Advertisement

© 2015

Real time deforestation detection using ANN and Satellite images

The Amazon Rainforest study case

Benefits

  • Development of a tool to detect daily deforestation in the Amazon rainforest, using satellite images from the MODIS/TERRA sensor and Artificial Neural Networks

  • Tool provides parameterization of the configuration for the neural network training to select the best neural architecture to address the problem

  • The tool uses confusion matrices to determine the degree of success of the network

  • A spectrum-temporal analysis of the study area was done on 57 images from May 20 to July 15, 2003 using the trained neural network

Book
  • 6.3k Downloads

Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Table of contents

  1. Front Matter
    Pages i-x
  2. Thiago Nunes Kehl, Viviane Todt, Maurício Roberto Veronez, Silvio Cesar Cazella
    Pages 1-4
  3. Thiago Nunes Kehl, Viviane Todt, Maurício Roberto Veronez, Silvio Cesar Cazella
    Pages 5-18
  4. Thiago Nunes Kehl, Viviane Todt, Maurício Roberto Veronez, Silvio Cesar Cazella
    Pages 19-31
  5. Thiago Nunes Kehl, Viviane Todt, Maurício Roberto Veronez, Silvio Cesar Cazella
    Pages 33-38
  6. Thiago Nunes Kehl, Viviane Todt, Maurício Roberto Veronez, Silvio Cesar Cazella
    Pages 39-49
  7. Back Matter
    Pages 51-67

About this book

Introduction

The foremost aim of the present study was the development of a tool to detect daily deforestation in the Amazon rainforest, using satellite images from the MODIS/TERRA sensor and Artificial Neural Networks. The developed tool provides parameterization of the configuration for the neural network training to enable us to select the best neural architecture to address the problem. The tool makes use of confusion matrices to determine the degree of success of the network. A spectrum-temporal analysis of the study area was done on 57 images from May 20 to July 15, 2003 using the trained neural network. The analysis enabled verification of quality of the implemented neural network classification and also aided in understanding the dynamics of deforestation in the Amazon rainforest, thereby highlighting the vast potential of neural networks for image classification. However, the complex task of detection of predatory actions at the beginning, i.e., generation of consistent alarms, instead of false alarms has not been solved yet. Thus, the present article provides a theoretical basis and elaboration of practical use of neural networks and satellite images to combat illegal deforestation.

Keywords

MODIS amazon rainforest artificial neural networks deforestation detection satellite images classification

Authors and affiliations

  1. 1.Universidade do Vale do Rio dos SinosSão LeopoldoBrazil
  2. 2.Universidade do Vale do Rio dos Sinos -São LeopoldoBrazil
  3. 3.Universidade do Vale do Rio dos SinosSão LeopoldoBrazil
  4. 4.UFCSPAPorto AlegreBrazil

Bibliographic information

  • Book Title Real time deforestation detection using ANN and Satellite images
  • Book Subtitle The Amazon Rainforest study case
  • Authors Thiago Nunes Kehl
    Viviane Todt
    Maurício Roberto Veronez
    Silvio Cesar Cazella
  • Series Title SpringerBriefs in Computer Science
  • Series Abbreviated Title SpringerBriefs Computer Sci.
  • DOI https://doi.org/10.1007/978-3-319-15741-2
  • Copyright Information Springer International Publishing Switzerland 2015
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science Computer Science (R0)
  • Softcover ISBN 978-3-319-15740-5
  • eBook ISBN 978-3-319-15741-2
  • Series ISSN 2191-5768
  • Series E-ISSN 2191-5776
  • Edition Number 1
  • Number of Pages X, 67
  • Number of Illustrations 4 b/w illustrations, 21 illustrations in colour
  • Topics Remote Sensing/Photogrammetry
    Artificial Intelligence
  • Buy this book on publisher's site
Industry Sectors
Aerospace
Oil, Gas & Geosciences