Books in Computers in geosciences

Comprehensive Cryospheric Science and Environmental Change

1st Edition
February 2, 2026
Richard Kelly + 1 more
English
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.

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.

Deep Learning for Synthetic Aperture Radar Remote Sensing

1st Edition
January 1, 2026
Michael Schmitt + 1 more
English
Paperback
9 7 8 0 4 4 3 3 6 3 4 4 3
eBook
9 7 8 0 4 4 3 3 6 3 4 5 0

Deep Learning for Synthetic Aperture Radar Remote Sensing delves into the transformative synergy between synthetic aperture radar (SAR) and cutting-edge machine learning techniques. Traditionally rooted in signal processing, SAR's active imaging capabilities rise above optical limitations, offering resilience to environmental factors like cloud cover. This book showcases how machine learning augments every stage of SAR image processing, from raw data refinement to advanced information extraction. Through comprehensive coverage of acquisition modes and processing methodologies, including polarimetry and interferometry, this book equips readers with the tools to harness SAR's full potential. Aiming to further enhance remote sensing imaging, it serves as a vital resource for those seeking to integrate SAR data seamlessly into the modern machine learning landscape. Deep Learning for Synthetic Aperture Radar Remote Sensing addresses a critical gap in the intersection of SAR technology and machine learning, offering a pioneering roadmap for researchers and practitioners alike. With its emphasis on modern techniques, it serves as a catalyst for unlocking SAR's untapped potential and shaping the future of Earth observation.

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.

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.

Geospatial Techniques in Climate Change Monitoring and Environmental Mapping

1st Edition
Volume 10
November 1, 2025
Jung-Sup Um + 3 more
English
Paperback
9 7 8 0 4 4 3 3 6 3 9 6 2
eBook
9 7 8 0 4 4 3 3 6 3 9 7 9

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.

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.

Geospatial Information and Services for Climate Resilient Disaster Management

1st Edition
September 1, 2025
Deepak Kumar + 1 more
English
Paperback
9 7 8 0 4 4 3 2 9 2 1 6 3
eBook
9 7 8 0 4 4 3 2 9 2 1 7 0

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.

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.

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.

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