@InProceedings{MelloVieiAguiRudo:2009:ClCoCa,
author = "Mello, M{\'a}rcio Pupin de and Vieira, Carlos Ant{\^o}nio
Oliveira and Aguiar, Daniel Alves de and Rudorff, Bernardo
Friedrich Theodor",
affiliation = "{Instituto Nacional de Pesquisas Espaciais - INPE} and
{Universidade Federal de Vi{\c{c}}osa - UFV} and {Instituto
Nacional de Pesquisas Espaciais - INPE} and {Instituto Nacional de
Pesquisas Espaciais - INPE}",
title = "Classifica{\c{c}}{\~a}o da colheita da
cana-de-a{\c{c}}{\'u}car por meio de imagens de sat{\'e}lite
utilizando superf{\'{\i}}cies de resposta espectro-temporais",
booktitle = "Anais...",
year = "2009",
editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio
Soares",
pages = "279--286",
organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 14. (SBSR)",
publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
address = "S{\~a}o Jos{\'e} dos Campos",
keywords = "remote sensing, multitemporal image classification, accuracy
assessment, automatization, sensoriamento remoto,
classifica{\c{c}}{\~a}o multitemporal de imagens,
avalia{\c{c}}{\~a}o da exatid{\~a}o,
automatiza{\c{c}}{\~a}o.",
abstract = "Environmental impacts related to sugarcane crop cultivation are
becoming a worldwide issue due to the great potential that ethanol
has to mitigate the emission of green house gases. However, the
sugarcane straw burning prior to harvest is still a critical
environmental problem that needs special attention. S{\~a}o Paulo
State represents more than 60% of the Brazilian sugarcane
production with 4.9 millions ha of cultivated area. The State
government together with the private sugarcane production sector
established in 2007 a protocol to gradually stop the sugarcane
straw burning up to 2014. Remote sensing images have the potential
to monitor the harvest management procedure identifying the fields
that were harvested with and without straw burning prior to
harvest. Currently, this identification and classification is
carried out using visual interpretation which provides high
quality results but is extremely tedious and time consuming. The
present work has the objective to propose an automated
classification procedure based on Spectral Temporal Response
Surfaces (STRS) to classify the recent harvested sugarcane into
burned and non-burned fields. This procedure is based on a
pixel-by-pixel classification considering the spectral-temporal
reflectance of each image pixel generating a thematic map. A
visual interpreted reference map was used to assess the automated
classification map accuracy which showed an overall index of
87.3%. The STRS classification procedure showed to be a promising
alternative to automate the generation of thematic maps of
harvested sugarcane with and without straw burning based on
spectral-temporal remote sensing images.",
conference-location = "Natal",
conference-year = "25-30 abr. 2009",
isbn = "978-85-17-00044-7",
language = "pt",
organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
ibi = "dpi.inpe.br/sbsr@80/2008/11.17.05.02.44",
url = "http://urlib.net/ibi/dpi.inpe.br/sbsr@80/2008/11.17.05.02.44",
targetfile = "279-286.pdf",
type = "Agricultura",
urlaccessdate = "30 abr. 2024"
}