Books in Earth surface processes

Erosion, Deposition, and Weathering Across the Solar System

1st Edition
Volume 4
October 1, 2025
Jani Radebaugh + 1 more
English
Paperback
9 7 8 0 4 4 3 1 4 0 2 0 4
eBook
9 7 8 0 4 4 3 1 4 0 2 1 1

Erosion, Deposition, and Weathering Across the Solar System, Volume Four summarizes erosional landforms across the Solar System, with an emphasis on the mechanistic processes responsible for these features, including case studies and methods of data and image analysis. Using comparative studies of planetary bodies and various Earth locations as natural laboratories to test models of erosive processes and landscape evolution, the book provides a current review of understanding of the evolution of planetary surfaces for Earth and those of our Solar System.Planetary surfaces images across the Solar System reveal the ubiquity of erosional processes on planets, moons, and other bodies. From branching valley networks on Mars to hydrocarbon rivers on Titan to nitrogen glaciers on Pluto, landforms across the Solar System are conspicuously similar to features that we are familiar with on Earth. This familiarity suggests similar erosional processes are occurring across the Solar System despite drastically different surface conditions and material properties.

Remote Sensing, Big Data, and GeoAI

1st Edition
October 1, 2025
Erin Bunting + 3 more
English

Remote Sensing, Big Data, and GeoAI: Exploring Applications with Geospatial Insights is a foundational analysis and review exploring the transformative intersection of cutting-edge technologies in remote sensing. From fundamentals to advanced applications, this book equips readers with the knowledge and tools needed to apply AI and Big Data to remote sensing research, in order to improve decision-making and analysis. The book employs a dual approach, providing accessible explanations followed by real-world examples and case studies to bridge the gap between theory and practice. Readers will gain a deeper understanding of practical implications through a structured format that balances theoretical knowledge with immersive case studies, and will also gain an appreciation for ethical and legal considerations, making it an invaluable resource. Remote Sensing, Big Data, and GeoAI: Exploring Applications with Geospatial Insights offers insights for researchers, professionals, and students interested in harnessing the latest AI and Big Data techniques in remote sensing to address complex geospatial challenges.

Multimodal Remote Sensing Fusion and Classification

1st Edition
October 1, 2025
Man-On Pun + 1 more
English

Multimodal Remote Sensing Data Fusion for Classification: Algorithms and Applications provides a foundation for Earth observation data fusion using multimodal remote sensing, offering cutting-edge algorithms and practical applications. Through detailed analysis and case studies, the book equips readers with the knowledge and tools to utilize multimodal remote sensing data fusion to better understand Earth's dynamic processes and promote sustainable solutions in the classification and mapping of land cover and land use, and monitoring environmental change. Multimodal Remote Sensing Data Fusion for Classification: Algorithms and Applications provides Masters and Doctorate students, scientists and professionals in remote sensing, geography and Earth sciences with a foundation in integrating and analyzing multimodal remote sensing data.

Supervised Learning in Remote Sensing and Geospatial Science

1st Edition
October 1, 2025
Aaron E Maxwell + 2 more
English

Supervised Learning in Remote Sensing and Geospatial Science is a practical reference on supervised learning and associated best practices for applications in remote sensing and geospatial data science, in the context of practical and applied mapping and modeling tasks. With an emphasis on practicality, the book covers all supervised learning processes associated with developing labeled datasets to train and evaluate models, along with methods for combating common problems such as data imbalance, and direction on assessing model performance. Methods for preparing a wide variety of remotely sensed and geospatial data as input to supervised learning workflows are discussed.With a focus on bridging the gap between theory and practice, Supervised Machine Learning in Remote Sensing and Geospatial Data equips researchers, practitioners, and students with the necessary tools and techniques to extract actionable information from raw geospatial data.

Utilizing Earth Observation Data in Reaching Sustainable Development Goals

1st Edition
October 1, 2025
Aqil Tariq + 4 more
English

Utilizing Earth Observation Data in Reaching Sustainable Development Goals reviews the transformative potential of Earth observation data through targeted case studies showcasing its pivotal role in realizing Sustainable Development Goals (SDGs) in developing regions. After introducing the historical and theoretical background of EO data missions in the first part of the book, the second part is structured to deal with actionable SDGs. The book not only highlights successes but also addresses challenges and lessons learned, offering a comprehensive understanding of the dynamic interplay between technology and sustainability. Utilizing Earth Observation Data in Reaching Sustainable Development Goals utilises a consistent template for each chapter, exploring instances where satellite imagery, remote sensing, and geospatial analytics converge to provide actionable insights.

Earth Observation using Scatterometers

1st Edition
October 1, 2025
Sartajvir Singh + 4 more
English

Earth Observation using Scatterometers: State-of-the-Art Techniques, Applications, and Challenges details the critical role scatterometers can play in addressing natural disasters, climate action, and food security. This in-depth reference offers indispensable guidance on harnessing the potential of scatterometers for real-time applications, delving into advanced techniques such as super-resolution mapping and multi-source data fusion. It covers the latest advancements in algorithms and emerging applications of scatterometers, empowering professionals to efficiently analyze vast amounts of Earth observation data to better understand Earth systems, provides a unique resource for understanding the challenges and opportunities of scatterometer satellite datasets. With the continuous evolution of space-borne scatterometers, their applicability in oceanography, agriculture, the cryosphere, and related Earth-science fields is expanding, making this book an invaluable resource for scientists, geospatial data analysts, and students of Remote Sensing and Geoscience.

Quantitative Geomorphology in the Artificial intelligence Era

1st Edition
August 1, 2025
Hamid Reza Pourghasemi + 1 more
English
Paperback
9 7 8 0 4 4 3 3 0 0 3 6 3
eBook
9 7 8 0 4 4 3 3 0 0 3 7 0

Quantitative Geomorphology in the Artificial Intelligence Era: Applications of AI for Earth and Environmental Change focuses on bridging the gaps in this emerging discipline, it delves into the complex interplay between landforms and the processes that shape them, offering innovative solutions through AI and data-driven methods. The book addresses the standards, quality assessment of data, spatial and temporal analysis tools, and rigorous validation techniques in geomorphology. It uses computational intelligence as a pivotal tool alongside GIS, remote sensing, and other advanced technologies. Readers will find a holistic resource that fosters collaboration and knowledge exchange among geological fields, aiming to address geomorphological challenges, hazards, and solutions. By harnessing AI, GIS, remote sensing, machine learning, and geophysical techniques, it offers new dimensions to existing assessment methods and techniques.

Machine Learning in Geohazard Risk Prediction and Assessment

1st Edition
July 1, 2025
Biswajeet Pradhan + 2 more
English
Paperback
9 7 8 0 4 4 3 2 3 6 6 3 1
eBook
9 7 8 0 4 4 3 2 3 6 6 4 8

Machine Learning in Geohazard Risk Prediction and Assessment: From Microscale Analysis to Regional Mapping presents an overview of the most recent developments in machine learning techniques that have reshaped our understanding of geo-materials and management protocols of geo-risk. The book covers a broad category of research on machine-learning techniques that can be applied, from microscopic modeling to constitutive modeling, to physics-based numerical modeling, to regional susceptibility mapping. This is a good reference for researchers, academicians, graduate and undergraduate students, professionals, and practitioners in the field of geotechnical engineering and applied geology.

Carbon Fluxes and Biophysical Variables from Earth Observation

1st Edition
June 1, 2025
Manuel Campos-Taberner + 2 more
English
Paperback
9 7 8 0 4 4 3 2 9 9 9 1 9
eBook
9 7 8 0 4 4 3 2 9 9 9 2 6

Carbon Fluxes and Biophysical Variables from Earth Observation: Methods for Ecosystem Assessment transforms the way remote sensing data can be used to approach monitoring of carbon fluxes (CF) and biophysical variables (BV) in ecosystem and global vegetation monitoring. In a field where these two subjects have traditionally been treated as distinct entities, this book offers an integrated exploration of CF and BV retrieval through remote sensing. It not only delves into a wide array of approaches and methodologies but also assists readers in selecting the most suitable models based on available inputs and spatiotemporal scales. Carbon Fluxes and Biophysical Variables from Earth Observation is a useful resource for Earth Observation specialists, particularly in Remote Sensing, machine learning, ecology, and plant physiology, to enhance and adapt their approaches and methodologies.

Spatial Autocorrelation

1st Edition
June 1, 2025
Daniel Griffith + 1 more
English
Paperback
9 7 8 0 4 4 3 4 1 7 4 3 6
eBook
9 7 8 0 4 4 3 4 1 7 4 4 3

Spatial Autocorrelation: A Fundamental Property of Geospatial Sciences is an in-depth guide to understanding a crucial aspect of spatial analysis. The book begins with theories and clear definitions, laying a solid foundation for the reader. Through detailed explanations and practical examples, it delves into the concept and theory of spatial autocorrelation, illustrating the significance of spatial patterns in scientific research. The book includes comprehensive case studies that highlight the impact of spatial patterns on research and suggests innovative techniques for future studies. Additionally, it offers practical methodologies for quantifying spatial autocorrelation, complete with step-by-step guidance and real-world applications.This makes it an essential resource for graduate students, researchers, and professionals, providing them with the necessary tools to effectively apply spatial analysis in various fields.

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