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1. Identity statement
Reference TypeJournal Article
Sitemtc-m21c.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W34R/43F8FGB
Repositorysid.inpe.br/mtc-m21c/2020/10.23.14.03
Last Update2020:10.23.14.03.31 (UTC) simone
Metadata Repositorysid.inpe.br/mtc-m21c/2020/10.23.14.03.31
Metadata Last Update2024:01.23.14.36.59 (UTC) simone
DOI10.3390/ijgi9100564
ISSN2220-9964
Labelself-archiving-INPE-MCTIC-GOV-BR
Citation KeyBarbozaCastilloTASRSBOE:2020:MoWiNo
TitleMonitoring wildfires in the northeastern peruvian amazon using landsat-8 and sentinel-2 imagery in the GEE platform
Year2020
MonthOct.
Access Date2024, May 18
Type of Workjournal article
Secondary TypePRE PI
Number of Files1
Size3806 KiB
2. Context
Author1 Barboza Castillo, Elgar
2 Turpo Cayo, Efrain Yury
3 Almeida, Cláudia Maria de
4 Salas López, Rolando
5 Rojas Briceño, Nilton Beltrán
6 Silva López, Jhonsy Omar
7 Barrena Gurbillón, Miguel Ángel
8 Oliva, Manuel
9 Espinoza-Villar, Raul
Resume Identifier1
2
3 8JMKD3MGP5W/3C9JGS3
ORCID1 0000-0002-9628-8138
2 0000-0002-6691-9867
3 0000-0002-6523-3169
4 0000-0003-2184-6761
5 0000-0002-5352-6140
6 0000-0002-2618-7526
7 0000-0002-4200-4101
8
9 0000-0002-1355-9060
Group1
2
3 DIDSR-CGOBT-INPE-MCTIC-GOV-BR
Affiliation1 Universidad Nacional Toribio Rodríguez de Mendoza de Amazonas (UNTRM)
2 Universidad Nacional Agraria La Molina
3 Instituto Nacional de Pesquisas Espaciais (INPE)
4 Universidad Nacional Toribio Rodríguez de Mendoza de Amazonas (UNTRM)
5 Universidad Nacional Toribio Rodríguez de Mendoza de Amazonas (UNTRM)
6 Universidad Nacional Toribio Rodríguez de Mendoza de Amazonas (UNTRM)
7 Universidad Nacional Toribio Rodríguez de Mendoza de Amazonas (UNTRM)
8 Universidad Nacional Toribio Rodríguez de Mendoza de Amazonas (UNTRM)
9 Universidad Nacional Agraria La Molina
Author e-Mail Address1 ebarboza@indes-ces.edu.pe
2 eturpo@lamolina.edu.pe
3 claudia.almeida@inpe.br
4 rsalas@indes-ces.edu.pe
5 nrojas@indes-ces.edu.pe
6 jsilva@indes-ces.edu.pe
7 miguel.barrena@untrm.edu.pe
8 soliva@indes-ces.edu.pe
9 respinoza@lamolina.edu.pe
JournalISPRS International Journal of Geo-Information
Volume9
Number10
Pagese564
Secondary MarkB3_GEOCIÊNCIAS B5_CIÊNCIAS_AMBIENTAIS
History (UTC)2020-10-23 14:03:32 :: simone -> administrator ::
2020-10-23 14:03:32 :: administrator -> simone :: 2020
2020-10-23 14:05:22 :: simone -> administrator :: 2020
2021-01-04 13:26:48 :: administrator -> self-uploading-INPE-MCTI-GOV-BR :: 2020
2021-04-08 18:16:06 :: self-uploading-INPE-MCTI-GOV-BR -> simone :: 2020
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
Keywordsremote sensing
GIS
spectral analysis
burn severity
forests
vegetation cover
biodiversity
AbstractDuring the latest decades, the Amazon has experienced a great loss of vegetation cover, in many cases as a direct consequence of wildfires, which became a problem at local, national, and global scales, leading to economic, social, and environmental impacts. Hence, this study is committed to developing a routine for monitoring fires in the vegetation cover relying on recent multitemporal data (20172019) of Landsat-8 and Sentinel-2 imagery using the cloud-based Google Earth Engine (GEE) platform. In order to assess the burnt areas (BA), spectral indices were employed, such as the Normalized Burn Ratio (NBR), Normalized Burn Ratio 2 (NBR2), and Mid-Infrared Burn Index (MIRBI). All these indices were applied for BA assessment according to appropriate thresholds. Additionally, to reduce confusion between burnt areas and other land cover classes, further indices were used, like those considering the temporal differences between pre and post-fire conditions: differential Mid-Infrared Burn Index (dMIRBI), differential Normalized Burn Ratio (dNBR), differential Normalized Burn Ratio 2 (dNBR2), and differential Near-Infrared (dNIR). The calculated BA by Sentinel-2 was larger during the three-year investigation span (16.55, 78.50, and 67.19 km2 ) and of greater detail (detected small areas) than the BA extracted by Landsat-8 (16.39, 6.24, and 32.93 km2 ). The routine for monitoring wildfires presented in this work is based on a sequence of decision rules. This enables the detection and monitoring of burnt vegetation cover and has been originally applied to an experiment in the northeastern Peruvian Amazon. The results obtained by the two satellites imagery are compared in terms of accuracy metrics and level of detail (size of BA patches). The accuracy for Landsat-8 and Sentinel-2 in 2017, 2018, and 2019 varied from 82.791.4% to 94.598.5%, respectively.
AreaSRE
Arrangementurlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDSR > Monitoring wildfires in...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGP3W34R/43F8FGB
zipped data URLhttp://urlib.net/zip/8JMKD3MGP3W34R/43F8FGB
Languageen
Target Filecastillo-monitoring.pdf
User Groupsimone
Reader Groupadministrator
simone
Visibilityshown
Archiving Policyallowpublisher allowfinaldraft
Update Permissionnot transferred
5. Allied materials
Next Higher Units8JMKD3MGPCW/3ER446E
Citing Item Listsid.inpe.br/bibdigital/2013/09.13.21.11 2
sid.inpe.br/mtc-m21/2012/07.13.14.43.49 1
DisseminationPORTALCAPES
Host Collectionurlib.net/www/2017/11.22.19.04
6. Notes
NotesPrêmio CAPES Elsevier 2023 - ODS 8: Trabalho decente e crescimento econômico
Empty Fieldsalternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel e-mailaddress format isbn lineage mark mirrorrepository nextedition parameterlist parentrepositories previousedition previouslowerunit progress project readpermission rightsholder schedulinginformation secondarydate secondarykey session shorttitle sponsor subject tertiarymark tertiarytype url
7. Description control
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