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Elsevier

Books in Computers in geosciences

This portfolio encompasses advanced computational methods, data analysis, modelling, and visualization techniques tailored for geoscience applications. It supports geologists, geophysicists, and environmental scientists engaged in simulating Earth systems, interpreting large datasets, and developing innovative tools. Featuring state-of-the-art algorithms and case studies, these resources facilitate breakthroughs in seismic imaging, mineral exploration, and environmental monitoring, enabling researchers to solve complex geological problems with precision and efficiency.

  • Image Segmentation in the Geosciences

    From Fundamentals to Frontiers
    • 1st Edition
    • Ardiansyah Koeshidayatullah
    • English
    Image Segmentation in Geosciences: From Fundamentals to Frontiers is the definitive resource for researchers, practitioners, and students working with complex geological imagery. This volume addresses the increasing need for precise, quantitative interpretation of diverse datasets, from micro-CT scans to satellite imagery, by consolidating classical and modern computational methodologies. As the volume of geoscience data expands, the book emphasizes the necessity of advanced segmentation techniques, including machine learning and deep learning, to transform raw data into actionable insights. It systematically covers core principles, innovative AI-driven approaches, and applications across reservoir characterization, geophysics, remote sensing, and environmental monitoring, supported by detailed case studies. The content spans methods, fractal and multifractal analysis, and cutting-edge AI architectures like CNNs, GANs, and transformers. It guides readers through practical workflows, visualization tools, and evaluation metrics, enabling them to bridge the gap between theoretical algorithms and real-world geoscience problems. This book empowers geoscientists, data scientists, and engineers to leverage the latest computational advances for more accurate resource assessment, hazard detection, and environmental management, fostering a new era of data-driven Earth sciences.

  • Harmonizing Earth Observation Data for Enhanced Spatial Analysis

    • 1st Edition
    • Tomaž Podobnikar
    • English
    Harmonizing Earth Observation Data for Enhanced Spatial Analysis explores the critical aspects of Earth observation (EO) data and its pivotal role in spatial analysis. Addressing fundamental aspects of EO data, the book emphasizes the importance of reliable, high-quality information for meaningful analysis. It reviews the interaction and integration of various datasets, highlighting the necessity of combining diverse sources to enhance analytical outcomes. In addition, sections cover essential techniques such as downscaling, generalization, and upscaling, providing insights into how these processes can optimize data usability while maintaining integrity. A significant focus is placed on harmonization, detailing strategies to reduce uncertainty and improve consistency across multidimensional datasets. This interoperability is crucial for effective spatial analysis, which relies on coherent datasets to derive actionable insights. Additionally, the book discusses the interplay between EO and geospatial data, illustrating how their integration can enhance analytics capabilities. It presents comprehensive workflows, tools and applications that facilitate advanced spatial analysis, equipping researchers and practitioners with the necessary resources to harness EO data effectively.

  • AI in Cartography

    A New Era of Making and Using Maps
    • 1st Edition
    • Samantha T. Arundel + 1 more
    • English
    AI in Cartography: A New Era of Making and Using Maps offers an in-depth exploration of how artificial intelligence is transforming the field of cartography. The book begins by establishing the foundational concepts of AI technologies relevant to mapmaking, including the data requirements and practical implementation of AI-driven cartographic solutions. It highlights how AI enhances map recognition and analysis, enabling more efficient and accurate interpretation of spatial information. The digitization of historical maps through AI techniques preserves valuable geographic heritage while facilitating modern analysis. The text further examines automated map generalization and generative AI approaches that revolutionize cartographic representation, improving both the creation and usability of maps. It also addresses important challenges such as bias, uncertainty, and the explainability of AI systems, alongside the ethical and governance issues surrounding AI in mapping. These discussions emphasize the need for responsible and transparent AI applications in cartography. Innovations in AI-driven topographic and thematic mapping are showcased, illustrating the growing role of AI in supporting smart cities and digital twin technologies. The book also explores how AI contributes to resilience and sustainability in environmental management. Looking ahead, it outlines future directions for integrating AI with cartographic practices, highlighting the potential for continued advancement in this dynamic field. This comprehensive volume serves as a valuable resource for researchers and practitioners, demonstrating how AI is reshaping the art and science of mapping for the modern era.

  • Landslide Science

    Geospatial Advances in Monitoring, Modeling, and Management
    • 1st Edition
    • Christos Polykretis + 3 more
    • English
    Landslide Science: Geospatial Advances in Monitoring, Modeling, and Management presents a detailed exploration of the latest advancements in landslide research, offering a thorough examination of the latest geospatial technologies and methodologies. The book begins with a comprehensive exploration of landslides, starting with an understanding of their nature, including characteristics, types, and historical perspectives. Factors triggering or influencing landslides are examined, such as rainfall, earthquakes, and topographical influences. Remote sensing techniques for landslide investigation are detailed, covering detection, monitoring, and imagery data processing methods using various sensors and technologies.In addition, spatial landslide assessment and mapping are discussed, including inventory mapping, susceptibility assessment, and hazard assessment utilizing different approaches and uncertainty validation methods. Engineering-based landslide analysis focuses on geotechnical aspects, hydrogeological influences, and methodologies for simulations and slope stability analysis. The book also addresses landslide impacts and risk management strategies, covering vulnerability assessment, risk analysis, environmental consequences, prevention, mitigation strategies, and community engagement.

  • AI and Remote Sensing for Monitoring, Prediction, and Mitigation of Urban Climate Risks

    • 1st Edition
    • Linlin Lu + 2 more
    • English
    AI and Remote Sensing for Monitoring, Prediction, and Mitigation of Urban Climate Risks provides a comprehensive exploration of the urban heat island (UHI) phenomenon, and the innovative technologies employed to address its challenges.The book begins by outlining the UHI crisis, highlighting the detrimental effects of urbanization on local climates, particularly the increased temperatures in urban environments. It emphasizes the role of remote sensing technologies and diverse data sources in analyzing UHIs, laying the groundwork for advanced research. The text then looks into AI-driven methodologies, showcasing how machine learning and deep learning techniques can enhance urban land classification, estimate urban 3D morphology, and retrieve land surface temperatures. Additionally, it discusses the application of deep learning for predicting UHIs and identifying the driving factors behind their formation, providing valuable insights into urban climate dynamics. In its final sections, the book addresses practical applications of these technologies, including the detection and assessment of heatwave events and urban heat health risk evaluations. It also emphasizes the importance of urban green infrastructure as a mitigation strategy and discusses the transition from data analysis to policy formulation. This essential resource illustrates how AI and remote sensing can be harnessed to monitor, predict, and mitigate urban climate risks effectively, fostering more resilient and sustainable cities.

  • Pattern Recognition Techniques in Gas Sensing

    • 1st Edition
    • Ajit Khosla + 2 more
    • English
    Pattern Recognition Techniques in Gas Sensing overviews the methods and technologies used to detect and analyze gases through advanced pattern recognition approaches. The book begins by introducing the fundamentals of gas sensors and their unique data characteristics, laying the groundwork for understanding the complexities involved in gas detection. It then explores the basics of pattern recognition, detailing various statistical methods that have been traditionally employed to interpret sensor data. The text looks into Bayesian and probabilistic methods, offering insights into their applications for improving gas sensing accuracy.Cluster analysis techniques are examined as tools for grouping sensor responses to identify specific gas patterns. The integration of machine learning in gas sensing is thoroughly discussed, highlighting how these algorithms enhance detection capabilities by learning from complex datasets. Further, the book presents deep learning techniques, showcasing their power in handling large volumes of sensor data and extracting meaningful features for precise gas identification. Data processing techniques essential for preparing and refining sensor outputs are also covered, providing readers with practical knowledge for real-world applications and future directions.

  • EnviroGIS

    Geographic Information Systems in Environmental Analysis
    • 1st Edition
    • Jesús Rodrigo-Comino
    • English
    EnviroGIS: Geographic Information Systems in Environmental Analysis is a comprehensive and timely textbook that provides a foundation for those considering further research in GIS, environmental sciences, or geosciences. It offers a thorough understanding of how to initiate a GIS course in Geosciences, introducing the importance of GIS by taking a step-by-step approach for delineating the study area. This book provides diverse ideas, data, and practical examples for both replication and reference to students, scientists, and lecturers engaging with GIS and environmental science, particularly areas focused on Earth Surface Processes using tools like ArcGIS Pro, QGIS, Terrset/Idrissi, Google Earth Engine, R, and Pix4D.In the first part, the textbook delineates the importance of GIS. Moving on, in the second part it focuses on the most relevant topics in environmental analysis. It outlines the preparation of seminars related to changing scales, soil, plant, and catchment dynamic processes, such as erosion and interpolations. Covering topics such as data mining, and connectivity processes, EnviroGIS highlights the way in which Artificial Intelligence enables the creation of accurate forecasts of challenging-to-predi... Earth surface processes. Additionally, the biosphere is delved into to show how GIS courses assess fauna and vegetation within natural or human ecosystems. The final part of the book is centered on specific cases, considering different GIS data formats including shapefiles, multilayer projects, and recent natural hazards or disasters, such as volcanic eruptions or hillslope degradation due to human activities.

  • Reshaping Geotechnical Engineering with Machine Learning

    Theory, Applications, and Innovations
    • 1st Edition
    • Divesh Ranjan Kumar + 3 more
    • English
    Reshaping Geotechnical Engineering with Machine Learning: Theory, Applications, and Innovations explores the transformative impact of machine learning (ML) on the field of geotechnical engineering. The book begins by examining the broad applications of ML in key areas such as foundation engineering and slope stability, demonstrating how advanced algorithms can enhance predictive accuracy and decision-making. It emphasizes the importance of robust data acquisition and preprocessing techniques, which are critical for the successful implementation of ML models in geotechnical contexts. The text examines the use of machine learning for predicting soil behavior, a complex challenge in geotechnical engineering, and highlights its role in risk assessment and management.In addition, it also addresses the integration of ML with finite element modeling to improve the analysis of tunnel and underground stability. The applications of machine learning in understanding geotechnical materials further showcase the versatility of these techniques. It also covers experimental investigations, including laboratory and field studies, which provide essential data for model training and validation. Through detailed case studies, the book illustrates practical implementations of machine learning, bridging theory and real-world problem-solving.

  • Big Data Mining and Machine Learning in Geoscience

    • 1st Edition
    • Yongzhang Zhou + 4 more
    • English
    Big Data Mining and Machine Learning in Geoscience offers a comprehensive overview of techniques and applications of data science in the geosciences. Sections cover essential, foundational concepts in data cleaning and preprocessing, thus ensuring the quality and reliability of geoscientific data. Next, the book explores dimensionality reduction methods designed to simplify high-dimensional data without losing critical information. The text covers classification and prediction techniques that enable the identification of patterns and forecasting of geological phenomena, and graphical data processing and handling of infinite stream data and time series are highlighted, along with their importance in real-time monitoring and dynamic systems analysis.In addition, the book explores advanced machine learning and deep learning methods, showcasing their transformative impact on geoscientific research. It also introduces knowledge graphs and large language models as emerging tools that enhance data integration, interpretation, and discovery. AI-driven geology is presented as a forward-looking approach that leverages artificial intelligence to revolutionize traditional geological practices, offering improved accuracy and insight. Throughout, practical examples and case studies illustrate how these technologies can be applied to solve complex problems in geoscience.

  • Multimodal Remote Sensing Fusion and Classification

    Algorithms and Applications
    • 1st Edition
    • Man-On Pun + 1 more
    • English
    Multimodal Remote Sensing Data Fusion for Classification: Algorithms and Applications offers a comprehensive overview of Earth observation data fusion, focusing on multimodal remote sensing. It presents state-of-the-art algorithms and practical applications that enhance understanding of Earth's dynamic processes. Through detailed analysis, case studies, and practical examples, this book equips readers with the necessary tools to effectively utilize multimodal data fusion for land cover and land use classification, as well as environmental monitoring, making it an invaluable resource for those in remote sensing and Earth sciences.Furthermore... the book is tailored for Masters and Doctorate students, scientists, and professionals in remote sensing, geography, and Earth sciences. It delves into the integration and analysis of multimodal remote sensing data, offering insights into sustainable solutions for environmental challenges. This comprehensive coverage ensures readers are well-versed in the cutting-edge techniques and methodologies required for advanced Earth observation and classification tasks.

  • Remote Sensing, Big Data, and GeoAI

    Exploring Applications with Geospatial Insights
    • 1st Edition
    • Erin Bunting + 3 more
    • English
    Remote Sensing, Big Data, and GeoAI: Exploring Applications with Geospatial Insights is an in-depth analysis of the transformative power of AI and Big Data in remote sensing. This book provides readers with the knowledge and tools to utilize these technologies to enhance decision-making and analysis. Starting from fundamental concepts, it progresses to advanced applications, offering accessible explanations and real-world examples to bridge the gap between theory and practice. The book uses a structured format to balance theoretical knowledge with immersive case studies, giving readers a deeper understanding of practical implications.It also covers ethical and legal considerations, making it an invaluable resource for researchers, professionals, and students keen on using AI and Big Data techniques in remote sensing to solve complex geospatial challenges.

  • Handbook of Satellite Land Products

    • 1st Edition
    • Shunlin Liang + 1 more
    • English
    Handbook of Satellite Land Products compiles the key information of as many satellite products as possible for each essential land variable. It provides a comprehensive list of openly accessible high-level satellite products that characterize the essential land surface variables of the Earth system, including the original data sources, inversion algorithms, product characteristics, validation accuracy, and any existing applications. Each product includes satellite data inversion methodology and high-level product generation and application information, allowing for comparison of different products and selection of the correct ones for different applications.This book will help researchers, professors, and graduate students grasp the knowledge of existing satellite land products, understand the advantages and limitations, and follow the practical application examples.

  • The Geoinformatics Frontier

    AI, Big Data, and Crowdsourced Technologies
    • 1st Edition
    • Kleomenis Kalogeropoulos + 3 more
    • English
    The Geoinformatics Frontier: AI, Big Data, and Crowdsourced Technologies tackles the critical challenge of integrating Geoinformatics, AI, Big Data, and VGI; offering a comprehensive introduction to these pivotal concepts, the book elucidates their foundations and relevance to Geoinformatics. It approaches builds on the theory discussed with practical guidance, examples, and detailed case studies; equipping readers with the knowledge needed to effectively implement them. The book presents case studies spanning various sectors, showcasing how the technologies can be successfully employed to address intricate spatial issues and facilitate well-informed decision-making for the complexities of managing large-scale spatial datasets. It also provides indispensable insights into data collection, storage, quality control, and fusion techniques, offering practical solutions to the challenges of data storage, processing, and analysis. The Geoinformatics Frontier serves as an indispensable guide, bridging the gap in understanding and practice for geospatial scientists, empowering readers to harness the transformative potential of Geoinformatics and advanced computer technologies.

  • GeoAI for Earth Observation Imagery

    Fundamentals and Practical Applications
    • 1st Edition
    • Dalton Lunga + 1 more
    • English
    GeoAI for Earth Observation Imagery: Fundamentals and Practical Applications comprehensively covers methodologies of AI and Machine Learning applications of image processing for Earth Observation (EO) Imagery. As traditional image processing methods face challenges with handling vast volumes of EO imagery, leading to efficiencies and limitations when extracting meaningful insights, AI-driven approaches can enhance the efficiency, accuracy, and scalability of image processing. Chapters cover essential methodologies including atmospheric compensation, image enhancement techniques like deblurring and superresolution, and advanced analysis methods such as semantic segmentation and object detection.Cutting-ed... approaches to computing, automating, and optimizing image processing tasks are also covered. Additionally, emerging trends in GeoAi and their implication on future research are reviewed. The book serves as an essential guide for navigating the complexities of spatial data and equips readers with knowledge to enhance their analytical capabilities.

  • Introduction and Applications of Machine Learning in Geotechnics

    • 1st Edition
    • Zong Woo Geem + 5 more
    • English
    Introduction and Applications of Machine Learning in Geotechnics offers a comprehensive exploration of machine learning methodologies and their diverse applications in geotechnical engineering. The book begins with a detailed review of machine learning methods tailored for geotechnical applications, setting the foundation for subsequent chapters. Regression models are utilized to predict shear wave velocities while optimization-based approaches are employed to determine the optimal dimensions of reinforced concrete (RC) retaining walls. The book further explores the identification of gravelly soil through optimized machine learning models and predicts stress-strain responses using data from simple shear tests.Additionally, it outlines the forecasting of liquefaction events triggered by seismic activities and estimates the uniaxial compressive strength of soil using machine learning techniques. The prediction of vertical effective stress and specific penetration resistance is examined to enhance soil characterization and geotechnical analyses. The book's authors provide valuable insights for geotechnical engineers and researchers seeking to leverage advanced computational tools for enhanced geotechnical assessments and design processes.

  • Advances in Computational Geomechanics

    Advanced Computational Techniques and Methodologies in Geotechnical Engineering
    • 1st Edition
    • Mohamed Shahin + 1 more
    • English
    Advances in Computational Geomechanics: Advanced Computational Techniques and Methodologies in Geotechnical Engineering provides a comprehensive overview of cutting-edge computational methodologies in geotechnical engineering. The first part examines stochastic, probabilistic, and reliability analyses in geotechnical engineering, covering stochastic methods, probabilistic approaches to soil characterization, reliability analysis in geotechnical design, and risk assessment and management in geotechnical projects. The second part delves into artificial intelligence (AI) and machine learning applications in geotechnical engineering, including machine learning algorithms for geotechnical data analysis, AI-based predictive models for soil behavior and properties, AI in geotechnical risk and decision-making, and data-driven approaches for soil classification and site characterization. The third part focuses on numerical modeling and analysis techniques, such as the Finite Element Method (FEM), Finite Difference Method (FDM), Discrete Element Method (DEM), and explores hybrid numerical methods and future directions in computational geomechanics. This book serves as a valuable resource for geotechnical engineers, researchers, and practitioners seeking to leverage advanced computational tools for geomechanical analyses and design.

  • Comprehensive Cryospheric Science and Environmental Change

    • 1st Edition
    • Richard Kelly + 1 more
    • English
    The cryosphere is where water is frozen on the Earth. It includes glaciers and ice sheets, sea ice and terrestrial snow cover, permanently and seasonally frozen ground, and frozen lakes and rivers. It is also where indigenous and non-indigenous communities reside across the high latitudes and at high altitudes. As a result of human-induced global warming, the cryosphere is shrinking in its coverage and changing in its temporal behavior, which will have profound implications for society.Comprehensiv... Cryospheric Science and Environmental Change, Four Volume Set provides a broad and comprehensive overview of the cryosphere and our understanding of its energy and mass processes. Containing approximately 80 chapters written by world-leading experts, it contextualizes the state of current cryosphere against past states over geologic time, explaining how and why the cryosphere is changing and what the implications are for the environment and society.Structured using an integrative approach, it draws together scientific understanding of the cryosphere from the perspective of fundamental physical principles, field experimentation, remote sensing observations and numerical modelling, to demonstrate how society will be impacted and respond to consequential environmental change. With the availability of sophisticated modelling tools and big data, scientific skill in modelling cryospheric systems has led to improved understanding of past cryospheric environments and increasingly skillful predictions of the future. With our evolving, yet not fully formed understanding of how society responds to environmental change, this work outlines current thinking around vulnerability, impact, adaptation and mitigation of cryosphere-induced environmental change, for example sea level rise, snow and sea ice season changes and permafrost degradation.Ideal for geoscience and earth/environmental science researchers of all levels, this one-stop reference work provides deep-level treatment of data science and the human responses to cryospheric change via a fully integrated, interdisciplinary approach.

  • Spatial Statistics and Analysis

    Techniques and Applications
    • 1st Edition
    • Anzhelika Antipova
    • English
    Spatial Statistics and Analysis: Techniques and Applications is an essential resource for anyone interested in the theory and application of spatial statistics. This comprehensive text delves into the principles, tools, and methods used in spatial analysis, making it invaluable for undergraduate and graduate students, researchers, and professionals across various fields including geography, public health, engineering, and social sciences. With hands-on exercises, the book guides readers through complex topics and ensures a deep understanding of spatial data analysis. In addition to covering key terms and tools, this valuable resource explores scales of measurement, data distributions, and spatial dataset visualizations.Other sections examine spatial statistical relationships, point and areal pattern analysis, complex spatial patterns, and geostatistical analysis. The text also addresses spatial error and uncertainty and includes practical applications of Markov chains. Supplementary resources such as instructional slides, lab activities, data sets, and graphic illustrations are provided to aid both teaching and learning.

  • Geospatial Techniques in Climate Change Monitoring and Environmental Mapping

    Advances and Applications
    • 1st Edition
    • Volume 10
    • Jung-Sup Um + 3 more
    • English
    Geospatial Techniques in Climate Change Monitoring and Environmental Mapping: Advances and Applications, Volume Ten delves into the novel methods and applications of remote sensing in climate-change studies. The book begins by exploring climate observation and monitoring, consolidating remote sensing data systems for environmental mapping, and tracking air pollution using remote sensing data. The volume covers the use of remote sensing data for monitoring and predicting climate change, characterizing land changes with climate time series data, and tracking climate change and tropical cyclones with geospatial techniques.It also discusses the system dynamics model of economic development and climate change, as well as climate change mitigation, adaptation, and future directions. Additionally, it addresses climate modeling, validation, uncertainty mapping, and the application of remote sensing data in government climate policies and sustainable risk reduction approaches for global climate change issues.Members of the Royal Meteorological Society are eligible for a 35% discount on all Developments in Weather and Climate Science series titles. See the RMetS member dashboard for the discount code.

  • Geospatial Information and Services for Climate Resilient Disaster Management

    • 1st Edition
    • Deepak Kumar + 1 more
    • English
    Geospatial Information and Services for Climate Resilient Disaster Management explores how cutting-edge technology can shape our response to climate-related disasters. Leading experts uncover the indispensable role that geospatial information and services can play in disaster preparedness, response, and recovery. The book opens with an overview of climate resilient disaster management and the application of geospatial technology. The chapters next undertake a thorough examination of early warning systems, risk assessment, vulnerability mapping, resource allocation, and disaster response. Following from those vital tools and applications, the editors then evaluate climate adaptation planning and community engagement in the light of geospatial technology.The book wraps up with real-world case studies and success stories along with a discussion of current challenges and future trends. Readers concerned with the rising connections between natural disaster and climate change will be inspired by this inside view of the latest innovations in geospatial information and services.

  • Supervised Learning in Remote Sensing and Geospatial Science

    • 1st Edition
    • Aaron E Maxwell + 2 more
    • English
    Supervised Learning in Remote Sensing and Geospatial Science is an invaluable resource focusing on practical applications of supervised learning in remote sensing and geospatial data science. Emphasizing practicality, the book delves into creating labeled datasets for training and evaluating models. It addresses common challenges like data imbalance and offers methods for assessing model performance. This guide bridges the gap between theory and practice, providing tools and techniques for extracting actionable information from raw geospatial data.The book covers all aspects of supervised learning workflows, including preparing diverse remotely sensed and geospatial data inputs. It equips researchers, practitioners, and students with essential knowledge for applied mapping and modeling tasks, making it an indispensable reference for advancing geospatial science.

  • Computational Methods for Time-Series Analyses in Earth Sciences

    • 1st Edition
    • Silvio José Gumiere + 1 more
    • English
    Computational Methods for Time-Series Analyses in Earth Sciences bridges the gap between theoretical knowledge and practical application, offering a deep dive into the utilization of R programming for managing, analyzing, and forecasting time-series data within the realm of Earth sciences. It systematically unfolds the layers of data manipulation, graphical representation, and sampling to prepare the reader for complex analyses and predictive modeling from the basics of signal processing to the nuances of machine learning. It presents cutting-edge techniques, such as neural networks, kernel-based methods, and evolutionary algorithms, specifically tailored to tackle challenges, and provides practical case studies to aid readers with utilizing the techniques covered.Computationa... Methods for Time-Series Analyses in Earth Sciences is a valuable resource for scientists, researchers, and students delving into the intricacies of Earth's environmental patterns and cycles through the lens of computational analysis and guides readers through various computational approaches to deciphering spatial and temporal data.

  • Deep Learning for Earth Observation and Climate Monitoring

    • 1st Edition
    • Uzair Aslam Bhatti + 3 more
    • English
    Deep Learning for Earth Observation and Climate Monitoring bridges the gap between deep learning and the Earth sciences, offering cutting-edge techniques and applications that are transforming our understanding of the environment. With a focus on practical scenarios, this book introduces readers to the fundamental concepts of deep learning, from classification and image segmentation to anomaly detection and domain adaptability. The book includes practical discussion on regression, parameter retrieval, forecasting, and interpolation, among other topics. With a solid foundational theory, real-world examples, and example codes, it provides a full understanding of how intelligent systems can be applied to enhance Earth observation and especially climate monitoring.This book allows readers to apply learning representations, unsupervised deep learning, and physics-aware models to Earth observation data, enabling them to leverage the power of deep learning to fully utilize the wealth of environmental data from satellite technologies.

  • Implementation and Interpretation of Machine and Deep Learning to Applied Subsurface Geological Problems

    Prediction Models Exploiting Well-Log Information
    • 1st Edition
    • David A. Wood
    • English
    Implementation and Interpretation of Machine and Deep Learning to Applied Subsurface Geological Problems: Prediction Models Exploiting Well-Log Information explores machine and deep learning models for subsurface geological prediction problems commonly encountered in applied resource evaluation and reservoir characterization tasks. The book provides insights into how the performance of ML/DL models can be optimized—and sparse datasets of input variables enhanced and/or rescaled—to improve prediction performances. A variety of topics are covered, including regression models to estimate total organic carbon from well-log data, predicting brittleness indexes in tight formation sequences, trapping mechanisms in potential sub-surface carbon storage reservoirs, and more.Each chapter includes its own introduction, summary, and nomenclature sections, along with one or more case studies focused on prediction model implementation related to its topic.

  • Deep Learning for Multi-Sensor Earth Observation

    • 1st Edition
    • Sudipan Saha
    • English
    Deep Learning for Multi-Sensor Earth Observation addresses the need for transformative Deep Learning techniques to navigate the complexity of multi-sensor data fusion. With insights drawn from the frontiers of remote sensing technology and AI advancements, it covers the potential of fusing data of varying spatial, spectral, and temporal dimensions from both active and passive sensors. This book offers a concise, yet comprehensive, resource, addressing the challenges of data integration and uncertainty quantification from foundational concepts to advanced applications. Case studies illustrate the practicality of deep learning techniques, while cutting-edge approaches such as self-supervised learning, graph neural networks, and foundation models chart a course for future development.Structur... for clarity, the book builds upon its own concepts, leading readers through introductory explanations, sensor-specific insights, and ultimately to advanced concepts and specialized applications. By bridging the gap between theory and practice, this volume equips researchers, geoscientists, and enthusiasts with the knowledge to reshape Earth observation through the dynamic lens of deep learning.

  • Data Analytics and Artificial Intelligence for Earth Resource Management

    • 1st Edition
    • Deepak Kumar + 2 more
    • English
    Data Analytics and Artificial Intelligence for Earth Resource Management offers a detailed look at the different ways data analytics and artificial intelligence can help organizations make better-informed decisions, improve operations, and minimize the negative impacts of resource extraction on the environment. The book explains several different ways data analytics and artificial intelligence can improve and support earth resource management. Predictive modeling can help organizations understand the impacts of different management decisions on earth resources, such as water availability, land use, and biodiversity.Resourc... monitoring tracks the state of earth resources in real-time, identifying issues and opportunities for improvement. Providing managers with real-time data and analytics allows them to make more informed choices. Optimizing resource management decisions help to identify the most efficient and effective ways to allocate resources. Predictive maintenance allows organizations to anticipate when equipment might fail and take action to prevent it, reducing downtime and maintenance costs. Remote sensing with image processing and analysis can be used to extract information from satellite images and other remote sensing data, providing valuable information on land use, water resources, and other earth resources.

  • Intelligence Systems for Earth, Environmental and Planetary Sciences

    Methods, Models and Applications
    • 1st Edition
    • Hossein Bonakdari + 1 more
    • English
    Intelligence Systems for Earth, Environmental and Planetary Sciences: Methods, Models and Applications provides cutting-edge theory and applications of modern-day artificial intelligence and data science in the Earth, environment, and planetary science fields. The book is divided into three sections: (i) Methods, covering the fundamentals of intelligence systems, along with an introduction to the preparation of datasets; (ii) Models, detailing model development, data assimilation, and techniques in each field; and (iii) Applications, presenting case studies of artificial intelligence and data science solutions to Earth, environmental, and planetary sciences problems, as well as future perspectives.Intelli... Systems for Earth, Environmental and Planetary Sciences will be of interest to students, academics, and postgraduate professionals in the field of applied sciences, Earth, environmental, and planetary sciences and would also serve as an excellent companion resource to courses studying artificial intelligence applications for theoretical and practical studies in Earth, environmental, and planetary sciences.

  • Machine Learning in Earth, Environmental and Planetary Sciences

    Theoretical and Practical Applications
    • 1st Edition
    • Hossein Bonakdari + 2 more
    • English
    Machine Learning in Earth, Environmental and Planetary Sciences: Theoretical and Practical Applications is a practical guide on implementing different variety of extreme learning machine algorithms to Earth and environmental data. The book provides guided examples using real-world data for numerous novel and mathematically detailed machine learning techniques that can be applied in Earth, environmental, and planetary sciences, including detailed MATLAB coding coupled with line-by-line descriptions of the advantages and limitations of each method. The book also presents common postprocessing techniques required for correct data interpretation. This book provides students, academics, and researchers with detailed understanding of how machine learning algorithms can be applied to solve real case problems, how to prepare data, and how to interpret the results.

  • Geoinformatics for Geosciences

    Advanced Geospatial Analysis using RS, GIS and Soft Computing
    • 1st Edition
    • Nikolaos Stathopoulos + 2 more
    • English
    Geoinformatics for Geosciences: Advanced Geospatial Analysis using RS, GIS and Soft Computing is a comprehensive guide to the methodologies and techniques that can be used in Earth observation data assessments, geospatial analysis, and soft computing in the geosciences. The book covers a variety of spatiotemporal problems and topics in the areas of the environment, geohazards, urban analysis, health, pollution, climate change, resources and geomorphology, among others. Sections cover environmental and climate issues, analysis of geomorphological data, hazard and disaster impacts, natural and human resources, the influence of environmental conditions, geohazards, climate change, geomorphological changes, etc., and socioeconomic challenges. Detailing up-to-date techniques in geoinformatics, this book offers in-depth, up-to-date methodologies for researchers and academics to understand how contemporary data can be combined with innovative techniques and tools in order to address challenges in the geosciences.

  • Case Studies in Geospatial Applications to Groundwater Resources

    • 1st Edition
    • Pravat Kumar Shit + 2 more
    • English
    Case Studies in Geospatial Applications to Groundwater Resources provides thorough the most up-to-date techniques in GIS and geostatistics as they relate to groundwater, through detailed case studies that prove real-world applications of remote sensing applications to this subject. Groundwater is the primary source of fresh water in many parts of the world, while come regions are becoming overly dependent on it, consuming groundwater faster than it is naturally replenished and causing water tables to decline unremittingly. India is the largest user of groundwater in the world followed by China and the USA, with developing countries using groundwater at an unsustainable rate. Systematic planning of groundwater usage using modern techniques is essential for the proper utilization, management and modeling of this precious but shrinking natural resource. With the advent of powerful and highspeed personal computers, efficient techniques for water management have evolved, of which remote sensing, GIS (Geographic Information Systems), GPS (Global Positioning Systems) and Geostatistical techniques are of great significance. This book advances the scientific understanding, development, and application of geospatial technologies related to water resource management. Case Studies in Geospatial Applications to Groundwater Resources is a valuable reference for researchers and postgraduate students in Earth and Environmental Sciences, especially GIS, agriculture, hydrology, natural resources, and soil science, who need to be able to apply the latest technologies in groundwater research in a practical manner.

  • Advances in Subsurface Data Analytics

    • 1st Edition
    • Shuvajit Bhattacharya + 1 more
    • English
    Advances in Subsurface Data Analytics: Traditional and Physics-Based Approaches brings together the fundamentals of popular and emerging machine learning (ML) algorithms with their applications in subsurface analysis, including geology, geophysics, petrophysics, and reservoir engineering. The book is divided into four parts: traditional ML, deep learning, physics-based ML, and new directions, with an increasing level of diversity and complexity of topics. Each chapter focuses on one ML algorithm with a detailed workflow for a specific application in geosciences. Some chapters also compare the results from an algorithm with others to better equip the readers with different strategies to implement automated workflows for subsurface analysis. Advances in Subsurface Data Analytics: Traditional and Physics-Based Approaches will help researchers in academia and professional geoscientists working on the subsurface-related problems (oil and gas, geothermal, carbon sequestration, and seismology) at different scales to understand and appreciate current trends in ML approaches, their applications, advances and limitations, and future potential in geosciences by bringing together several contributions in a single volume.

  • Knowledge Discovery in Big Data from Astronomy and Earth Observation

    Astrogeoinformatics
    • 1st Edition
    • Petr Skoda + 1 more
    • English
    Knowledge Discovery in Big Data from Astronomy and Earth Observation: Astrogeoinformatics bridges the gap between astronomy and geoscience in the context of applications, techniques and key principles of big data. Machine learning and parallel computing are increasingly becoming cross-disciplinary as the phenomena of Big Data is becoming common place. This book provides insight into the common workflows and data science tools used for big data in astronomy and geoscience. After establishing similarity in data gathering, pre-processing and handling, the data science aspects are illustrated in the context of both fields. Software, hardware and algorithms of big data are addressed. Finally, the book offers insight into the emerging science which combines data and expertise from both fields in studying the effect of cosmos on the earth and its inhabitants.

  • Adjustment Models in 3D Geomatics and Computational Geophysics

    With MATLAB Examples
    • 1st Edition
    • Volume 4
    • Bashar Alsadik
    • English
    Adjustment Models in 3D Geomatics and Computational Geophysics: With MATLAB Examples, Volume Four introduces a complete package of theoretical and practical subjects in adjustment computations relating to Geomatics and geophysical applications, particularly photogrammetry, surveying, remote sensing, GIS, cartography, and geodesy. Supported by illustrating figures and solved examples with MATLAB codes, the book provides clear methods for processing 3D data for accurate and reliable results. Problems cover free net adjustment, adjustment with constraints, blunder detection, RANSAC, robust estimation, error propagation, 3D co-registration, image pose determination, and more.

  • Mineral Resources and Energy

    Future Stakes in Energy Transition
    • 1st Edition
    • Olivier Vidal
    • English
    Our consumption of raw materials and energy has reached unprecedented levels which are continuing to increase at a steady rate due to the economic emergence of many countries and the development of new technologies. Metal and cement usage has doubled since the beginning of the 21st Century and this production, between now and 2050, will be equivalent to that produced since the beginning of humanity. It is in this context that the transition to low-carbon and renewable energies is taking place, which involves profound changes to the existing global energy system. This book addresses these different aspects and attempts to estimate first-order requirements for cement, steel, copper, aluminum and energy for different power generation technologies, and for three types of energy scenarios. Some dynamic modeling approaches are proposed to assess the needs and likely evolution of primary production and recycling. The link between production and primary reserves, recycling and stocks of end-of-life products, production costs, incomes and prices using a prey–predator dynamic is discussed.

  • Geotechnical Engineering Calculations and Rules of Thumb

    • 2nd Edition
    • Ruwan Abey Rajapakse
    • English
    Geotechnical Engineering Calculations and Rules of Thumb, Second Edition, offers geotechnical, civil and structural engineers a concise, easy-to-understand approach to selecting the right formula and solving even most difficult calculations in geotechnical engineering. A "quick look up guide", this book places formulas and calculations at the reader’s finger tips. In this book, theories are explained in a "nutshell" and then the calculation is presented and solved in an illustrated, step-by-step fashion.In its first part, the book covers the fundamentals of Geotechnical Engineering: Soil investigation, condition and theoretical concepts. In the second part it addresses Shallow Foundations, including bearing capacity, elastic settlement, foundation reinforcement, grillage design, footings, geogrids, tie and grade beams, and drainage. This session ends with a chapter on selecting foundation types. The next part covers Earth Retaining Structures and contains chapters on its basic concepts and types, gabion walls and reinforced earth walls. The following part covers Geotechnical Engineering Strategies providing coverage of softwares, instrumentation, excavations, raft design, rock mechanics, dip angle and strike, rock stabilization equipment, soil anchors, tunnel design, seismology, geosynthetics, and slurry cutoff walls. The final part is on Pile Foundations including content on design on sandy soils, clay soils, pin piles, negative skin friction, caissons and pile clusters.In this new and updated edition the author has incorporated new software calculation tools, current techniques for foundation design, liquefaction information, seismic studies, laboratory soil tests, geophysical techniques, new concepts for foundation design and Dam designs. All calculations have been updated to most current material characteristics available in the market.Practicing Geotechnical, Civil and Structural Engineers may find in this book an excellent companion to their day-to day work, benefiting from the clear and direct calculations, examples, and cases. Civil Engineering students may find particular interest in the concise theory presented in the beginning of each chapter.

  • Principles of Electromagnetic Methods in Surface Geophysics

    • 1st Edition
    • Volume 45
    • Alex Kaufman + 2 more
    • English
    Principles of Electromagnetic Methods in Surface Geophysics contains information about the theory of electromagnetic fields in a conducting media. It describes the theoretical and physical principles of the main geophysical methods using electromagnetic fields, including frequency and transient soundings, electromagnetic profiling, and magnetotelluric soundings. Special attention is paid to models and signal processing methods used in modern exploration geophysics for groundwater, mineral and hydrocarbon exploration.

  • Geographic Information Systems for Geoscientists

    Modelling with GIS
    • 1st Edition
    • Volume 13
    • G.F. Bonham-Carter
    • Daniel F Merriam
    • English
    Geographic Information Systems for Geoscientists is unique in its coverage of examples from the geological sciences, many centred on applications to mineral exploration. The underlying principles of GIS are stressed and emphasis placed on the analysis and modelling of spatial data with applications to site selection and potential mapping. The book commences with a definition of GIS and describes a case study of mapping mineral potential. The ways in which spatial data are organized with models (raster, vector, relational) are discussed and data structures, such as quadtrees and topological structures are introduced. Data input including digitizing, geographic projections and conversions is covered together with output (visualization, representation of colour and spatial query). Spatial data transformations are dealt with thoroughly and attention is paid to map analysis and modelling as related to single maps, map pairs and multiple maps respectively. Methods of quantifying the associations between pairs of maps are emphasized. Finally, examples of landfill site selection and mineral potential mapping illustrate the application of map algebra for combining maps and tables with models, employing Boolean logic, index weighting, fuzzy logic and probability methods such as weights of evidence. There is an extensive glossary of terms, and references accompany each chapter. Contains 40 pages of colour illustrations.

  • Simulating Nearshore Environments

    • 1st Edition
    • Volume 12
    • P.A. Martinez + 1 more
    • Daniel F Merriam
    • English
    Simulating Nearshore Environments provides computer procedures that realistically represent nearshore processes and supplement or replace trial and error methodology. The procedures simulate transport by waves and fluvial processes on beaches and deltas at various scales. They will aid coastal engineers, oceanographers and sedimentary geologists who focus on both modern and ancient nearshore deposits.How do you simulate nearshore processes using a computer? Can evolving deltaic and coastal environments be simulated realistically by mathematically representing the physical processes that create them? Once the physics and mathematical formulation are described, what are the techniques for transforming them into computer programs? The authors deal with all these aspects and take a "how to" approach in guiding the reader through the development of computer models for simulating sediment transport in coastal environments. In addition to describing the devised computer programs, the book provides a basis for those wishing to formulate their own mathematical models for simulating nearshore processes.

  • Geochemical Anomaly and Mineral Prospectivity Mapping in GIS

    • 1st Edition
    • Volume 11
    • E.J.M. Carranza
    • English
    Geochemical Anomaly and Mineral Prospectivity Mapping in GIS documents and explains, in three parts, geochemical anomaly and mineral prospectivity mapping by using a geographic information system (GIS). Part I reviews and couples the concepts of (a) mapping geochemical anomalies and mineral prospectivity and (b) spatial data models, management and operations in a GIS. Part II demonstrates GIS-aided and GIS-based techniques for analysis of robust thresholds in mapping of geochemical anomalies. Part III explains GIS-aided and GIS-based techniques for spatial data analysis and geo-information sybthesis for conceptual and predictive modeling of mineral prospectivity. Because methods of geochemical anomaly mapping and mineral potential mapping are highly specialized yet diverse, the book explains only methods in which GIS plays an important role. The book avoids using language and functional organization of particular commercial GIS software, but explains, where necessary, GIS functionality and spatial data structures appropriate to problems in geochemical anomaly mapping and mineral potential mapping. Because GIS-based methods of spatial data analysis and spatial data integration are quantitative, which can be complicated to non-numerate readers, the book simplifies explanations of mathematical concepts and their applications so that the methods demonstrated would be useful to professional geoscientists, to mineral explorationists and to research students in fields that involve analysis and integration of maps or spatial datasets. The book provides adequate illustrations for more thorough explanation of the various concepts.

  • Electromagnetic Sounding of the Earth's Interior

    • 1st Edition
    • Volume 40
    • Viacheslav V. Spichak
    • Viacheslav V. Spichak
    • English
    Based on lectures given in the First Russian School-Seminar on electromagnetic soundings of the Earth held in Moscow on 15th November, 2003, this book acquaints scientists and technologists with the latest achievements in theory, techniques and practical applications of the methods of electromagnetic sounding. This three part text covers the methods considered for Earth electromagnetic sounding on a global, regional, and local scale; modern methods for solving forward and inverse problems of geoelectrics, particularily contemporary approaches to the EM data modeling and interpretation in the class of three-dimensional models; and the results of regional EM on-land and sea soundings

  • Soft Computing and Intelligent Data Analysis in Oil Exploration

    • 1st Edition
    • Volume 51
    • M. Nikravesh + 2 more
    • English
    This comprehensive book highlights soft computing and geostatistics applications in hydrocarbon exploration and production, combining practical and theoretical aspects.It spans a wide spectrum of applications in the oil industry, crossing many discipline boundaries such as geophysics, geology, petrophysics and reservoir engineering. It is complemented by several tutorial chapters on fuzzy logic, neural networks and genetic algorithms and geostatistics to introduce these concepts to the uninitiated. The application areas include prediction of reservoir properties (porosity, sand thickness, lithology, fluid), seismic processing, seismic and bio stratigraphy, time lapse seismic and core analysis.There is a good balance between introducing soft computing and geostatistics methodologies that are not routinely used in the petroleum industry and various applications areas. The book can be used by many practitioners such as processing geophysicists, seismic interpreters, geologists, reservoir engineers, petrophysicist, geostatistians, asset mangers and technology application professionals. It will also be of interest to academics to assess the importance of, and contribute to, R&D efforts in relevant areas.

  • Geoscience After IT

    A View of the Present and Future Impact of Information Technology on Geoscience
    • 1st Edition
    • Volume 17
    • T.V. Loudon
    • English
    Most geoscientists are aware of recent IT developments, but cannot spend time on obscure technicalities. Few have considered their implications for the science as a whole. Yet the information industry is moving fast: electronic delivery of hyperlinked multimedia; standards to support interdisciplinary and geographic integration; new models to represent and visualize our concepts, and control and manage our activities; plummeting costs that force the pace. To stay on course, the scientist needs a broad appreciation of the complex and profound interactions of geoscience and IT, not previously reviewed in a single work.The book brings together ideas from many sources, some probably unfamiliar, that bear on the geoscience information system. It encourages readers to give thought to areas that, for various reasons, they have taken for granted, and to take a view on forces affecting geoscience, the consequences for themselves and their organisations, and the need to reconsider, adapt and rebuild.Practicing geoscientists with a general interest in how IT will affect their work and influence future directions of the science; geoscientists familiar with IT applications in their own specialist field who need a broader perspective; and students or educators specializing in IT applications in geoscience who require a top-down overview of their subject will find this title valuable. The IT background from this book should help geoscientists build a strategy for the new century.

  • Structural Geology and Personal Computers

    • 1st Edition
    • Volume 15
    • D.G. De Paor
    • English
    This book will help structural geologists keep abreast of rapid changes in work practices resulting from the personal computer revolution. It is organized into six parts: I Computer-Aided Learning; II Microstructural Analysis; III Analysis of Orientation Data; IV Strain and Kinematic Analysis; V Mathematical and Physical Modeling; VI Structural Mapping and GIS. The 45 contributing authors explain how to: set up computer-aided teaching and learning facilities on a low budget; illustrate tectonic strain concepts with a drawing program; integrate multimedia presentations into structural coursework; analyze microstructures with computer-aided microscopy; produce sophisticated stereonets with custom software for both the Mac and IBM PC; evaluate orientation data using a spreadsheet program; model the development of macrostructures and microstructures numerically; integrate structural and geophysical data; and apply PC technology to the production of structural maps, cross sections, and block diagrams. The editor's own contributions reveal the inner workings of his renowned structural research applications which are used in hundreds of universities worldwide. Commercial and non-commercial applications of particular interest to structural geologists are reviewed.This volume will prove an invaluable resource for professors, instructors, and research students, as well as research scientists in the public services and exploration industries. If you are such a person, have you lectured with the aid of a gyroscopic mouse? Or used Bézier curves to model heterogeneous deformation? Or analyzed a fold structure using a digital terrain model? If not, you'll need to rush out and buy this book before the next wave of new technology hits!