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Hyperspectral remote sensing: fundamentals and practices / Ruiliang Pu

Por: Pu, Ruiliang [autor/a].
Tipo de material: Libro
 impreso(a) 
 Libro impreso(a) Series Editor: Boca Raton, Florida: CRC Press Taylor and Francis Group, c2017Descripción: xxiv, 466 páginas : fotografías, retratos, ilustraciones, mapas ; 26 centímetros.ISBN: 1138747173; 9781138747173.Tema(s): Sensores remotos | imágenes hiperespectrales | Procesamiento de imágenesClasificación: 621.3678 / P8 Nota de bibliografía: Incluye bibliografía e índice Número de sistema: 58448Contenidos:Mostrar Resumen:
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Hyperspectral remote sensing has been a frontier of geospatial technology since the late 1980s, first with the launch of airborne sensors, and later, in the 1990s, with the addition of spaceborne sensors. Today, we can witness the maturity of hyperspectral remote sensing from its wide range of applications, readily available software for image processing, and large volume of pertinent publications. With the expectation of future satellite missions of hyperspectral imaging with global coverage and increasing improvement in image-processing efficiency and information extraction effectiveness, hyperspectral remote sensing will usher in an era of reinvention with the integrated use of high spatial and temporal resolution, LiDAR, and radar sensing. In this context, I am pleased that Dr. Ruiliang Pu has the vision and energy to have written a book on this important topic. The book provides an exhaustive review of the characteristics of airborne and spaceborne hyperspectral sensors, systems, and missions; it discusses in detail the algorithms, techniques, and methods for processing and analyzing hyperspectral data. Further, the author assesses the features and modules of operational tools and software for processing hyperspectral data, followed by a comprehensive investigation of hyperspectral remote sensing applications to geology, soils, vegetation, and environments. Dr. Pu instills his research of more than two decades and rich teaching experience across the Pacific Ocean into the writing of this book. It is a one-of-a-kind textbook, as well as research monograph. I plan to use this book for my multiple remote sensing classes. This book is the sixteenth volume in the Taylor & Francis Series in Remote Sensing Applications, and 2017 marks the tenth anniversary of this series.

As envisioned in 2007, the books in the series contribute to advancements in theories, methods, techniques, and applications of remote sensing in various fields. In fact, as seen today, many of the books in the series have served well as references for professionals, researchers, and scientists, and as textbooks for teachers and students throughout countries all over the world. I hope that the publication of this book will promote a wider and deeper appreciation and application of hyperspectral remote sensing technology. Finally, my hearty congratulations go to Dr. Pu for creating a new milestone in the history of remote sensing.

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Acervo General 621.3678 P8 Prestado 11/08/2021 ECO030008661

Incluye bibliografía e índice

Foreword.. Preface.. Acknowledgments.. Author.. Introduction.. Chapter 1 Overview of Hyperspectral Remote Sensing.. Chapter 2 Field Spectrometers and Plant Biology Instruments for HRS.. Chapter 3 Imaging Spectrometers, Sensors, Systems, and Missions.. Chapter 4 Hyperspectral Image Radiometric Correction.. Chapter 5 Hyperspectral Data Analysis Techniques.. Chapter 6 Hyperspectral Data Processing Software.. Chapter 7 Hyperspectral Applications in Geology and Soil Sciences.. Chapter 8 Hyperspectral Applications to Vegetation.. Chapter 9 Hyperspectral Applications to Environments.. Index

Hyperspectral remote sensing has been a frontier of geospatial technology since the late 1980s, first with the launch of airborne sensors, and later, in the 1990s, with the addition of spaceborne sensors. Today, we can witness the maturity of hyperspectral remote sensing from its wide range of applications, readily available software for image processing, and large volume of pertinent publications. With the expectation of future satellite missions of hyperspectral imaging with global coverage and increasing improvement in image-processing efficiency and information extraction effectiveness, hyperspectral remote sensing will usher in an era of reinvention with the integrated use of high spatial and temporal resolution, LiDAR, and radar sensing. In this context, I am pleased that Dr. Ruiliang Pu has the vision and energy to have written a book on this important topic. The book provides an exhaustive review of the characteristics of airborne and spaceborne hyperspectral sensors, systems, and missions; it discusses in detail the algorithms, techniques, and methods for processing and analyzing hyperspectral data. Further, the author assesses the features and modules of operational tools and software for processing hyperspectral data, followed by a comprehensive investigation of hyperspectral remote sensing applications to geology, soils, vegetation, and environments. Dr. Pu instills his research of more than two decades and rich teaching experience across the Pacific Ocean into the writing of this book. It is a one-of-a-kind textbook, as well as research monograph. I plan to use this book for my multiple remote sensing classes. This book is the sixteenth volume in the Taylor & Francis Series in Remote Sensing Applications, and 2017 marks the tenth anniversary of this series. eng

As envisioned in 2007, the books in the series contribute to advancements in theories, methods, techniques, and applications of remote sensing in various fields. In fact, as seen today, many of the books in the series have served well as references for professionals, researchers, and scientists, and as textbooks for teachers and students throughout countries all over the world. I hope that the publication of this book will promote a wider and deeper appreciation and application of hyperspectral remote sensing technology. Finally, my hearty congratulations go to Dr. Pu for creating a new milestone in the history of remote sensing. eng

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