@Article{DinizSSDLMMGNVMA:2015:NeAmNe,
author = "Diniz, Cesar Guerreiro and Souza, Arleson Antonio de Almeida and
Santos, Diogo Correa and Dias, Miriam Correa and Luz, Nelton
Cavalcante and Moraes, Douglas Rafael Vidal de and Maia, Janaina
Sant'Ana and Gomes, Alessandra Rodrigues and Narvaes, Igor da
Silva and Valeriano, Dalton de Morisson and Maurano, Luis Eduardo
Pinheiro and Adami, Marcos",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de
Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas
Espaciais (INPE)} and {Instituto Nacional de Pesquisas Espaciais
(INPE)} and {Instituto Nacional de Pesquisas Espaciais (INPE)} and
{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de
Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas
Espaciais (INPE)} and {Instituto Nacional de Pesquisas Espaciais
(INPE)} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
title = "DETER-B: the new Amazon near real-time deforestation detection
system",
journal = "IEEE Journal of Selected Topics in Applied Earth Observations and
Remote Sensing",
year = "2015",
volume = "8",
number = "7",
pages = "3619--3628",
month = "July",
keywords = ": Deforestation, Monitoring, Public policy, Remote sensing, Space
research, Area estimation, Detection capability, Detection system,
Early Warning System, Government investment, Monitoring system,
Near-real time, rainforest, Real time systems, deforestation,
early warning system, forestry policy, MODIS, monitoring system,
rainforest, real time, remote sensing, satellite imagery,
Amazonia, Brazil.",
abstract = "The Brazilian Legal Amazon (BLA), the largest global rainforest on
earth, contains nearly 30% of the rainforest on earth. Given the
regional complexity and dynamics, there are large government
investments focused on controlling and preventing deforestation.
The National Institute for Space Research (INPE) is currently
developing five complementary BLA monitoring systems, among which
the near real-time deforestation detection system (DETER) excels.
DETER employs MODIS 250 m imagery and almost daily revisit,
enabling an early warning system to support surveillance and
control of deforestation. The aim of this paper is to present the
methodology and results of the DETER based on AWIFS data, called
DETER-B. Supported by 56 m images, the new system is effective in
detecting deforestation smaller than 25 ha, concentrating 80% of
its total detections and 45% of the total mapped area in this
range. It also presents higher detection capability in identifying
areas between 25 and 100 ha. The area estimation per municipality
is statistically equal to those of the official deforestation data
(PRODES) and allows the identification of degradation and logging
patterns not observed with the traditional DETER system.",
doi = "10.1109/JSTARS.2015.2437075",
url = "http://dx.doi.org/10.1109/JSTARS.2015.2437075",
issn = "1939-1404 and 2151-1535",
language = "en",
urlaccessdate = "27 abr. 2024"
}