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Spectral mixture for remote sensing ...

Shimabukuro, Yosio Edemir.

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Spectral mixture for remote sensing = linear model and applications /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Spectral mixture for remote sensing/ by Yosio Edemir Shimabukuro, Flavio Jorge Ponzoni.
Reminder of title:	linear model and applications /
Author:	Shimabukuro, Yosio Edemir.
other author:	Ponzoni, Flavio Jorge.
Published:	Cham :Springer International Publishing : : 2019.,
Description:	xiii, 80 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Chapter1: Basic concepts -- Chapter2: The origin of digital numbers (DN) -- Chapter3: Orbital sensors -- Chapter4: Linear spectral mixing model -- Chapter5: Fraction images -- Chapter6: Applications of fraction images -- Chapter7: Final considerations.
Contained By:	Springer eBooks
Subject:	Remote sensing - Mathematical models. -
Online resource:	https://doi.org/10.1007/978-3-030-02017-0
ISBN:	9783030020170

Spectral mixture for remote sensing = linear model and applications /
Shimabukuro, Yosio Edemir.

Spectral mixture for remote sensinglinear model and applications /[electronic resource] :by Yosio Edemir Shimabukuro, Flavio Jorge Ponzoni. - Cham :Springer International Publishing :2019. - xiii, 80 p. :ill. (some col.), digital ;24 cm. - Springer remote sensing/photogrammetry,2198-0721. - Springer remote sensing/photogrammetry..

Chapter1: Basic concepts -- Chapter2: The origin of digital numbers (DN) -- Chapter3: Orbital sensors -- Chapter4: Linear spectral mixing model -- Chapter5: Fraction images -- Chapter6: Applications of fraction images -- Chapter7: Final considerations.

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.

ISBN: 9783030020170

Standard No.: 10.1007/978-3-030-02017-0doiSubjects--Topical Terms:

901143
Remote sensing
--Mathematical models.

LC Class. No.: G70.4 / .S556 2019

Dewey Class. No.: 621.3670285

Spectral mixture for remote sensing = linear model and applications /
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100 1 $a Shimabukuro, Yosio Edemir. $3 3381478
245 1 0 $a Spectral mixture for remote sensing $h [electronic resource] : $b linear model and applications / $c by Yosio Edemir Shimabukuro, Flavio Jorge Ponzoni.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2019.
300 $a xiii, 80 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Springer remote sensing/photogrammetry, $x 2198-0721
505 0 $a Chapter1: Basic concepts -- Chapter2: The origin of digital numbers (DN) -- Chapter3: Orbital sensors -- Chapter4: Linear spectral mixing model -- Chapter5: Fraction images -- Chapter6: Applications of fraction images -- Chapter7: Final considerations.
520 $a 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.
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650 2 4 $a Physical Geography. $3 893400
650 2 4 $a Monitoring/Environmental Analysis. $3 3135580
650 2 4 $a Image Processing and Computer Vision. $3 891070
650 2 4 $a Simulation and Modeling. $3 890873
650 2 4 $a Optics, Lasers, Photonics, Optical Devices. $3 2209850
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