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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.

  • 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.

  • 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.

  • 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.

  • 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 authors' provide valuable insights for geotechnical engineers and researchers seeking to leverage advanced computational tools for enhanced geotechnical assessments and design processes.

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.