@InProceedings{KuckKePaLiVaAr:2011:MaMu20,
author = "Kuck, Tahisa Neitzel and Keizer, Edwin Willem Hermanus and
Pacheco, Pablo and Lira, Roni Von Cascais de and Vasconcelos,
S{\^a}mia Amorim de and Arruda, Andr{\'e} N{\'o}brega de",
affiliation = "{Greenpeace – Campanha Amaz{\^o}nia} and {Greenpeace – Campanha
Amaz{\^o}nia} and {Greenpeace – Campanha Amaz{\^o}nia} and
{Greenpeace – Campanha Amaz{\^o}nia} and {Greenpeace – Campanha
Amaz{\^o}nia} and {Greenpeace – Campanha Amaz{\^o}nia}",
title = "Mapeamento multitemporal (2001-2009) do uso da terra no bioma
Amaz{\^o}nia do estado do Mato Grosso atrav{\'e}s de imagens
MODIS",
booktitle = "Anais...",
year = "2011",
editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio
Soares",
pages = "7776--7783",
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 = "remote sensing, LUCC, EVI, decision tree, sensoriamento remoto,
mudan{\c{c}}a de uso/cobertura da terra, EVI, {\'a}rvore de
decis{\~a}o.",
abstract = "Large scale agriculture and extensive cattle ranging are the main
drivers of deforestation within the Amazon are responsible for
158.310 km2 of forest cover loss since 2001. Although these two
activities represent significant importance within the context of
land use and land cover change and their impacts on greenhouse gas
emissions, there is still no adequate operational monitoring
system which provides high quality data and information on land
use change considering the spatial-temporal dynamics. This
information is crucial for territorial planning, zonation for use
and conservation, environmental monitoring, agricultural planning
and agro-business among others. The objective of this study by
Greenpeace was the development of a land use classification
methodology for the annual land use mapping within the Amazon
Biome covering the state of Mato Grosso, based on multitemporal
analysis of EVI (Enhanced Vegetation Index) values derived from
the MOD12Q1 product of the MODIS sensor. The classification was
implemented through the construction of a decision tree based on
knowledge differentiating the temporal behavior of EVI of the
different land use types. Field data collection, literature
analysis and medium to high resolution image interpretation were
the basis for land use differentiation. The obtained results were
validated and demonstrated excellent accuracies according to
literature. The methodology showed to be applicable for the
mapping of the principal land use types present within the study
area and permits to analyze interannual transitions to increase
our understanding of the land use dynamics within the Amazon
biome.",
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/39UFBGL",
url = "http://urlib.net/ibi/3ERPFQRTRW/39UFBGL",
targetfile = "p0541.pdf",
type = "Mudan{\c{c}}a de Uso e Cobertura da Terra",
urlaccessdate = "01 maio 2024"
}