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Allen Philip A.: Basin Analysis

Basin Analysis

Journeys to the Polar Regions in Search of Life, the Cosmos, and our Future

Ends of the Earth

Earth Observation

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. Structured 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 Multi-Sensor Earth Observation

Energy and Environment

An Introduction

Environmental Management

When ecologist Carl Safina and his wife, Patricia, took in a near-death baby owl, they expected that, like other wild orphans they'd rescued, she'd be a temporary presence. But Alfie's feathers were not growing correctly, requiring prolonged care. As Alfie grew and gained strength, she became a part of the family, joining a menagerie of dogs and chickens and making a home for herself in the backyard. Carl and Patricia began to realise that the healing was mutual; Alfie had been braided into their world and was now pulling them into hers.
Alfie &amp; Me is the story of the remarkable impact this little owl would have on their lives. The continuing bond of trust following her freedom-and her raising of her own wild brood-coincided with the onset of the COVID-19 pandemic, a year in which Carl and Patricia were forced to spend time at home without the normal obligations of work and travel. Witnessing all the fine details of their feathered friend's life offered Carl and Patricia a view of existence from Alfie's perspective.
One can travel the world and go nowhere; one can be stuck keeping the faith at home and discover a new world. Safina's relationship with an owl made him want to better understand how people have viewed humanity's relationship with nature across cultures and throughout history. Interwoven with Safina's keen observations, insight and reflections, Alfie &amp; Me is a work of profound beauties and magical timing harboured within one upended year.

What Owls Know, What Humans Believe

Alfie and Me

The deep sea is one of humanity's last frontiers. For most of our history it has been a remote realm, invoking awe and terror as it lays shrouded in darkness. But here, where the light cannot reach, lies a strange, wonderful and breath-taking portal into Earth's past, teeming with scientific marvels and lessons for the future of life on this planet. In The Dark Frontier, marine microbiologist and expert deep-sea explorer Jeffrey Marlow plunges us into the unreachable realm and invites us into close-up encounters with its hidden brilliance. There are translucent shrimp that dance through sulfurous vents, crabs that stretch twelve feet from claw to claw and the eerie chalk-white towers of the 'Lost City'. Immersive and illuminating, Marlow's journeys heed warnings too: our reach is exceeding our grasp. We are irrevocably changing the deep sea before we even know it. This expansive book offers crucial and surprising insights into the birthplace of life on ancient Earth. It shows how life can thrive in even the most extreme conditions and expands our understanding of possibilities - and our responsibilities - on earth and beyond.

Unlocking the Secrets of the Deep Sea

The Dark Frontier

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.

Algorithms and Applications

Multimodal Remote Sensing Fusion and Classification

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.

Prediction Models Exploiting Well-Log Information

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

Mining has evolved in the 21st century into an indispensable industry that provides a variety of mineral products needed to sustain a modern society. To achieve efficiency, it has also grown into an integrated enterprise of enormous size, wielding substantial economic power. Tailings is essentially a fine-particle mine-waste byproduct. Its management has gone through major transformations in the last century. In early years tailings was disposed of out of sight and literally out of mind. However, due to the physical and chemical characteristics of tailings, this laissez-faire approach in dealing with its disposal led to significant environmental degradation such as pollution and blockage of watercourses, etc. With the rising environmental protection movement, the mining operation is under increasing regulatory constraints and governmental monitoring. Modern tailings dams have become major hydraulic structures designed, constructed, and monitored until they are properly closed and reclaimed after the completion of mining tenure. These dams are often higher than 100 m, with a storage capacity of over hundreds of million cubic metres, serving a vital industrial function for the public. Unfortunately, when such a dam fails, it unleashes tremendous destructive power causing inundation of water and tailings mud over the downstream area resulting in fatalities, loss of property and infrastructure, and lasting environmental degradation. This book presents a condensed monograph on forensic investigations of select case histories of failed tailings dams. The selection tends to emphasize recent cases that have representative characteristics including those affecting the evolution of the current practice of tailings dam engineering. Efforts are made to facilitate readers’ understanding of important factors involved by using plain language. Technical terms are clearly explained before their usage. The objective of the monograph is to provide a neutral reference on tailings dam failure.The author hopes ongoing dialogues by all stakeholders on the important topics of dam safety will raise the safety standard of tailings dams to a new level compatible with public expectations of the sustainable mining industry.&nbsp; &nbsp; &nbsp;&nbsp;

Socio-Economic-Environmental Impacts

Tailings Dam Failure

Remote Sensing

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.

Exploring Applications with Geospatial Insights

Remote Sensing, Big Data, and GeoAI

Advances in Geophysical and Environmental Mechanics and Mathematics

A thematic introduction to the modern theory of continuum mechanics and thermodynamics is presented from the viewpoint of granular and porous materials. In the approach taken here, granular and porous media are treated as continuous macroscopic systems of which the overall response is significantly influenced and determined by microstructural effects. In the continuum mechanical modeling, those microscale effects are captured by the introduction of so-called internal variables which account for geometric and material inhomogeneities or the multiphase nature of granular mixtures. Describing the evolution of such internal variables by additional balance laws, the resulting continuum-thermodynamical system requires careful analysis, including, e.g. the application of the entropy principle of Müller with the corresponding approach of exploitation as suggested by Liu. The book is self-contained and addresses an interdisciplinary audience including civil and geotechnical engineers, physicists, applied mathematicians, soil mechanicians and continuum mechanicians.

A thematic introduction to the modern theory of continuum mechanics and thermodynamics is presented from the viewpoint of granular and porous materials. In the approach taken here, granular and porous media are treated as continuous macroscopic systems of which the overall response is significantly influenced and determined by microstructural effects. In the continuum mechanical modeling, those microscale effects are captured by the introduction of so-called internal variables which account for geometric and material inhomogeneities or the multiphase nature of granular mixtures. Describing the evolution of such internal variables by additional balance laws, the resulting continuum-thermodynamical system requires careful analysis, including, e.g. the application of the entropy principle of Müller with the corresponding approach of exploitation as suggested by Liu. The book is self-contained and addresses an interdisciplinary audience including civil and geotechnical engineers, physicists, applied mathematicians, soil mechanicians and continuum mechanicians.

Continuum Description of Granular Materials

Sustainable Computing and Optimization

Multi-Criteria Decision Making for Risk Assessment of Emerging Environmental Contaminants

Basin Analysis

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Schlagworte

Bibliografische Angaben

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