Surface Displacement Measurement from Remote Sensing Images. Olivier CavalieЧитать онлайн книгу.
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SCIENCES
Image, Field Director – Laure Blanc-Feraud
Remote Sensing Imagery, Subject Head – Emmanuel Trouvé and Avik Bhattacharya
Surface Displacement Measurement from Remote Sensing Images
Coordinated by
Olivier Cavalié
Emmanuel Trouvé
First published 2022 in Great Britain and the United States by ISTE Ltd and John Wiley & Sons, Inc.
Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms and licenses issued by the CLA. Enquiries concerning reproduction outside these terms should be sent to the publishers at the undermentioned address:
ISTE Ltd
27-37 St George’s Road
London SW19 4EU
UK
John Wiley & Sons, Inc.
111 River Street
Hoboken, NJ 07030
USA
© ISTE Ltd 2022
The rights of Olivier Cavalié and Emmanuel Trouvé to be identified as the authors of this work have been asserted by them in accordance with the Copyright, Designs and Patents Act 1988.
Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s), contributor(s) or editor(s) and do not necessarily reflect the views of ISTE Group.
Library of Congress Control Number: 2022934057
British Library Cataloguing-in-Publication Data
A CIP record for this book is available from the British Library
ISBN 978-1-78945-083-5
ERC code:
PE6 Computer Science and Informatics
PE6_11 Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video)
PE10 Earth System Science
PE10_14 Earth observations from space/remote sensing
Preface
This book is part of ISTE–Wiley’s SCIENCES series and belongs to the Image field of the Engineering and Systems department. The Image field covers the entire processing chain, from acquisition to interpretation, by analyzing the data provided by various imaging systems. This field is split into seven subjects, including remote sensing imagery (RSI). Based on this subject, we proposed a series of books that would portray diverse and comprehensive topics related to advanced remote sensing images and their applications for Earth observation (EO). There has been an increasing demand for the monitoring and prediction of our planet’s evolution on local, regional and global scales. Hence, airborne, space-borne and ground-based platforms with active and passive sensors have been used to acquire images that measure several features at various spatial and temporal resolutions over the past few decades.
RSI has become a broad multidisciplinary domain, attracting scientists across the diverse fields of science and engineering. The books proposed in this RSI series aim to present state-of-the-art scientific knowledge about the primary sources of images acquired by optical and radar sensors. The books cover the processing methods that have been developed by the signal and image processing community to extract useful information for end-users for an extensive range of EO applications.
Each RSI book focuses on a general topic, such as change detection, surface displacement measurement, target detection, model inversion or data assimilation. We dedicate this second book of the RSI series to the measurement of displacements on the Earth’s surface using RSI. It presents the main approaches that are used to derive displacement information from image pairs or image time series using optical and synthetic aperture radar (SAR) data. Following the numerous studies conducted in this domain, we divide this book into methodology and applications.
The first part, Theory, Principles and Methodology, is dedicated to the wide range of methods that have been developed to measure displacement fields from remote sensing images. Chapter 1 provides an overview of the main space missions devoted to EO, which have been used to acquire optical and SAR images for more than 40 years. From the archives of space agencies to future missions, this chapter presents the history and the main characteristics of the data processed to measure the Earth’s topography and surface displacement. Chapters 2 and 3 present the first group of methods developed, which measure displacement from the radiometry of images acquired at different dates, for optical and SAR images, respectively. These methods based on template matching are known as correlation or offset tracking techniques. These chapters include a brief description of the sensor geometry that is required to transform the measured offsets into velocities and to evaluate the potential and limits of this approach. Chapters 4, 5 and 6 examine the second group of methods, which use the phase of SAR images to derive surface displacement using interferometry (InSAR). The principle of InSAR, the geometric and statistical issues and the first processing steps are described in Chapter 4, including the limitations due to atmospheric artifacts. Chapter 5 shows how time-series InSAR methods, namely persistent scatterer and small baseline approaches, succeed in measuring centimeter-