@InProceedings{SilvaFormShimSano:2011:MoDeDe,
author = "Silva, Gustavo Bayma Siqueira da and Formaggio, Antonio Roberto
and Shimabukuro, Yosio Edemir and Sano, Edson Eyji",
affiliation = "{Instituto Nacional de Pesquisas Espaciais - INPE} and {Instituto
Nacional de Pesquisas Espaciais - INPE} and {Instituto Nacional de
Pesquisas Espaciais - INPE} and {Embrapa Cerrados}",
title = "Monitoramento e detec{\c{c}}{\~a}o de desmatamentos no bioma
Cerrado matogrossense utilizando imagens de multisensores",
booktitle = "Anais...",
year = "2011",
editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio
Soares",
pages = "2849--2855",
organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 15. (SBSR).",
publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
address = "S{\~a}o Jos{\'e} dos Campos",
keywords = "monitoramento operacional, cobertura vegetal, forma{\c{c}}{\~a}o
florestal e sav{\^a}nica, modelo linear de mistura espectral,
operational monitoring system, vegetation cover, forestland and
shrubland formation, linear spectral mixing model.",
abstract = "In the last decades, Brazil has become a global agricultural power
and the Cerrado biome (Brazilian savanna) has been playing an
important role in the Brazilian agriculture growth. To better
analyze the biome human disturbance dynamics, it is necessary to
develop and adopt effective methods of assessment and monitoring
of land use and land cover changes. The goal is to provide
adequate land cover classifications and implement an operational
monitoring system in the Cerrado biome, since there is only a few
attempts to control the degradation of this biome. This monitoring
system can be accomplished using MODIS images, as this sensor has
great potential for studies about the seasonal dynamics of Cerrado
vegetation phytophysiognomies. Due to this new dynamics, the main
objective of this work was to apply the PRODES and DETER like
methodologies to detect and map deforestation in the Cerrado biome
of Mato Grosso State, Brazil, using Landsat and MODIS data. The
proposed methodology was able to detect correctly 65% of all MODIS
detected polygons; this represented 74% of estimated area of
deforestation. Also, it showed suitability to identify new
deforested areas in both shrubland and forestland areas with a
tendency to misclassify smaller polygons (< 50 ha) of
deforestation.",
conference-location = "Curitiba",
conference-year = "30 abr. - 5 maio 2011",
isbn = "{978-85-17-00056-0 (Internet)} and {978-85-17-00057-7 (DVD)}",
language = "pt",
organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
ibi = "3ERPFQRTRW/39ULFRS",
url = "http://urlib.net/ibi/3ERPFQRTRW/39ULFRS",
targetfile = "p0588.pdf",
type = "An{\'a}lise Florestal e Vegeta{\c{c}}{\~a}o",
urlaccessdate = "08 maio 2024"
}