Skip to main content
Elsevier

Books in Earth surface processes

Covering erosion, sediment transport, landscape evolution, and hydrology, this collection provides in-depth insights into dynamic surface phenomena. It supports geoscientists, geomorphologists, and environmental engineers seeking to understand and manage Earth's surface changes. Featuring innovative research, field studies, and modelling approaches, these resources help address environmental challenges, natural hazards, and land use planning, fostering sustainable interactions with our planet’s surface environments.

  • Utilizing Earth Observation Data in Reaching Sustainable Development Goals

    • 1st Edition
    • Aqil Tariq + 2 more
    • English
    Utilizing Earth Observation Data in Reaching Sustainable Development Goals explores the transformative potential of Earth observation data through case studies showcasing its pivotal role in achieving Sustainable Development Goals (SDGs) in developing regions. The book begins with a historical and theoretical overview of EO data missions, then shifts to actionable SDGs, highlighting successes, challenges, and lessons learned. This comprehensive work delves into the dynamic interplay between technology and sustainability. The book utilizes a consistent template for each chapter, exploring instances where satellite imagery, remote sensing, and geospatial analytics converge to provide actionable insights.It emphasizes both achievements and obstacles, offering practical solutions and strategies for effective implementation.

  • Satellite Remote Sensing for Forest and Environmental Monitoring

    • 1st Edition
    • Pablo Rodríguez Gonzálvez + 2 more
    • English
    Satellite Remote Sensing for Forest and Environmental Monitoring provides a thorough examination of the applications and methods of satellite remote sensing for analyzing and managing forest environments. From forest height mapping to biodiversity modeling, the book explores a variety of Earth observation applications across cutting-edge sensors and platforms. The book addresses the ability of satelitte technologies to observe and analyse ecological functions, conditions, and socioeconomic benefits for sustainable nature protection in the face of anthropogenic change, offering practical tools and strategies for large-scale forest inventories, fire risk assessment, and freshwater management. Satellite Remote Sensing for Forest and Environmental Monitoring offers postgraduates, researchers, and academics in remote sensing and geospatial technologies, particularly those focusing on forestry applications and related disciplines insights into environmental changes, land use patterns, vegetation mapping, and climate indicators.

  • Data-Driven Earth Observation for Disaster Management

    From Theory to Practical Applications
    • 1st Edition
    • Xiao Huang + 3 more
    • English
    Data-Driven Earth Observation for Disaster Management: From Theory to Practical Applications delves into the critical role of Earth observation data and technologies in predicting, managing, and mitigating a spectrum of disasters. With a multidisciplinary approach encompassing geography and geospatial science, the book addresses the challenges of comprehending and managing disasters in our rapidly changing world. Offering solutions through insights into early detection, prediction, management, and prevention, it provides strategies for understanding Earth surface changes and the application of Earth Observation technologies. Readers will gain understanding on how to use Earth observation data and techniques in studying different domains of disaster management.Chapters follow a consistent format, featuring introductory summaries, key takeaways, and a focus on the role of Earth observation, enhancing both comprehensibility and searchability. The book also includes case studies and practical applications of Earth observation technologies, providing context and demonstrating the tangible impact of the techniques covered.

  • Earth Observation using Scatterometers

    State-of-the-Art Techniques, Applications, and Challenges
    • 1st Edition
    • Sartajvir Singh + 4 more
    • English
    Earth Observation using Scatterometers: State-of-the-Art Techniques, Applications, and Challenges explores the critical role scatterometers play in addressing natural disasters, climate action, and food security. It provides comprehensive guidance on leveraging scatterometers for real-time applications, including advanced techniques like super-resolution mapping and multi-source data fusion. This book is an essential resource for understanding the challenges and opportunities of scatterometer satellite datasets. In addition to covering the latest advancements in algorithms and emerging applications, it empowers professionals to efficiently analyze vast amounts of Earth observation data.The book addresses scatterometers' expanding applicability in oceanography, agriculture, the cryosphere, and related Earth-science fields, making it invaluable for scientists, geospatial data analysts, and students of Remote Sensing and Geoscience.

  • Deep Learning for Synthetic Aperture Radar Remote Sensing

    • 1st Edition
    • Michael Schmitt + 1 more
    • English
    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.

  • Supervised Learning in Remote Sensing and Geospatial Science

    • 1st Edition
    • Aaron E Maxwell + 2 more
    • English
    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.

  • Geoheritage

    Assessment, Protection, and Management
    • 2nd Edition
    • Emmanuel Reynard + 1 more
    • English
    Geoheritage: Assessment, Protection, and Management, Second Edition provides a comprehensive exploration of geoheritage, beginning with an introduction to geodiversity and progressing to the characterisation of in situ and ex situ geoheritage, its protection and sustainable use. It also offers advanced concepts and methodologies for site assessment, mapping, conservation, visualisation and management, and features 12 case studies spanning five continents.Authored by 75 experts from 22 countries, this edition includes nearly 200 figures and maps. New chapters expand the scope of the first edition to address geoheritage’s links to biodiversity, climate change, natural hazards, ecosystem services, education and cities.This essential resource is perfect for geoscientists and students in the fields of geodiversity, geoheritage, geoconservation and geotourism, as well as professionals involved in nature conservation, protected areas and geoparks.

  • Spatial Autocorrelation

    A Fundamental Property of Geospatial Phenomena
    • 1st Edition
    • Daniel Griffith + 1 more
    • English
    Spatial Autocorrelation: A Fundamental Property of Geospatial Phenomena offers a state-of-the-art exploration of one of the most pivotal spatial analysis concepts. Beginning with foundational theories and clear definitions, it sets out the concepts and basic theory of spatial autocorrelation through elaborated conceptualizations and practical examples. In-depth case studies reveal the pervasive influence of spatial patterns in scientific inquiry while anticipating emerging research and innovative techniques. It offers practical methods for quantifying spatial autocorrelation, complete with step-by-step instructions and real-world examples.Spatial Autocorrelation equips graduate students, researchers, and professionals with the knowledge and tools to confidently comprehend, navigate, and apply spatial analysis in their respective domains, making it an ideal companion for technical reference books, and a vital addition to the libraries of any discipline utilizing spatial analysis.

  • Machine Learning in Geohazard Risk Prediction and Assessment

    From Microscale Analysis to Regional Mapping
    • 1st Edition
    • Biswajeet Pradhan + 2 more
    • English
    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

    Methods for Ecosystem Assessment
    • 1st Edition
    • Manuel Campos-Taberner + 2 more
    • English
    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.

Related subjects