Spectral Mixture

Yosio Edemir Shimabukuro , Flávio Jorge Ponzoni

In the classification of data and application of remote sensing techniques, one of the challenges faced is the classification of non-uniform pixels, with a mixture of components such as soil, vegetation, rock and water. Spectral mixture: linear model and applications deals with the techniques of characterization of these data and quantification of the mixture in the pixels, allowing its use.

 

The book explains in a didactic way the basic concepts of spectral mixture, digital numbers and orbital sensors, and then presents the technique of linear model of spectral mixture and the generation of fractional images. In addition to a solid theoretical basis, Spectral Mixture brings important examples of practical application, such as in projects for the estimation and monitoring of areas of deforestation and forest fire in the Legal Amazon.

Original title
Mistura espectral
ISBN
978-85-7975-270-4
eISBN
978-85-7975-269-8
Pages
128
Year of publication
2017
Edition
1st

About the authors

Yosio Edemir Shimabukuro

Yosio Edemir Shimabukuro is a forest engineer graduated from Federal Rural University of Rio de Janeiro, Master in Remote Sensing from National Institute For Space Research (INPE) and PhD in Forest Sciences and Remote Sensing from Colorado State University (USA).

Flávio Jorge Ponzoni

Flávio Jorge Ponzoni is a forest engineer graduated from the Federal University of Viçosa, Master in Forest Sciences from the Federal University of Viçosa and PhD in Forest Sciences from the Federal University of Paraná.

Introduction

 

Basis

Mixing problem in the pixel

 

The origin of digital numbers

 

Orbital sensors

Modis

Spot Vegetation

Landsat MSS, TM, ETM+, OLI

Hyperion

 

Linear model of spectral mixture

Mathematical algorithms

Choice of the endmembers

 

Fraction images

Error images

 

Application of fractional images

Deforestation monitoring

Mapping burned areas

Detection of selective cutting

Mapping land use and land cover

 

Final considerations

 

Works cited

Recommended literature