Paper Info
Title
Classifying Grasslands and Cultivated Pastures in the Brazilian Cerrado Using Support Vector Machines, Multilayer Perceptrons and Autoencoders
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$$^2$$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.
Year
DOI
Venue
2015
10.1007/978-3-319-21024-7_13
Machine Learning and Data Mining in Pattern Recognition
Keywords
Field
DocType
Data mining,Image processing,Brazilian cerrado,Support vector machine,Multilayer perceptron,Autoenconder
Vegetation,Autoencoder,Pattern recognition,Computer science,Grassland,Multilayer perceptron,Biome,Artificial intelligence,Contextual image classification,Perceptron,Land cover,Cartography
Conference
Volume
ISSN
Citations 
9166
0302-9743
0
PageRank 
References 
Authors
0.34
4
3
Name
Order
Citations
PageRank
Wanderson Costa100.34
Leila Maria Garcia Fonseca24717.89
Thales Sehn Körting332.42