discussed. Two of the most popular software VPN implementations are analyzed for comparison: SSTP, available for Microsoft Windows, and the free OpenVPN package. It is shown that both variants have commensurable performance. In unstable channels with low throughput, SSTP ensures a higher capacity, and OpenVPN is more stable and better resistant to discontinuous decreases in throughput.