❙ REMOTE SENSING AND IMAGE INTERPRETATION Seventh Edition ❙ REMOTE SENSING AND IMAGE INTERPRETATION Seventh Edition Thomas M Lillesand, Emeritus University of Wisconsin—Madison Ralph W Kiefer, Emeritus University of Wisconsin—Madison Jonathan W Chipman Dartmouth College Vice President and Publisher Executive Editor Sponsoring Editor Editorial Assistant Associate Editor Assistant Editor Senior Production Manager Production Editor Marketing Manager Photo Editor Cover Design Cover Photo Petra Recter Ryan Flahive Marian Provenzano Kathryn Hancox Christina Volpe Julia Nollen Janis Soo Bharathy Surya Prakash Suzanne Bochet James Russiello Kenji Ngieng Quantum Spatial and Washington State DOT This book was set in 10/12 New Aster by Laserwords and printed and bound by Courier Westford Founded in 1807, John Wiley & Sons, Inc has been a valued source of knowledge and understanding for more than 200 years, helping people around the world meet their needs and fulfill their aspirations Our company 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Congress Cataloging-in-Publication Data Lillesand, Thomas M Remote sensing and image interpretation / Thomas M Lillesand, Ralph W Kiefer, Jonathan W Chipman — Seventh edition pages cm Includes bibliographical references and index ISBN 978-1-118-34328-9 (paperback) Remote sensing I Kiefer, Ralph W II Chipman, Jonathan W III Title G70.4.L54 2015 621.36'78—dc23 2014046641 Printed in the United States of America 10 ❙ PREFACE This book is designed to be primarily used in two ways: as a textbook in introductory courses in remote sensing and image interpretation and as a reference for the burgeoning number of practitioners who use geospatial information and analysis in their work Rapid advances in computational power and sensor design are allowing remote sensing and its kindred technologies, such as geographic information systems (GIS) and the Global Positioning System (GPS), to play an increasingly important role in science, engineering, resource management, commerce, and other fields of human endeavor Because of the wide range of academic and professional settings in which this book might be used, we have made this discussion “discipline neutral.” That is, rather than writing a book heavily oriented toward a single field such as business, ecology, engineering, forestry, geography, geology, urban and regional planning, or water resource management, we approach the subject in such a manner that students and practitioners in any discipline should gain a clear understanding of remote sensing systems and their virtually unlimited applications In short, anyone involved in geospatial data acquisition and analysis should find this book to be a valuable text and reference The world has changed dramatically since the first edition of this book was published, nearly four decades ago Students may read this new edition in an ebook format on a tablet or laptop computer whose processing power and user interface are beyond the dreams of the scientists and engineers who pioneered the v vi PREFACE use of computers in remote sensing and image interpretation in the 1960s and early 1970s The book’s readers have diversified as the field of remote sensing has become a truly international activity, with countries in Asia, Africa, and Latin America contributing at all levels from training new remote sensing analysts, to using geospatial technology in managing their natural resources, to launching and operating new earth observation satellites At the same time, the proliferation of high‐resolution image‐based visualization platforms—from Google Earth to Microsoft’s Bing Maps—is in a sense turning everyone with access to the Internet into an “armchair remote‐sensing aficionado.” Acquiring the expertise to produce informed, reliable interpretations of all this newly available imagery, however, takes time and effort To paraphrase the words attributed to Euclid, there is no royal road to image analysis—developing these skills still requires a solid grounding in the principles of electromagnetic radiation, sensor design, digital image processing, and applications This edition of the book strongly emphasizes digital image acquisition and analysis, while retaining basic information about earlier analog sensors and methods (from which a vast amount of archival data exist, increasingly valuable as a source for studies of long‐term change) We have expanded our coverage of lidar systems and of 3D remote sensing more generally, including digital photogrammetric methods such as structure‐from‐motion (SFM) In keeping with the changes sweeping the field today, images acquired from uninhabited aerial system (UAS) platforms are now included among the figures and color plates, along with images from many of the new optical and radar satellites that have been launched since the previous edition was published On the image analysis side, the continuing improvement in computational power has led to an increased emphasis on techniques that take advantage of high‐volume data sets, such as those dealing with neural network classification, object‐based image analysis, change detection, and image time‐series analysis While adding in new material (including many new images and color plates) and updating our coverage of topics from previous editions, we have also made some improvements to the organization of the book Most notably, what was formerly Chapter 4—on visual image interpretation—has been split The first sections, dealing with methods for visual image interpretation, have been brought into Chapter 1, in recognition of the importance of visual interpretation throughout the book (and the field) The remainder of the former Chapter has been moved to the end of the book and expanded into a new, broader review of applications of remote sensing not limited to visual methods alone In addition, our coverage of radar and lidar systems has been moved ahead of the chapters on digital image analysis methods and applications of remote sensing Despite these changes, we have also endeavored to retain the traditional strengths of this book, which date back to the very first edition As noted above, the book is deliberately “discipline neutral” and can serve as an introduction to the principles, methods, and applications of remote sensing across many different subject areas There is enough material in this book for it to be used in many PREFACE vii different ways Some courses may omit certain chapters and use the book in a one‐semester or one‐quarter course; the book may also be used in a two‐course sequence Others may use this discussion in a series of modular courses, or in a shortcourse/workshop format Beyond the classroom, the remote sensing practitioner will find this book an enduring reference guide—technology changes constantly, but the fundamental principles of remote sensing remain the same We have designed the book with these different potential uses in mind As always, this edition stands upon the shoulders of those that preceded it Many individuals contributed to the first six editions of this book, and we thank them again, collectively, for their generosity in sharing their time and expertise In addition, we would like to acknowledge the efforts of all the expert reviewers who have helped guide changes in this edition and previous editions We thank the reviewers for their comments and suggestions Illustration materials for this edition were provided by: Dr Sam Batzli, USGS WisconsinView program, University of Wisconsin—Madison Space Science and Engineering Center; Ruediger Wagner, Vice President of Imaging, Geospatial Solutions Division and Jennifer Bumford, Marketing and Communications, Leica Geosystems; Philipp Grimm, Marketing and Sales Manager, ILI GmbH; Jan Schoderer, Sales Director UltraCam Business Unit and Alexander Wiechert, Business Director, Microsoft Photogrammetry; Roz Brown, Media Relations Manager, Ball Aerospace; Rick Holasek, NovaSol; Stephen Lich and Jason Howse, ITRES, Inc.; Qinghua Guo and Jacob Flanagan, UC‐Merced; Dr Thomas Morrison, Wake Forest University; Dr Andrea Laliberte, Earthmetrics, Inc.; Dr Christoph Borel‐Donohue, Research Associate Professor of Engineering Physics, U.S Air Force Institute of Technology; Elsevier Limited, the German Aerospace Center (DLR), Airbus Defence & Space, the Canadian Space Agency, Leica Geosystems, and the U.S Library of Congress Dr Douglas Bolger, Dartmouth College, and Dr Julian Fennessy, Giraffe Conservation Foundation, generously contributed to the discussion of wildlife monitoring in Chapter 8, including the giraffe telemetry data used in Figure 8.24 Our particular thanks go to those who kindly shared imagery and information about the Oso landslide in Washington State, including images that ultimately appeared in a figure, a color plate, and the front and back covers of this book; these sources include Rochelle Higgins and Susan Jackson at Quantum Spatial, Scott Campbell at the Washington State Department of Transportation, and Dr Ralph Haugerud of the U.S Geological Survey Numerous suggestions relative to the photogrammetric material contained in this edition were provided by Thomas Asbeck, CP, PE, PLS; Dr Terry Keating, CP, PE, PLS; and Michael Renslow, CP, RPP We also thank the many faculty, academic staff, and graduate and undergraduate students at Dartmouth College and the University of Wisconsin— Madison who made valuable contributions to this edition, both directly and indirectly Special recognition is due our families for their patient understanding and encouragement while this edition was in preparation viii PREFACE Finally, we want to encourage you, the reader, to use the knowledge of remote sensing that you might gain from this book to literally make the world a better place Remote sensing technology has proven to provide numerous scientific, commercial, and social benefits Among these is not only the efficiency it brings to the day‐to‐day decision‐making process in an ever‐increasing range of applications, but also the potential this field holds for improving the stewardship of earth’s resources and the global environment This book is intended to provide a technical foundation for you to aid in making this tremendous potential a reality Thomas M Lillesand Ralph W Kiefer Jonathan W Chipman This book is dedicated to the peaceful application of remote sensing in order to maximize the scientific, social, and commercial benefits of this technology for all humankind (a) (b) Epicenter (c) Surface deformation (cm) –12 +12 Plate 25 Differential radar interferograms showing surface deformation (a) Effects of the To¯hoku earthquake in Japan, March 11, 2011 (Courtesy JAXA.) (b) Ground uplift from magma accumulation below South Sister volcano, OR (Courtesy C Wicks, USGS.) (c) Subsidence in Las Vegas, NV White lines indicate surface faults (Courtesy Stanford University Radar Interferometry Group.) (For major discussion, see Section 6.9.) Plate 26 SIR-C color composite SAR image of a volcano-dominated landscape in central Africa, October 1994 Scale 1:360,000 (Courtesy NASA/JPL/Caltech.) (For major discussion, see Section 6.11.) (a) (b) Plate 27 Yellowstone National Park, WY: (a) SIR-C image, L-band, VH-polarization; (b) map of estimated aboveground biomass derived from (a) (Courtesy NASA/JPL/Caltech.) (For major discussion, see Section 6.11.) Plate 28 Shaded-relief DEM from airborne lidar data, Sagadahoc County, ME Nearshore waters of the Gulf of Maine appear in blue, low-lying areas (primarily tidal salt marshes) appear in green, and higher elevations appear in colors ranging from light green to white (Author-prepared figure.) (For major discussion, see Section 6.24.) Plate 29 Global bathymetric maps from satellite radar altimetry data (Author-prepared figure.) (For major discussion, see Section 6.21.) (a) (b) (d) (c) Plate 30 Sample interactive preliminary classification procedure used in the supervised training set refinement process: (a) original SPOT HRV color infrared composite image including selected training areas; (b) histograms and scatter diagram for band (red) and band (near-IR); (c) parallelepipeds associated with the initial training areas showing their locations in the band 2/band scatter diagram; (d) partially completed classification superimposed on band of the original images (Author-prepared figure.) (For major discussion, see Section 7.10.) (a) (b) (c) Plate 31 Use of multitemporal principal components analysis to detect change due to a tornado occurring in Burnett County in northwestern Wisconsin (a) ‘‘Before’’ image acquired approximately one month prior to the tornado (b) ‘‘After’’ image acquired one day after the tornado (c) ‘‘Change’’ image depicting the damage path as portrayed in the second principal component derived from a composite of the ‘‘before’’ and ‘‘after’’ images Scale 1:270,000 (Courtesy UW-Madison Environmental Remote Sensing Center.) (For major discussion, see Section 7.18.) (a) (b) 0.5 EVI mean (units) (c) –0.1 +0.1 EVI trend (units per decade) 0.5 EVI seasonal amplitude (units) Plate 32 Landscape phenology from time series of MODIS enhanced vegetation index (EVI) data, for Tarangire region in northern Tanzania (2000–2011) (a) Long-term mean of EVI (b) Decadal trend in EVI (c) Amplitude of seasonal cycle (Author-prepared figure.) (For major discussion, see Section 7.19.) (a) (b) Plate 33 Multitemporal NDVI data merging (a) Using multitemporal data as an aid in mapping invasive plant species, in this case reed canary grass (shown in red to pink tones) in wetlands This color composite results from the merger of NDVI values derived from Landsat-7 ETMỵ images of southern Wisconsin acquired on March (blue), April 24 (green), and October 15 (red), respectively Scale 1:120,000 (b) Monitoring algal blooms in portions of the two northernmost lakes shown NDVI values derived from Landsat-7 ETMỵ images acquired on April 24 (blue), October 31 (green), and October 15 (red), respectively Scale 1:130,000 (Author-prepared figure.) (For major discussion, see Section 7.20.) (a) (b) Plate 34 Biophysical modeling of chlorophyll concentration in lakes in Minnesota and Canada (a) MODIS true-color composite (bands 1, 4, and 3) for lake pixels only, superimposed on grayscale background, with sampling locations identified (red dots) (b) Resulting pixel-level map of chlorophyll concentration (Authorprepared figure.) (For major discussion, see Section 7.22.) (a) (b) Bare Shadow Creosote Broom snakeweed Sparse on bright soil Mesquite Tarbush Tobosa Sparse on dark soil Sumac Mariola Bush muhly 25 meters Plate 35 High resolution imagery (a) and species-level vegetation classification (b) from a UAV, for a rangeland in New Mexico, USA (From Laliberte et al., 2011 [doi:10.3390/rs3112529]; Courtesy of the journal Remote Sensing.) (For major discussion, see Section 8.6.) (a) (b) (c) (d) (e) (f) Plate 36 Oblique color infrared aerial photographs illustrating the effects of date of photography: (a) June 30; (b) July 1; (c) July 2; (d) August 11; (e) September 17; (f ) October Dane County, WI Approximate horizontal scale at photo center is 1:7600 (Author-prepared figure.) (For major discussion, see Section 8.3.) Plate 37 Digital camera image showing the aftermath of an F4 tornado striking Haysville, KS, on May 3, 1999 Scale 1:2300 (Courtesy Emerge.) (For major discussion, see Section 8.14.) (a) km 12 (b) km 15 30 60 Plate 38 Volcanic eruption at Bárðarbunga, Iceland, seen in a Landsat-8 OLI image acquired on September 6, 2014 Landsat OLI bands 7, 5, and displayed as red, green, and blue, respectively (a) Scale 1:275,000 (b) Scale 1:1,050,000 (Author-prepared figure.) (For major discussion, see Section 8.14.) (a) (b) Plate 39 QuickBird images of tsunami damage near Gleebruk, Indonesia (a) Pre-tsunami image, April 12, 2004 (b) Post-tsunami image, January 2, 2005 (Courtesy DigitalGlobe.) (For major discussion, see Section 8.14.) (a) (b) (c) (d) Plate 40 Oso landslide, Washington, March 2014 The landslide covered about 120 ha, with a volume of about 4,000,000 cubic meters of material moved downslope (a) April 2013 lidar image; (b) lidar image two days after the slide; (c) April 2013 normal color aerial photograph; (d) normal color aerial photograph two days after the slide Scale 1:23,000 (Image processing by Quantum Spatial Courtesy Washington State Department of Transportation.) (For major discussion, see Section 8.14.) WILEY END USER LICENSE AGREEMENT Go to www.wiley.com/go/eula to access Wiley’s ebook EULA ... ❙ REMOTE SENSING AND IMAGE INTERPRETATION Seventh Edition ❙ REMOTE SENSING AND IMAGE INTERPRETATION Seventh Edition Thomas M Lillesand, Emeritus University of Wisconsin—Madison... Data Lillesand, Thomas M Remote sensing and image interpretation / Thomas M Lillesand, Ralph W Kiefer, Jonathan W Chipman — Seventh edition pages cm Includes bibliographical references and index... scientists and engineers who pioneered the v vi PREFACE use of computers in remote sensing and image interpretation in the 1960s and early 1970s The book’s readers have diversified as the field of remote