Skip to main content
Elsevier
View Cart
My account

Books in Remote sensing and photogrammetry

BooksJournals

    • 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.

    • Remote Sensing for Vegetation Monitoring

      • 1st Edition
      • February 1, 2026
      • Prem Chandra Pandey + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 3 0 7 6 6
      • eBook
        9 7 8 0 4 4 3 3 3 0 7 7 3
      Remote Sensing for Vegetation Monitoring: Technologies, Applications and Models provides insight on the pivotal role that remote sensing plays in vegetation monitoring. As traditional field assessments face challenges due to inaccessible study sites and lengthy data collection, this book offers a comprehensive view of remote sensing applications for monitoring various vegetation ecosystems, including forests, grasslands, mangroves, and agriculture. The book presents a coherent and consistent structure, across five sections that build upon prior knowledge and detail the quantitative and qualitative assessments made possible through remote sensing technologies. Remote Sensing for Vegetation Monitoring: Technologies, Applications and Models caters to a diverse audience, including researchers and practitioners seeking to navigate the evolving landscape of vegetation monitoring through case studies, new algorithms and state-of-the-art methods.

    • Models and Methods for Synthetic Aperture Radar Remote Sensing

      • 1st Edition
      • April 1, 2026
      • Pasquale Imperatore + 2 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 4 0 5 3 6
      • eBook
        9 7 8 0 4 4 3 3 4 0 5 4 3
      Models and Methods for Synthetic Aperture Radar Remote Sensing: From Physics to Applications expansively outlines the use of SAR remote sensing in Earth Observation, offering state-of-the-art methodologies, broad applications and use cases, and a multidisciplinary approach. It explores basic and advanced methods, accompanied by practical applications and case studies, fostering a deep understanding and facilitating real-world problem-solving in Earth Observation. Models and Methods for Synthetic Aperture Radar Remote Sensing: From Physics to Applications provides invaluable insights into SAR technologies, enhancing research quality and relevance through reproduceable methodology for Earth Observation and remote sensing researchers and academics, or Earth and Environmental scientists employing remote sensing techniques.

    • GNSS Applications to Monitor Natural Hazards

      • 1st Edition
      • March 1, 2026
      • Joseph Awange
      • English
      • Paperback
        9 7 8 0 4 4 3 2 1 4 6 5 3
      • eBook
        9 7 8 0 4 4 3 2 1 4 6 6 0
      Global Navigation Satellite Systems (GNSS) are a cornerstone of modern geodetic positioning, but their true potential extends far beyond traditional applications. GNSS Applications to Monitor Natural Hazards presents a systematic, step-by-step methodology for leveraging satellite-based positioning to detect, analyze, and mitigate environmental threats—from floods and droughts to seismic shifts and landslides. As climate change intensifies natural hazards, this book bridges the gap between theory and practice, offering researchers, engineers, and policymakers reproducible techniques to enhance early-warning systems. For the first time, it also explores AI-enhanced GNSS, demonstrating how machine learning can unlock real-time hazard prediction and adaptive monitoring. Designed for both experts and newcomers, this work translates cutting-edge research into actionable strategies, empowering readers to harness GNSS technology for a more resilient future. Whether optimizing disaster response or decoding subtle environmental changes, this book is an essential guide to reducing the impact of catastrophic events through innovation.

    • Agricultural Applications of Earth Observation

      • 1st Edition
      • February 1, 2026
      • Peng Fu
      • English
      • Paperback
        9 7 8 0 4 4 3 3 8 3 4 5 8
      • eBook
        9 7 8 0 4 4 3 3 8 3 4 6 5
      Agricultural Applications of Earth Observation details the revolutionary impact of satellite and remote sensing technologies in enhancing agricultural practices. It bridges the knowledge gap by making advanced satellite and sensor data understandable and applicable, enabling readers to select the best tools for specific agricultural needs. Real-world case studies and practical examples demonstrate the successful implementation of Earth Observation technologies in agriculture, inspiring readers with tangible results and encouraging innovative thinking. Agricultural Applications of Earth Observation enables readers to apply Earth Observation technologies to enhance agronomical sustainability and contribute to more environmentally friendly practices. With detailed methodologies and a range of additional supplementary elements, the book equips readers with the knowledge and tools to drive the future of agriculture into a more sustainable era.

    • Remote Sensing at Night

      • 1st Edition
      • February 1, 2026
      • Qingling Zhang
      • English
      • Paperback
        9 7 8 0 4 4 3 3 0 0 2 4 0
      • eBook
        9 7 8 0 4 4 3 3 0 0 2 5 7
      Remote Sensing at Night: Technologies, Applications, and Perspectives delves into the pivotal role of remote sensing in deciphering Earth's nocturnal landscapes. This comprehensive resource utilizes a range of case studies to make complex topics accessible to a diverse audience with varied scientific backgrounds. The book emphasizes recent advances in remote sensing technology, encompassing nightlight, thermal infrared, and Synthetic Aperture Radar (SAR) capabilities facilitated by state-of-the-art Earth observation satellites. The book also explores the technological advancements in nighttime monitoring for practical and research purposes, Earth observation datasets, and the challenges faced. It equips readers with multidisciplinary knowledge and practical solutions for nighttime monitoring, providing up-to-date global case studies and methodologies for researchers, graduate students, scientists, and academics in remote sensing, geospatial research, and environmental science.

    • Multimodal Remote Sensing Fusion and Classification

      • 1st Edition
      • March 1, 2026
      • Man-On Pun + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 9 1 5 2 4
      • eBook
        9 7 8 0 4 4 3 2 9 1 5 3 1
      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.

    • Remote Sensing, Big Data, and GeoAI

      • 1st Edition
      • March 1, 2026
      • Erin Bunting + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 6 7 4 1 3
      • eBook
        9 7 8 0 4 4 3 2 6 7 4 2 0
      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.

    • Satellite Remote Sensing for Forest and Environmental Monitoring

      • 1st Edition
      • December 1, 2025
      • Pablo Rodríguez Gonzálvez + 2 more
      • English
      • Paperback
        9 7 8 0 4 4 3 4 0 2 9 6 8
      • eBook
        9 7 8 0 4 4 3 4 0 2 9 7 5
      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.

    • Deep Learning for Synthetic Aperture Radar Remote Sensing

      • 1st Edition
      • December 1, 2025
      • 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.