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Erschienen in:
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2019 | OriginalPaper | Buchkapitel

Method for the Automated Generation of a Forest Non Forest Map with LANDSAT 8 Imagery by Using Artificial Neural Networks and the Identification of Pure Class Pixels

verfasst von : Juan-Carlos Tituana, Cindy-Pamela Lopez, Sang Guun Yoo

Erschienen in: Technology Trends

Verlag: Springer International Publishing

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Abstract

In this work, a methodology for the automated classification of Landsat 8 images from the integration of Artificial Neural Networks and the identification of pixels of pure classes is presented. The exercise carried out in this research by using the SEPAL platform, allowed to obtain a mosaic L8 of the study area, fully preprocessed and calibrated, and it was generated automatically in a short period of time. This result represents a significant advance in terms of preprocessing capacity that currently exists for the management of satellite data compared to the state of the area a decade ago. This relevant advance has been possible due to the use of artificial neural networks and the cross-correlation coefficient of the pixels of the Landsat 8 satellite platform images. Their use and differentiation of areas in remote sensing of wooded, agricultural and water areas are discussed.

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Vorheriges Kapitel Computer Aided Diagnosis of Gastrointestinal Diseases Based on Iridology
Nächstes Kapitel A Computer Aided Diagnosis System for Skin Cancer Detection
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Metadaten
Titel
Method for the Automated Generation of a Forest Non Forest Map with LANDSAT 8 Imagery by Using Artificial Neural Networks and the Identification of Pure Class Pixels
verfasst von
Juan-Carlos Tituana
Cindy-Pamela Lopez
Sang Guun Yoo
Copyright-Jahr
2019
Buch
Technology Trends

Print ISBN: 978-3-030-05531-8

Electronic ISBN: 978-3-030-05532-5

Copyright-Jahr: 2019

DOI
https://doi.org/10.1007/978-3-030-05532-5_41

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