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Books in Computers in geosciences

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    • The Geoinformatics Frontier

      • 1st Edition
      • January 1, 2026
      • Kleomenis Kalogeropoulos + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 1 5 7 4 9
      • eBook
        9 7 8 0 4 4 3 3 1 5 7 5 6
      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.

    • Multimodal Remote Sensing Fusion and Classification

      • 1st Edition
      • March 1, 2026
      • Man-On Pun + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 9 1 5 2 4
      • eBook
        9 7 8 0 4 4 3 2 9 1 5 3 1
      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.

    • Comprehensive Cryospheric Science and Environmental Change

      • 1st Edition
      • February 2, 2026
      • Richard Kelly + 1 more
      • English
      • Hardback
        9 7 8 0 3 2 3 8 5 2 4 2 5
      • eBook
        9 7 8 0 3 2 3 8 5 8 9 3 9
      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.

    • Remote Sensing, Big Data, and GeoAI

      • 1st Edition
      • March 1, 2026
      • Erin Bunting + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 6 7 4 1 3
      • eBook
        9 7 8 0 4 4 3 2 6 7 4 2 0
      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
      • November 1, 2025
      • Shunlin Liang + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 1 4 8 5 1
      • eBook
        9 7 8 0 4 4 3 2 1 4 9 7 4
      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.

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

      • 1st Edition
      • February 18, 2025
      • David A. Wood
      • English
      • Paperback
        9 7 8 0 4 4 3 2 6 5 1 0 5
      • eBook
        9 7 8 0 4 4 3 2 6 5 1 1 2
      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
      • February 1, 2025
      • Sudipan Saha
      • English
      • Paperback
        9 7 8 0 4 4 3 2 6 4 8 4 9
      • eBook
        9 7 8 0 4 4 3 2 6 4 8 5 6
      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.

    • Deep Learning for Earth Observation and Climate Monitoring

      • 1st Edition
      • March 19, 2025
      • Uzair Aslam Bhatti + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 4 7 1 2 5
      • eBook
        9 7 8 0 4 4 3 2 4 7 1 3 2
      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.

    • Supervised Learning in Remote Sensing and Geospatial Science

      • 1st Edition
      • October 1, 2025
      • Aaron E Maxwell + 2 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 9 3 0 6 1
      • eBook
        9 7 8 0 4 4 3 2 9 3 0 7 8
      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.

    • Spatial Statistics and Analysis

      • 1st Edition
      • November 1, 2025
      • Anzhelika Antipova
      • English
      • Paperback
        9 7 8 0 4 4 3 2 4 8 0 0 9
      • eBook
        9 7 8 0 4 4 3 2 4 8 0 1 6
      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.