@InProceedings{CarvalhoCarvSantReze:2017:UsTiSe,
author = "Carvalho, Nath{\'a}lia Silva de and Carvalho, Luis Marcelo
Tavares de and Santiago, Thais Muniz Ottoni and Rezende, Jos{\'e}
Luiz Pereira",
title = "Using time series with object-image NDVI/TM for monitoring land
cover dynamics in the Brazilian Amazon",
booktitle = "Anais...",
year = "2017",
editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz
Eduardo Oliveira e Cruz de",
pages = "3632--3639",
organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 18. (SBSR)",
publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
address = "S{\~a}o Jos{\'e} dos Campos",
abstract = "Biomes like the Amazon Rainforest are a challenge for change
detection analysis due to high frequency of clouds. Moreover, time
series analysis to change detection in Tropical Rainforests are
still recent. This work investigates how a TM/NDVI time series
constructed from object-images can help understand the
deforestation process in the Amazon Rainforest over 28 years. The
study area is located in the state of Mato Grosso, Brazil, within
the Arc of Deforestation. We used the bfastSpatial package to
obtain the mean annual behaviour of object-based time series from
1984 to 2011. Moreover, we have also detected deforestation in
2002, extracting the lower mean value of each object in this
period. To evaluate the proposed method, we compare the processing
time between a time series object-based and pixel level.
Deforestation initiated in the 90s, with an intensification of the
process in the early 2000s. The peak of deforestation observed
from this period can be related to an increase in agricultural
commodities prices, especially soybeans and meat in the early
2000s. The validation to deforestation detection in 2002 has
resulted in a producers accuracy of 85%. Construction of time
series by applying an object-based methodology reduced the
computational time in 95% and removed the influence of salt-pepper
effect. The combination of these factors, may have contributed to
the quality this result, representing a new approach for time
series analysis.",
conference-location = "Santos",
conference-year = "28-31 maio 2017",
isbn = "978-85-17-00088-1",
label = "59877",
language = "en",
organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
ibi = "8JMKD3MGP6W34M/3PSLTAL",
url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSLTAL",
targetfile = "59877.pdf",
type = "Paisagens naturais",
urlaccessdate = "28 abr. 2024"
}