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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitemarte2.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP6W34M/3PSLTAL
Repositorysid.inpe.br/marte2/2017/10.27.13.14.33
Last Update2017:10.27.13.14.33 (UTC) banon
Metadata Repositorysid.inpe.br/marte2/2017/10.27.13.14.34
Metadata Last Update2018:06.06.03.07.33 (UTC) administrator
ISBN978-85-17-00088-1
Label59877
Citation KeyCarvalhoCarvSantReze:2017:UsTiSe
TitleUsing time series with object-image NDVI/TM for monitoring land cover dynamics in the Brazilian Amazon
FormatInternet
Year2017
Access Date2024, Apr. 16
Secondary TypePRE CN
Number of Files1
Size812 KiB
2. Context
Author1 Carvalho, Nathália Silva de
2 Carvalho, Luis Marcelo Tavares de
3 Santiago, Thais Muniz Ottoni
4 Rezende, José Luiz Pereira
Author e-Mail Address1 nathalia.bioufla@gmail.com
EditorGherardi, Douglas Francisco Marcolino
Aragão, Luiz Eduardo Oliveira e Cruz de
e-Mail Addressdaniela.seki@inpe.br
Conference NameSimpósio Brasileiro de Sensoriamento Remoto, 18 (SBSR)
Conference LocationSantos
Date28-31 maio 2017
PublisherInstituto Nacional de Pesquisas Espaciais (INPE)
Publisher CitySão José dos Campos
Pages3632-3639
Book TitleAnais
OrganizationInstituto Nacional de Pesquisas Espaciais (INPE)
History (UTC)2017-10-27 13:14:34 :: banon -> administrator ::
2018-06-06 03:07:33 :: administrator -> banon :: 2017
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
AbstractBiomes 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.
AreaSRE
TypePaisagens naturais
Arrangement 1urlib.net > BDMCI > Fonds > SBSR > SBSR 18 > Using time series...
Arrangement 2urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDSR > SBSR 18 > Using time series...
Arrangement 3Projeto Memória 60... > Livros e livros editados > SBSR 18 > Using time series...
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGP6W34M/3PSLTAL
zipped data URLhttp://urlib.net/zip/8JMKD3MGP6W34M/3PSLTAL
Languageen
Target File59877.pdf
User Groupbanon
Visibilityshown
5. Allied materials
Mirror Repositoryurlib.net/www/2011/03.29.20.55
Next Higher Units8JMKD3MGP6W34M/3PMFNUS
Citing Item Listsid.inpe.br/marte2/2017/09.25.14.55 1
Host Collectiondpi.inpe.br/marte2/2013/05.17.15.03.06
6. Notes
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