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Application of Geology and GIS

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A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).

Deadline for manuscript submissions: closed (31 August 2021) | Viewed by 35496

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Dr. Peter Blišťan

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Institute of Geodesy, Cartography and Geographical Information Systems, Faculty of Mining, Ecology, Process Control and Geotechnology, Technical University of Kosice, 040 01 Kosice, Slovakia
Interests: geographic information systems (GIS); 3D visualization; spatial modelling; applied geology; remote sensing and data collection; geostatistics; CAD systems
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Dear Colleagues,

Geology is one of the oldest scientific disciplines and is known for its interdisciplinarity. It includes a group of basic geological sciences and applied geological sciences (paleontology, mineralogy, petrology, stratigraphy, sedimentology, structural geology, regional geology, engineering geology, deposit geology, volcanology, hydrogeology, marine geology, geochemistry). Geology and Geographic Information Systems (GIS) are now closely linked scientific disciplines that offer a set of tools effectively used to process and analyze different types of geological data. Geographic information systems and their tools are thus basic tools for observing and exploring the Earth. Probably the most widespread applications of geology and GIS today include remote sensing of the Earth and image data processing in GIS; monitoring the quality and condition of the abiotic component of the environment; monitoring of natural phenomena, including geohazards; spatial modeling of mineral deposits; monitoring of dynamics of land changes in GIS and prediction of further development; geological mapping and creation of geological maps and 3D models; modeling of spatial distribution of objects and phenomena using mathematical-statistical and geostatistical techniques and procedures and others.

The above-mentioned links between geology and GIS also significantly affect the problems that arise mainly from the negative human impact on the environment. The world's population is growing at a rapid pace and the relocation of the population from the countryside to the cities will not stop in the foreseeable future. Human activity is thus the main cause of all global environmental changes. GIS technologies are thus becoming a fundamental pillar on which interdisciplinary research and cooperation of researchers is built in order to achieve a better understanding of the relationship—man versus the environment.

The aim of this Special Issue is to provide an innovative and original view of the relationship between geology and GIS technologies in several application areas, but with an emphasis on the interdisciplinarity that lies behind the term geology. Last but not least, it will focus on the processes of acquisition, processing, and analysis of geospatial data, which have undergone significant development in recent years and have seen the emergence of new methods and techniques.

Prof. Dr. Peter Blišťan
Guest Editor

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Keywords

Applied Geology
Geographic Information Systems (GIS)
Geomatics
Remote sensing and Data Collection
Mapping and Monitoring
Spatial Data Analysis
Geospatial Modelling
Geostatistics for Geology
3D Visualization
Geohazards
Environment

Published Papers (10 papers)

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Research

20 pages, 13613 KiB

Open AccessArticle

Spatial Modelling of Kaolin Deposit Demonstrated on the Jimlíkov-East Deposit, Karlovy Vary, Czech Republic

by Marcela Jarošová and František Staněk

ISPRS Int. J. Geo-Inf. 2021, 10(11), 788; https://doi.org/10.3390/ijgi10110788 - 18 Nov 2021

Viewed by 1706

Abstract

The present study is focused on spatial modelling of a kaolin deposit in Karlovy Vary, Czech Republic, and the methodical procedure of development, evaluation and visualization of a 3D model are described step by step. The implementation of this methodology is performed in Visual Studio 2019 with use of the Surfer and Voxler objects from Golden Software. This methodology combined with the newly developed software (Kaolin_A and Kaolin_Viz programs) allow a user to create a variant dynamic model for the same or similar types of deposits. It enables a quick update of the model when changing the input data, based on the new mining exploration or when changing the modelling parameters. The presented approach leads to a more advanced evaluation of deposits, including various estimates of reserves according to pre-specified usability conditions. The efficiency of the developed methodology and the software for the evaluation of the deposit are demonstrated on the kaolin deposit Jimlíkov-East, located near the village Jimlíkov about 5 km west of Karlovy Vary in the Czech Republic. Full article

(This article belongs to the Special Issue Application of Geology and GIS)

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22 pages, 17914 KiB

Open AccessArticle

Morpho-tectonic Assessment of the Abu-Dabbab Area, Eastern Desert, Egypt: Insights from Remote Sensing and Geospatial Analysis

by Abdelrahman Khalifa, Bashar Bashir, Abdullah Alsalman and Nazik Öğretmen

ISPRS Int. J. Geo-Inf. 2021, 10(11), 784; https://doi.org/10.3390/ijgi10110784 - 17 Nov 2021

Cited by 12 | Viewed by 2067

Abstract

The Abu-Dabbab area, located in the central part of the Egyptian Eastern Desert, is an active seismic region where micro-earthquakes (≈M_L < 2.0) are recorded regularly. Earthquake epicenters are concentrated along an ENE–WSW trending pattern. In this study, we used morphological indexes, including the valley floor width-to-valley floor height ratio (V_f), mountain front sinuosity (S_mf), the asymmetry factor index (A_f), the drainage basin shape index (B_s), the stream length–gradient index (S_L), hypsometric integral (H_i) water drainage systems, and a digital elevation model analysis, to identify the role of tectonics. These indexes were used to define the relative tectonic activity index (RTAI), which can be utilized to distinguish low (RTAI < 1.26), moderate (RTAI = 1.26–1.73), and high (RTAI > 1.73) tectonic activity signals all over the study area. Firstly, our results indicate low to medium tectonic activity and general anomaly patterns detected along the major tectonic zones of the study area. Secondly, based on most of the low to medium tectonic activity distributed in the study area and the detected anomalies, we discuss two potential drivers of the seismicity in the Abu-Dabbab area, which are fault-controlled and deep-rooted activities. Full article

(This article belongs to the Special Issue Application of Geology and GIS)

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16 pages, 5882 KiB

Open AccessArticle

Mapping Mineral Prospectivity Using a Hybrid Genetic Algorithm–Support Vector Machine (GA–SVM) Model

by Xishihui Du, Kefa Zhou, Yao Cui, Jinlin Wang and Shuguang Zhou

ISPRS Int. J. Geo-Inf. 2021, 10(11), 766; https://doi.org/10.3390/ijgi10110766 - 12 Nov 2021

Cited by 7 | Viewed by 2316

Abstract

Machine learning (ML) as a powerful data-driven method is widely used for mineral prospectivity mapping. This study employs a hybrid of the genetic algorithm (GA) and support vector machine (SVM) model to map prospective areas for Au deposits in Karamay, northwest China. In the proposed method, GA is used as an adaptive optimization search method to optimize the SVM parameters that result in the best fitness. After obtaining evidence layers from geological and geochemical data, GA–SVM models trained using different training datasets were applied to discriminate between prospective and non-prospective areas for Au deposits, and to produce prospectivity maps for mineral exploration. The F1 score and spatial efficiency of classification were calculated to objectively evaluate the performance of each prospectivity model. The best model predicted 95.83% of the known Au deposits within prospective areas, occupying 35.68% of the study area. The results demonstrate the effectiveness of the GA–SVM model as a tool for mapping mineral prospectivity. Full article

(This article belongs to the Special Issue Application of Geology and GIS)

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20 pages, 5247 KiB

Open AccessArticle

A Comparative Study of Frequency Ratio, Shannon’s Entropy and Analytic Hierarchy Process (AHP) Models for Landslide Susceptibility Assessment

by Sandeep Panchal and Amit K. Shrivastava

ISPRS Int. J. Geo-Inf. 2021, 10(9), 603; https://doi.org/10.3390/ijgi10090603 - 12 Sep 2021

Cited by 29 | Viewed by 3626

Abstract

Landslide susceptibility maps are very important tools in the planning and management of landslide prone areas. Qualitative and quantitative methods each have their own advantages and dis-advantages in landslide susceptibility mapping. The aim of this study is to compare three models, i.e., frequency ratio (FR), Shannon’s entropy and analytic hierarchy process (AHP) by implementing them for the preparation of landslide susceptibility maps. Shimla, a district in Himachal Pradesh (H.P.), India was chosen for the study. A landslide inventory containing more than 1500 landslide events was prepared using previous literature, available historical data and a field survey. Out of the total number of landslide events, 30% data was used for training and 70% data was used for testing purpose. The frequency ratio, Shannon’s entropy and AHP models were implemented and three landslide susceptibility maps were prepared for the study area. The final landslide susceptibility maps were validated using a receiver operating characteristic (ROC) curve. The frequency ratio (FR) model yielded the highest accuracy, with 0.925 fitted ROC area, while the accuracy achieved by Shannon’s entropy model was 0.883. Analytic hierarchy process (AHP) yielded the lowest accuracy, with 0.732 fitted ROC area. The results of this study can be used by engineers and planners for better management and mitigation of landslides in the study area. Full article

(This article belongs to the Special Issue Application of Geology and GIS)

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16 pages, 3737 KiB

Open AccessArticle

Geospatial Management and Analysis of Microstructural Data from San Andreas Fault Observatory at Depth (SAFOD) Core Samples

by Elliott M. Holmes, Andrea E. Gaughan, Donald J. Biddle, Forrest R. Stevens and Jafar Hadizadeh

ISPRS Int. J. Geo-Inf. 2021, 10(5), 332; https://doi.org/10.3390/ijgi10050332 - 14 May 2021

Cited by 1 | Viewed by 2858

Abstract

Core samples obtained from scientific drilling could provide large volumes of direct microstructural and compositional data, but generating results via the traditional treatment of such data is often time-consuming and inefficient. Unifying microstructural data within a spatially referenced Geographic Information System (GIS) environment provides an opportunity to readily locate, visualize, correlate, and apply remote sensing techniques to the data. Using 26 core billet samples from the San Andreas Fault Observatory at Depth (SAFOD), this study developed GIS-based procedures for: 1. Spatially referenced visualization and storage of various microstructural data from core billets; 2. 3D modeling of billets and thin section positions within each billet, which serve as a digital record after irreversible fragmentation of the physical billets; and 3. Vector feature creation and unsupervised classification of a multi-generation calcite vein network from cathodluminescence (CL) imagery. Building on existing work which is predominantly limited to the 2D space of single thin sections, our results indicate that a GIS can facilitate spatial treatment of data even at centimeter to nanometer scales, but also revealed challenges involving intensive 3D representations and complex matrix transformations required to create geographically translated forms of the within-billet coordinate systems, which are suggested for consideration in future studies. Full article

(This article belongs to the Special Issue Application of Geology and GIS)

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17 pages, 5878 KiB

Open AccessArticle

Integration of an InSAR and ANN for Sinkhole Susceptibility Mapping: A Case Study from Kirikkale-Delice (Turkey)

by Hakan A. Nefeslioglu, Beste Tavus, Melahat Er, Gamze Ertugrul, Aybuke Ozdemir, Alperen Kaya and Sultan Kocaman

ISPRS Int. J. Geo-Inf. 2021, 10(3), 119; https://doi.org/10.3390/ijgi10030119 - 27 Feb 2021

Cited by 7 | Viewed by 3519

Abstract

Suitable route determination for linear engineering structures is a fundamental problem in engineering geology. Rapid evaluation of alternative routes is essential, and novel approaches are indispensable. This study aims to integrate various InSAR (Interferometric Synthetic Aperture Radar) techniques for sinkhole susceptibility mapping in the Kirikkale-Delice Region of Turkey, in which sinkhole formations have been observed in evaporitic units and a high-speed train railway route has been planned. Nine months (2019–2020) of ground deformations were determined using data from the European Space Agency’s (ESA) Sentinel-1A/1B satellites. A sinkhole inventory was prepared manually using satellite optical imagery and employed in an ANN (Artificial Neural Network) model with topographic conditioning factors derived from InSAR digital elevation models (DEMs) and morphological lineaments. The results indicate that high deformation areas on the vertical displacement map and sinkhole-prone areas on the sinkhole susceptibility map (SSM) almost coincide. InSAR techniques are useful for long-term deformation monitoring and can be successfully associated in sinkhole susceptibility mapping using an ANN. Continuous monitoring is recommended for existing sinkholes and highly susceptible areas, and SSMs should be updated with new results. Up-to-date SSMs are crucial for the route selection, planning, and construction of important transportation elements, as well as settlement site selection, in such regions. Full article

(This article belongs to the Special Issue Application of Geology and GIS)

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26 pages, 17363 KiB

Open AccessArticle

Micro-Fabric Analyzer (MFA): A New Semiautomated ArcGIS-Based Edge Detector for Quantitative Microstructural Analysis of Rock Thin-Sections

by Roberto Visalli, Gaetano Ortolano, Gaston Godard and Rosolino Cirrincione

ISPRS Int. J. Geo-Inf. 2021, 10(2), 51; https://doi.org/10.3390/ijgi10020051 - 27 Jan 2021

Cited by 12 | Viewed by 3237

Abstract

Micro-Fabric Analyzer (MFA) is a new GIS-based tool for the quantitative extrapolation of rock microstructural features that takes advantage both of the characteristics of the X-ray images and the optical image features. Most of the previously developed edge mineral grain detectors are uniquely based on the physical properties of the X-ray-, electron-, or optical-derived images; not permitting the exploitation of the specific physical properties of each image type at the same time. More advanced techniques, such as 3D microtomography, permit the reconstruction of tridimensional models of mineral fabric arrays, even though adjacent mineral grain boundaries with the same atomic density are often not detectable. Only electron backscatter diffraction (EBSD) allows providing high-performing grain boundary detection that is crystallographically differentiated per mineral phase, even though it is relatively expensive and can be executed only in duly equipped microanalytical laboratories by suitably trained users. Instead, the MFA toolbox allows quantifying fabric parameters subdivided per mineral type starting from a crossed-polarizers high-resolution RGB image, which is useful for identifying the edges of the individual grains characterizing rock fabrics. Then, this image is integrated with a set of micro-X-ray maps, which are useful for the quantitative extrapolation of elemental distribution maps. In addition, all this is achieved by means of low-cost and easy-to-use equipment. We applied the tool on amphibolite, mylonitic-paragneiss, and -tonalite samples to extrapolate the particle fabric on different metamorphic rock types, as well as on the same sandstone sample used for another edge detector, which is useful for comparing the obtained results. Full article

(This article belongs to the Special Issue Application of Geology and GIS)

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32 pages, 17751 KiB

Open AccessArticle

ArcStereoNet: A New ArcGIS^® Toolbox for Projection and Analysis of Meso- and Micro-Structural Data

by Gaetano Ortolano, Alberto D’Agostino, Mario Pagano, Roberto Visalli, Michele Zucali, Eugenio Fazio, Ian Alsop and Rosolino Cirrincione

ISPRS Int. J. Geo-Inf. 2021, 10(2), 50; https://doi.org/10.3390/ijgi10020050 - 26 Jan 2021

Cited by 4 | Viewed by 5143

Abstract

ArcStereoNet is a new ArcGIS^® based toolbox for stereographic projections that we implement here using Python 2.7 programming language. The reason to develop another stereographic projection package arises from the recent use of Python as an exclusive programming language within the ArcGIS^® environment. This permits a more flexible approach for the development of tools with very intuitive GUIs, and also allows the user to take full advantage of all potential GIS mapping processes. The core of this new projections toolbox is based on the capability to easily apply and compare most of the commonly used statistical methods for cluster and girdle analysis of structural data. In addition to the well-known Fisher, K-means, and Bingham data elaborations, a completely new algorithm for cluster analysis and mean vector extraction (Mean Extractor from Azimuthal Data), was developed, thereby allowing a more reliable interpretation of any possible structural data distribution. Furthermore, as in any other GIS platform, users can always precisely correlate each single projected data point with the corresponding geographical/locality position, thereby merging or subdividing groups of structural stations with a simple selection procedure. ArcStereoNet also creates rose diagrams, which may be applied not only to fault/joint planes orientation data, but also for the analysis of 2D microstructural fabric parameters. These include geometrical datasets derived from the minimum bounding approach as applied to vectorized grains in thin sections. Finally, several customization settings ensure high-quality graphic outputs of plots, that also allow easy vector graphics post-processing. Full article

(This article belongs to the Special Issue Application of Geology and GIS)

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21 pages, 13190 KiB

Open AccessArticle

Estimating Soil Erosion Rate Changes in Areas Affected by Wildfires

by Nikolaos Depountis, Maria Michalopoulou, Katerina Kavoura, Konstantinos Nikolakopoulos and Nikolaos Sabatakakis

ISPRS Int. J. Geo-Inf. 2020, 9(10), 562; https://doi.org/10.3390/ijgi9100562 - 28 Sep 2020

Cited by 18 | Viewed by 3547

Abstract

In recent decades, wildfires have become a serious threat worldwide, producing disasters in the natural and anthropogenic environment as well as serious economic losses. One of wildfire’s major impacts is soil erosion, as it may cause major problems in both the physical and anthropogenic environment and seriously affect the landscape. This study investigates the soil erosion rate changes in areas affected by wildfires and uses, as a pilot area, the drainage basin of the Pinios earth-filled dam located in the Ilia Regional Unit, western Greece, which has suffered serious erosion changes after a wildfire event. For this purpose, the Revised Universal Soil Loss Equation (RUSLE) is applied in GIS software, and the soil erosion rate changes in the selected investigation area are estimated at different time intervals. Specifically, soil erosion rate changes are calculated by importing the factors from the RUSLE equation in the GIS software and uses as a dependent variable the cover management factor C, which is strongly influenced by large destructive fires. The models that are produced are compared with each other by collating average annual soil erosion maps and rates before the fire, immediately after the fire and for the existing conditions occurring in the pilot area. Full article

(This article belongs to the Special Issue Application of Geology and GIS)

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16 pages, 7037 KiB

Open AccessArticle

Research of Automatic Generation for Engineering Geological Survey Reports Based on a Four-Dimensional Dynamic Template

by Yujiao Lei, Jiqiu Deng, Jian Lin, Jeffrey M. Dick, Mohammad Naser Lessani and Chaoyue Liu

ISPRS Int. J. Geo-Inf. 2020, 9(9), 496; https://doi.org/10.3390/ijgi9090496 - 21 Aug 2020

Cited by 3 | Viewed by 3040

Abstract

Errors and inefficiency may be caused by manual processing of complex templates for the preparation and management of engineering survey reports. To address this problem, this paper analyzes the multidimensional variable features of professional field documents and proposes a generation model of standardized reports based on a four-dimensional dynamic template. This approach splits the standardized report into multiple parts to construct a hierarchical tree that represents the report structure according to the report rules, then stores the tree in a graph database, and finally generates the desired report dynamically by retrieving the relational tree for the template and obtaining the relevant data. The model has been applied to the engineering geological survey report system and is shown to improve the working efficiency and data accuracy of the report preparation. Results indicate that the model is feasible and effective. Full article

(This article belongs to the Special Issue Application of Geology and GIS)

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