1. Identity statement | |
Reference Type | Journal Article |
Site | mtc-m21d.sid.inpe.br |
Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
Identifier | 8JMKD3MGP3W34T/45D9KTP |
Repository | sid.inpe.br/mtc-m21d/2021/09.08.16.47 (restricted access) |
Last Update | 2021:09.08.16.47.42 (UTC) simone |
Metadata Repository | sid.inpe.br/mtc-m21d/2021/09.08.16.47.42 |
Metadata Last Update | 2022:04.03.22.27.34 (UTC) administrator |
ISSN | 2236-9716 |
Citation Key | SilvaCremBoggAlve:2021:InImOr |
Title | Integração de imagens orbitais ópticas e SAR com processamento em nuvem no mapeamento da cobertura da terra no cerrado |
Year | 2021 |
Month | Ago. |
Access Date | 2024, May 19 |
Type of Work | journal article |
Secondary Type | PRE PN |
Number of Files | 1 |
Size | 1667 KiB |
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2. Context | |
Author | 1 Silva, Angela Gabrielly Pires 2 Cremon, Édipo Henrique 3 Boggione, Giovanni de Araújo 4 Alves, Fábio Corrêa |
ORCID | 1 0000-0001-7759-9806 2 0000-0003-3174-7273 3 0000-0002-1675-6529 4 0000-0002-2941-8393 |
Group | 1 2 3 4 DIOTG-CGCT-INPE-MCTI-GOV-BR |
Affiliation | 1 Instituto Federal de Goiás (IFG) 2 Instituto Federal de Goiás (IFG) 3 Instituto Federal de Goiás (IFG) 4 Instituto Nacional de Pesquisas Espaciais (INPE) |
Author e-Mail Address | 1 angelagabrielly225@gmail.com 2 edipo.cremon@ifg.edu.br 3 giovanni.boggione@ifg.edu.br 4 alves.fabioc@gmail.com |
Journal | Revista Geoaraguaia |
Volume | 11 |
Number | esp. |
Pages | 85-106 |
Secondary Mark | B4_INTERDISCIPLINAR B4_HISTÓRIA B4_GEOGRAFIA B4_ENGENHARIAS_I |
History (UTC) | 2021-09-08 16:48:55 :: simone -> administrator :: 2021 2022-04-03 22:27:34 :: administrator -> simone :: 2021 |
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3. Content and structure | |
Is the master or a copy? | is the master |
Content Stage | completed |
Transferable | 1 |
Content Type | External Contribution |
Version Type | publisher |
Keywords | Google Earth Engine sensoriamento remoto integração de dados orbitais Random Forest aprendizado de máquina Google Earth Engine remote sensing orbital data integration Random Forest machine learning |
Abstract | O mapeamento da cobertura da terra é de suma importância para o monitoramento ambiental e gestão territorial. Séries temporais de radar de abertura sintética (SAR) do Sentinel-1 (S-1) e o sensor óptico MSI/Sentinel-2 (S-2) fornecem condições favoráveis para o mapeamento da cobertura da terra devido às suas resoluções espectrais, espaciais e temporais. Este trabalho parte do pressuposto que a combinação entre as séries temporais do S-1 e S-2 permite maior exatidão no mapeamento da cobertura da terra no bioma Cerrado. As imagens foram classificadas utilizando o algoritmo Random Forest na plataforma de processamento em nuvem Google Earth Engine. As classificações obtidas apenas com os dados S-2 (kappa = 89,99) foram melhores do que as obtidas com os dados S-1 (kappa = 75,78). A eficiência da classificação aumentou ao combinar os dados de ambas as missões S-1 e S-2 (kappa= 93,07). Os resultados obtidos neste trabalho sugerem que a banda do infravermelho de ondas curtas, a polarização VH dos dados SAR e os índices cellulose absorption index (CAI) e o Hall Cover foram as variáveis mais importantes no mapeamento da cobertura da terra do bioma Cerrado. ABSTRACT: The land cover mapping is of great relevance for the environmental monitoring and land management. Time series from the synthetic aperture radar (SAR) of Sentinel-1 (S-1) and the MSI/Sentinel-2 (S-2) optical sensor provide promising conditions for the land cover mapping due to their spectral, spatial and temporal resolutions. Here, we explored the hypothesis that the combination of S-1 and S-2 time series allows higher accuracy in the land cover mapping in Cerrado biome. The images were classified using the Random Forest algorithm in the Google Earth Engine cloud processing platform. The classifications obtained using only the S-2 data (kappa = 89.99) showed higher accuracy than those with the S-1 data (kappa = 75.78). The classification efficiency increased by combining the S-1 and S-2 data (kappa = 93.07). The results found here suggest that the shortwave infrared band, the VH polarization from SAR data, and the Cellulose absorption index (CAI) and Hall Cover index were the most significant variables in the land cover mapping of the Cerrado biome. |
Area | SRE |
doc Directory Content | access |
source Directory Content | there are no files |
agreement Directory Content | |
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4. Conditions of access and use | |
Language | pt |
Target File | silva_integracao.pdf |
User Group | simone |
Reader Group | administrator simone |
Visibility | shown |
Read Permission | deny from all and allow from 150.163 |
Update Permission | not transferred |
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5. Allied materials | |
Next Higher Units | 8JMKD3MGPCW/46KUATE |
Host Collection | urlib.net/www/2021/06.04.03.40 |
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6. Notes | |
Empty Fields | alternatejournal archivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel dissemination doi e-mailaddress format isbn label lineage mark mirrorrepository nextedition notes parameterlist parentrepositories previousedition previouslowerunit progress project resumeid rightsholder schedulinginformation secondarydate secondarykey session shorttitle sponsor subject tertiarymark tertiarytype url |
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7. Description control | |
e-Mail (login) | simone |
update | |
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