- Published Year: 2005
- Page count: 454
- File Size: 8 Mb
- Language: English
- Published by: Springer
- Visited by: 1
- Rating/Review: 4.5
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ISBN:
9783540251286
3-540-25128-6
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Introduction to "Remote Sensing Digital Image Analysis: An Introduction"
"Remote Sensing Digital Image Analysis: An Introduction" by John A. Richards and Xiuping Jia is a definitive exploration of the field of digital image analysis as it pertains to remotely sensed data. This book is a cornerstone resource for students, researchers, and professionals in remote sensing, geospatial sciences, and environmental studies, offering powerful insights into the methodologies and applications of digital image processing in remote sensing contexts.
With technological advancements enabling the acquisition of large remote sensing datasets, the book provides the essential skills to process, analyze, and interpret this imagery effectively. It delves into both theoretical concepts and practical tools, creating a comprehensive guide designed to cater to a diverse audience ranging from beginners to seasoned practitioners.
Detailed Summary of the Book
The book is structured to cover the full spectrum of digital image analysis, starting with an introduction to remote sensing systems and their foundational principles. It discusses the generation of remotely sensed data and explains techniques for pre-processing raw imagery to ensure quality and consistency. This includes geometric corrections, radiometric calibration, and noise reduction processes.
Subsequent chapters meticulously dissect various methods used for image enhancement, feature extraction, and image classification. These include spectral and spatial techniques, algorithms for pattern recognition, and approaches to multi-resolution or multi-temporal image analysis. Given the explosive growth in computational capabilities, the book addresses modern machine learning algorithms and their applications in remote sensing image processing tasks.
Later sections cover advanced topics such as hyperspectral image analysis, texture analysis, and integration of geographical information systems (GIS) in processing remotely sensed data. Additionally, the book emphasizes the practical application of digital image analysis to areas like land use mapping, environmental monitoring, and natural resource management. Exercises and examples are included throughout, offering real-world context and reinforcing theoretical concepts.
Rich in clarity, precision, and utility, this book remains a must-have resource for anyone aiming to excel in the field.
Key Takeaways
- A solid foundation in the physical principles behind digital remote sensing systems.
- Critical insights into pre-processing techniques designed to prepare raw remote sensing data for advanced analysis.
- Comprehensive coverage of image classification, including supervised and unsupervised methodologies.
- Exploration of modern tools, such as machine learning, and their role in digital image analysis.
- Practical applications of remote sensing for environmental problem-solving, urban planning, and resource management.
- Exercises and case studies that bridge theory and practice, making concepts easy to understand and apply.
Famous Quotes from the Book
"The science of remote sensing enables us to view the world from a perspective unattainable by human vision alone."
"The essence of digital image analysis is the extraction of meaningful information from imagery in a quantitative manner."
"In a time when global change is accelerating, remote sensing stands as a critical tool in understanding and managing the Earth's complex systems."
Why This Book Matters
As the demand for actionable insights from geospatial data continues to grow, "Remote Sensing Digital Image Analysis: An Introduction" becomes increasingly relevant. The book matters because it bridges the gap between traditional methodologies and cutting-edge technological advances in remote sensing. By providing unparalleled clarity and practicality, it creates opportunities for learners to comprehend and apply intricate analytical techniques.
Whether you are focused on environmental sustainability, urban planning, agriculture, or disaster management, this book equips you with the tools to make informed, data-driven decisions. Moreover, with its clear structure and accessible language, the book ensures knowledge transfer across academic and professional boundaries. Its balanced treatment of theory and practical application ensures that readers can transition smoothly from foundational concepts to hands-on expertise.
Ultimately, this book continues to hold its place as an essential reference in the ever-evolving field of remote sensing and digital image analysis.
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