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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitemarte2.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP6W34M/3PSMFB5
Repositorysid.inpe.br/marte2/2017/10.27.16.17
Last Update2017:10.27.16.17.02 (UTC) banon
Metadata Repositorysid.inpe.br/marte2/2017/10.27.16.17.03
Metadata Last Update2018:06.06.03.12.07 (UTC) administrator
ISBN978-85-17-00088-1
Label59365
Citation KeyXaudSantMartXaud:2017:PrImSA
TitleProcessamento de imagem SAR (Banda L) para detecção histórica de áreas florestais degradadas por incêndios recorrentes em Roraima
FormatInternet
Year2017
Access Date2024, Apr. 24
Secondary TypePRE CN
Number of Files1
Size1248 KiB
2. Context
Author1 Xaud, Haron Abrahim Magalhães
2 Santos, João Roberto dos
3 Martins, Flora da Silva Ramos Vieira
4 Xaud, Maristela Ramalho
Resume Identifier1
2 8JMKD3MGP5W/3C9JHF4
Author e-Mail Address1 haron.xaud@embrapa.br
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
Pages7216-7223
Book TitleAnais
OrganizationInstituto Nacional de Pesquisas Espaciais (INPE)
History (UTC)2017-10-27 16:17:03 :: banon -> administrator ::
2018-06-06 03:12:07 :: administrator -> banon :: 2017
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
AbstractThis paper aims to analyse the historical images of ALOS/PALSAR data (L Band) as an alternative to monitoring degradation of tropical forests affected by fires in the Northernmost Amazon Region. The sites of this study are located in the Apiaú Region, State of Roraima, Brazil. The study area was burned irregularly in 1998, 2003 and 2007 fires. The post-fire image (Jan.2008) was obtained in HH polarization. We ortoretified the PALSAR data and generated Amplitude and Intensity images. Additionally it were generated 13 textural data based on occurrence and co-occurrence matrix. Using Object-Based Image Analysis (OBIA) we segmented a 2007 Landsat TM image (as reference) to obtain objects that were described by 15 attributes derived from SAR images plus the standard deviation (SD) of each one, totalizing 30 attributes per object. We selected training and reference samples divided into 5 classes: (FN) unburned forests; (FQ1B) forests affected by 1 fire-low intensity; (FQ1A) forests affected by 1 fire-high intensity; (FQ2) forests affected by 2 fires; (FQ3) forests affected by 3 fires. We optimized the selection of PALSAR attributes to obtain the best separability among classes using a feature space optimization tool in OBIA based on Nearest Neighbor classifier. From the 30 attributes derived from PALSAR image, the results highlighted the best attributes (images) to detect degraded areas by recurrent fires; eight of them obtained from SD of textures and amplitude images.
AreaSRE
TypeDegradação de florestas
Arrangement 1urlib.net > BDMCI > Fonds > SBSR > SBSR 18 > Processamento de imagem...
Arrangement 2urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDSR > SBSR 18 > Processamento de imagem...
Arrangement 3Projeto Memória 60... > Livros e livros editados > SBSR 18 > Processamento de imagem...
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGP6W34M/3PSMFB5
zipped data URLhttp://urlib.net/zip/8JMKD3MGP6W34M/3PSMFB5
Languagept
Target File59365.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 3
Host Collectiondpi.inpe.br/marte2/2013/05.17.15.03.06
6. Notes
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