Earth Systems Data and Models – serie

This book offers extensive information on the operation of gravimeters, including airborne, marine and terrestrial ones, and on the associated data processing methods such as optimal and adaptive filtering, smoothing, structural and parametric identification.

This book offers extensive information on the operation of gravimeters, including airborne, marine and terrestrial ones, and on the associated data processing methods such as optimal and adaptive filtering, smoothing, structural and parametric identification.

The book aims to enhance understanding of landslides by focusing on detection, prediction, and monitoring. Recently, the number of significant landslides and the damage they cause has increased globally. Landslides are among the most devastating natural hazards, resulting in widespread damage to habitats on local, regional, and global scales. Experts from around the world have shared their experiences in landslide research and practice, which may help stakeholders mitigate and predict these events. The book comprises chapters on✔       Dynamics, mechanisms, and processes of landslides.✔       Mapping and assessment of hazard, vulnerability, and risk associated with landslides.✔       Geological, geotechnical, hydrological, and geophysical modelling for landslides.✔       Numerical simulation of slope to analyse their stability.✔       Monitoring and early warning of landslides.✔       Application of remote sensing and GIS techniques in monitoring and assessment of landslides.The book is very much helpful for researchers, practitioners, and decision-makers to adapt suitable modern techniques for landslide study.

The book aims to enhance understanding of landslides by focusing on detection, prediction, and monitoring. Recently, the number of significant landslides and the damage they cause has increased globally. Landslides are among the most devastating natural hazards, resulting in widespread damage to habitats on local, regional, and global scales. Experts from around the world have shared their experiences in landslide research and practice, which may help stakeholders mitigate and predict these events. The book comprises chapters on✔       Dynamics, mechanisms, and processes of landslides.✔       Mapping and assessment of hazard, vulnerability, and risk associated with landslides.✔       Geological, geotechnical, hydrological, and geophysical modelling for landslides.✔       Numerical simulation of slope to analyse their stability.✔       Monitoring and early warning of landslides.✔       Application of remote sensing and GIS techniques in monitoring and assessment of landslides.The book is very much helpful for researchers, practitioners, and decision-makers to adapt suitable modern techniques for landslide study.

This book aims to provide a comprehensive understanding of tensor computation and its applications in seismic data analysis, exclusively catering to seasoned researchers, graduate students, and industrial engineers alike. Tensor emerges as a natural representation of multi-dimensional modern seismic data, and tensor computation can help prevent possible harm to the multi-dimensional geological structure of the subsurface that occurred in classical seismic data analysis.It delivers a wealth of theoretical, computational, technical, and experimental details, presenting an engineer's perspective on tensor computation and an extensive investigation of tensor-based seismic data analysis techniques. Embark on a transformative exploration of seismic data processing—unlock the potential of tensor computation and reshape your approach to high-dimensional geological structures.The discussion begins with foundational chapters, providing a solid background in both seismic data processing and tensor computation. The heart of the book lies in its seven chapters on tensor-based seismic data analysis methods. From structured low-tubal-rank tensor completion to cutting-edge techniques like tensor deep learning and tensor convolutional neural networks, each method is meticulously detailed. The superiority of tensor-based data analysis methods over traditional matrix-based data analysis approaches is substantiated through synthetic and real field examples, showcasing their prowess in handling high-dimensional modern seismic data. Notable chapters delve into seismic noise suppression, seismic data interpolation, and seismic data super-resolution using advanced tensor models. The final chapter provides a cohesive summary of the conclusion and future research directions, ensuring readers facilitate a thorough understanding of tensor computation applications in seismic data processing. The appendix includes a hatful of information on existing tensor computation software, enhancing the book's practical utility.

This book aims to provide a comprehensive understanding of tensor computation and its applications in seismic data analysis, exclusively catering to seasoned researchers, graduate students, and industrial engineers alike. Tensor emerges as a natural representation of multi-dimensional modern seismic data, and tensor computation can help prevent possible harm to the multi-dimensional geological structure of the subsurface that occurred in classical seismic data analysis.It delivers a wealth of theoretical, computational, technical, and experimental details, presenting an engineer's perspective on tensor computation and an extensive investigation of tensor-based seismic data analysis techniques. Embark on a transformative exploration of seismic data processing—unlock the potential of tensor computation and reshape your approach to high-dimensional geological structures.The discussion begins with foundational chapters, providing a solid background in both seismic data processing and tensor computation. The heart of the book lies in its seven chapters on tensor-based seismic data analysis methods. From structured low-tubal-rank tensor completion to cutting-edge techniques like tensor deep learning and tensor convolutional neural networks, each method is meticulously detailed. The superiority of tensor-based data analysis methods over traditional matrix-based data analysis approaches is substantiated through synthetic and real field examples, showcasing their prowess in handling high-dimensional modern seismic data. Notable chapters delve into seismic noise suppression, seismic data interpolation, and seismic data super-resolution using advanced tensor models. The final chapter provides a cohesive summary of the conclusion and future research directions, ensuring readers facilitate a thorough understanding of tensor computation applications in seismic data processing. The appendix includes a hatful of information on existing tensor computation software, enhancing the book's practical utility.

This book looks into the Direct Current Resistivity Method and Induced Polarization (IP) techniques, essential for geophysical exploration. Covering both theoretical foundations and practical applications, it explores subsurface imaging, inversion modeling, and real-world case studies in mineral exploration, groundwater detection, and environmental studies. With depth discussions on electrode configurations, resistivity sounding, self-potential methods, and mathematical modeling, this book serves as a valuable resource for geophysicists, researchers, and professionals seeking advanced insights into electrical geophysics.

Advances in Engineering Geophysics: Concepts and Applications is a high-standard postgraduate textbook that unifies core geological principles with advanced geophysical methods for engineering applications. Spanning diverse themes – such as subsurface characterization, environmental monitoring, disaster risk reduction, infrastructure resilience, defense installations, archaeological investigations, and sustainability – it addresses the growing global demand for reliable, multidisciplinary geoscience solutions. Authored by international experts, this contributed volume blends foundational theory with state-of-the-art techniques and emerging innovations. Rich with case studies, illustrations, and cross-disciplinary insights, the book is an essential reference for researchers, engineering professionals, postgraduate students, and educators worldwide. It is especially valuable for institutions, universities, and technical organizations committed to infrastructure safety, sustainable development, and climate-resilient engineering.

This book focuses on the use of open source software for geospatial analysis. It demonstrates the effectiveness of the command line interface for handling both vector, raster and 3D geospatial data. Appropriate open-source tools for data processing are clearly explained and discusses how they can be used to solve everyday tasks.A series of fully worked case studies are presented including vector spatial analysis, remote sensing data analysis, landcover classification and LiDAR processing. A hands-on introduction to the application programming interface (API) of GDAL/OGR in Python/C++ is provided for readers who want to extend existing tools and/or develop their own software.

This book explores a new realm in data-based modeling with applications to hydrology. Pursuing a case study approach, it presents a rigorous evaluation of state-of-the-art input selection methods on the basis of detailed and comprehensive experimentation and comparative studies that employ emerging hybrid techniques for modeling and analysis.

This book focuses on the use of open source software for geospatial analysis. It demonstrates the effectiveness of the command line interface for handling both vector, raster and 3D geospatial data. Appropriate open-source tools for data processing are clearly explained and discusses how they can be used to solve everyday tasks.A series of fully worked case studies are presented including vector spatial analysis, remote sensing data analysis, landcover classification and LiDAR processing. A hands-on introduction to the application programming interface (API) of GDAL/OGR in Python/C++ is provided for readers who want to extend existing tools and/or develop their own software.

This book explores a new realm in data-based modeling with applications to hydrology. Pursuing a case study approach, it presents a rigorous evaluation of state-of-the-art input selection methods on the basis of detailed and comprehensive experimentation and comparative studies that employ emerging hybrid techniques for modeling and analysis. Advanced computing offers a range of new options for hydrologic modeling with the help of mathematical and data-based approaches like wavelets, neural networks, fuzzy logic, and support vector machines. Recently machine learning/artificial intelligence techniques have come to be used for time series modeling. However, though initial studies have shown this approach to be effective, there are still concerns about their accuracy and ability to make predictions on a selected input space.

This book, written by an international team of prominent authors, gathers the latest developments in mobile technologies for the acquisition, management, analysis and sharing of Volunteered Geographic Information (VGI) in the context of Earth observation.  It is divided into three parts, the first of which presents case studies on the implementation of VGI for Earth observation, discusses the characteristics of volunteers’ engagement in relation with their expertise and motivation, analyzes the tasks they are called upon to perform, and examines the available tools for developing VGI. In turn, the second part introduces readers to essential methods, techniques and algorithms used to develop mobile information systems based on VGI for distinct Earth observation tasks, while the last part focuses on the drawbacks and limitations of VGI with regard to the above-mentioned tasks and proposes innovative methods and techniques to help overcome them. Given its breadth of coverage, the bookoffers a comprehensive, practice-oriented reference guide for researchers and practitioners in the field of geo-information management.

This book, written by an international team of prominent authors, gathers the latest developments in mobile technologies for the acquisition, management, analysis and sharing of Volunteered Geographic Information (VGI) in the context of Earth observation.  It is divided into three parts, the first of which presents case studies on the implementation of VGI for Earth observation, discusses the characteristics of volunteers’ engagement in relation with their expertise and motivation, analyzes the tasks they are called upon to perform, and examines the available tools for developing VGI. In turn, the second part introduces readers to essential methods, techniques and algorithms used to develop mobile information systems based on VGI for distinct Earth observation tasks, while the last part focuses on the drawbacks and limitations of VGI with regard to the above-mentioned tasks and proposes innovative methods and techniques to help overcome them. Given its breadth of coverage, the bookoffers a comprehensive, practice-oriented reference guide for researchers and practitioners in the field of geo-information management.

This book demystifies the models we use to simulate present and future climates, allowing readers to better understand how to use climate model results.