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Spectral Mixture for Remote Sensing

Linear Model and Applications

  • Yosio Edemir Shimabukuro
  • Flávio Jorge Ponzoni

Part of the Springer Remote Sensing/Photogrammetry book series (SPRINGERREMO)

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Yosio Edemir Shimabukuro, Flávio Jorge Ponzoni
    Pages 1-8
  3. Yosio Edemir Shimabukuro, Flávio Jorge Ponzoni
    Pages 9-16
  4. Yosio Edemir Shimabukuro, Flávio Jorge Ponzoni
    Pages 17-22
  5. Yosio Edemir Shimabukuro, Flávio Jorge Ponzoni
    Pages 23-41
  6. Yosio Edemir Shimabukuro, Flávio Jorge Ponzoni
    Pages 43-50
  7. Yosio Edemir Shimabukuro, Flávio Jorge Ponzoni
    Pages 51-67
  8. Yosio Edemir Shimabukuro, Flávio Jorge Ponzoni
    Pages 69-69
  9. Back Matter
    Pages 71-80

About this book

Introduction

This book explains in a didactic way the basic concepts of spectral mixing, digital numbers and orbital sensors, and then presents the linear modeling technique of spectral mixing and the generation of fractional images. In addition to presenting a theoretical basis for spectral mixing, the book provides examples of practical applications such as projects for estimating and monitoring deforested areas in the Amazon region. In its seven chapters, the book offers remote sensing techniques to understand the main concepts, methods, and limitations of spectral mixing for digital image processing.

Chapter 1 addresses the basic concepts of spectral mixing, while chapters 2 and 3 discuss digital numbers and orbital sensors such as MODIS and Landsat MSS. Chapter 4 details the linear spectral mixing model, and chapter 5 explains the use of this technique to create fraction images. Chapter 6 offers remote sensing applications of fraction images in deforestation monitoring, burned-area mapping, selective logging detection, and land-use/land-cover mapping. Chapter 7 gives some concluding thoughts on spectral mixing, and considers future uses in environmental remote sensing. This book will be of interest to students, teachers, and researchers using remote sensing for Earth observation and environmental modeling.


Keywords

Photogrammetry Linear spectral mixing model Electro-optical sensors Remote sensing Digital numbers (DN) MODIS Satellites Pixel Landsat MSS Fraction images Elements of interpretation Land cover mapping

Authors and affiliations

  • Yosio Edemir Shimabukuro
    • 1
  • Flávio Jorge Ponzoni
    • 2
  1. 1.Remote Sensing DivisionNational Institute for Space ResearchSão José dos CamposBrazil
  2. 2.Remote Sensing DivisionNational Institute for Space ResearchSão José dos CamposBrazil

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-030-02017-0
  • Copyright Information Springer Nature Switzerland AG 2019
  • Publisher Name Springer, Cham
  • eBook Packages Earth and Environmental Science
  • Print ISBN 978-3-030-02016-3
  • Online ISBN 978-3-030-02017-0
  • Series Print ISSN 2198-0721
  • Series Online ISSN 2198-073X
  • Buy this book on publisher's site