Big Data for Remote Sensing: Visualization, Analysis and Interpretation
This book thoroughly covers the remote sensing visualization and analysis techniques based on computational imaging and vision in Earth science. Remote sensing is considered a significant information source for monitoring and mapping natural and man-
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Data for Remote Sensing: Visualization, Analysis and Interpretation Digital Earth and Smart Earth
Big Data for Remote Sensing: Visualization, Analysis and Interpretation
Nilanjan Dey Chintan Bhatt Amira S. Ashour •
Editors
Big Data for Remote Sensing: Visualization, Analysis and Interpretation Digital Earth and Smart Earth
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Editors Nilanjan Dey Department of Information Technology Techno India College of Technology Kolkata, West Bengal India Chintan Bhatt Charotar University of Science and Technology Changa, Gujarat India
Amira S. Ashour Department of Electronics and Electrical Communications Engineering, Faculty of Engineering Tanta University Tanta Egypt
ISBN 978-3-319-89922-0 ISBN 978-3-319-89923-7 https://doi.org/10.1007/978-3-319-89923-7
(eBook)
Library of Congress Control Number: 2018941536 © Springer International Publishing AG, part of Springer Nature 2019 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Printed on acid-free paper This Springer imprint is published by the registered company Springer International Publishing AG part of Springer Nature The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
Foreword
In this digital era, the size of the data involved in countless applications of our society has been increased substantially. Therefore, new computational methods, algorithms, and infrastructures are highly demanded in order to handle such sets of big data more efficiently, mainly in numerous real-time applications, requiring less powerful computational resources, so can be processed by common computational solutions. Among the various areas where big data sets have become common, the ones related to Remote Sensing and information and communication technology are foremost, since the datasets involved have reached huge dimensions, which makes exceptionally complex their visualization, analysis, and interpretatio
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