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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.

  • 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. 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. Advancing science and future directions in landslide research are explored, including trends in landslide occurrence, early warning systems, technological innovations, and remaining challenging issues in landslide science. This comprehensive guide offers valuable insights and strategies for understanding, assessing, and managing landslides for a more resilient future.

  • 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. The book begins by addressing the quality aspects of EO data, emphasizing the importance of reliable and accurate information for meaningful analysis. It reviews the interaction and integration of various EO datasets, highlighting the necessity of combining diverse data sources to enhance analytical outcomes. The text covers essential techniques such as downsampling, generalization, and upsampling, 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 data consistency across multidimensional datasets. This harmonization 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 spatial analysis capabilities. It presents comprehensive workflows and tools that facilitate advanced spatial analysis, equipping researchers and practitioners with the necessary resources to harness EO data effectively. The book serves as a valuable resource to emphasize the importance of high-quality, integrated datasets in fostering informed decision-making and advancing research in environmental monitoring, urban planning, and resource management.

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.