@InProceedings{GirolamoNetoFonsKört:2016:CaStBr,
author = "Girolamo Neto, Cesare di and Fonseca, Leila Maria Garcia and
K{\"o}rting, Thales Sehn",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de
Pesquisas Espaciais (INPE)}",
title = "Assessment of texture features for Brazilian savanna
classification: a case study in Brasilia National Park",
booktitle = "Anais...",
year = "2016",
organization = "Brazilian Symposium on GeoInformatics, 17. (GEOINFO)",
abstract = "Distinguishing Brazilian savanna physiognomies is an essential
task to better evaluate carbon storage and potential emissions of
greenhouse gases. In this study, we propose to evaluate the
potential of texture features to improve the discrimination among
five physiognomies in the Brazilian savanna: Open Grasslands,
Shrubby Grassland, Shrubby Savanna, Savanna Woodland and Gallery
Forest. Texture features extracted from RapidEye images and also
from Spectral Linear Mixture Model components and Vegetation Index
are evaluated in this study. Results showed that texture features
based on GLCM can reduce misclassification for Open Grasslands,
Shrubby Grasslands and Shrubby Savanna classes.",
conference-location = "Campos do Jord{\~a}o, SP",
conference-year = "27-30 nov. 2016",
language = "en",
ibi = "8JMKD3MGP3W34P/3N2UA78",
url = "http://urlib.net/ibi/8JMKD3MGP3W34P/3N2UA78",
targetfile = "204-215girolamo.pdf",
urlaccessdate = "28 abr. 2024"
}