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2015 | OriginalPaper | Buchkapitel

Classifying Grasslands and Cultivated Pastures in the Brazilian Cerrado Using Support Vector Machines, Multilayer Perceptrons and Autoencoders

verfasst von : Wanderson Costa, Leila Fonseca, Thales Körting

Erschienen in: Machine Learning and Data Mining in Pattern Recognition

Verlag: Springer International Publishing

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Abstract

One of the most biodiverse regions on the planet, Cerrado is the second largest biome in Brazil. Among the land changes in the Cerrado, over 500,000 km\(^2\) of the biome have been changed into cultivated pastures in recent years. Categorizing types of land cover and its native formations is important for protection policy and monitoring of the biome. Based on remote sensing techniques, this work aims at developing a methodology to map pasture and native grassland areas in the biome. Data related to EVI vegetation indices obtained by MODIS images were used to perform image classification. Support Vector Machine, Multilayer Perceptron and Autoencoder algorithms were used and the results showed that the analysis of different attributes extracted from EVI indices can aid in the classification process. The best result obtained an accuracy of 85.96 % in the study area, identifying data and attributes required to map pasture and native grassland in Cerrado.

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Vorheriges Kapitel MOGACAR: A Method for Filtering Interesting Classification Association Rules
Nächstes Kapitel Hybrid Approach for Inductive Semi Supervised Learning Using Label Propagation and Support Vector Machine
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Metadaten
Titel
Classifying Grasslands and Cultivated Pastures in the Brazilian Cerrado Using Support Vector Machines, Multilayer Perceptrons and Autoencoders
verfasst von
Wanderson Costa
Leila Fonseca
Thales Körting
Copyright-Jahr
2015
Buch
Machine Learning and Data Mining in Pattern Recognition

Print ISBN: 978-3-319-21023-0

Electronic ISBN: 978-3-319-21024-7

Copyright-Jahr: 2015

DOI
https://doi.org/10.1007/978-3-319-21024-7_13

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