1. Identity statement | |
Reference Type | Journal Article |
Site | mtc-m21c.sid.inpe.br |
Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
Identifier | 8JMKD3MGP3W34R/436TFA5 |
Repository | sid.inpe.br/mtc-m21c/2020/09.02.13.17 (restricted access) |
Last Update | 2020:09.02.13.17.01 (UTC) administrator |
Metadata Repository | sid.inpe.br/mtc-m21c/2020/09.02.13.17.01 |
Metadata Last Update | 2022:01.04.01.35.20 (UTC) administrator |
DOI | 10.1109/JSTARS.2020.2994893 |
ISSN | 1939-1404 2151-1535 |
Citation Key | ShimabukuroArDuDuCaSaHo:2020:DiLaUs |
Title | Discriminating land use and land cover classes in Brazil based on the annual PROBA-V 100 m time series |
Year | 2020 |
Access Date | 2024, May 09 |
Type of Work | journal article |
Secondary Type | PRE PI |
Number of Files | 1 |
Size | 4018 KiB |
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2. Context | |
Author | 1 Shimabukuro, Yosio Edemir 2 Arai, Egídio 3 Duarte, Valdete 4 Dutra, Andeise Cerqueira 5 Cassol, Henrique Luis Godinho 6 Sano, Edson Eyji 7 Hoffmann, Tânia Beatriz |
Resume Identifier | 1 8JMKD3MGP5W/3C9JJCQ 2 8JMKD3MGP5W/3C9JGUP 3 8JMKD3MGP5W/3C9JJAU |
ORCID | 1 0000-0002-1469-8433 2 3 4 0000-0002-4454-7732 5 0000-0001-6728-4712 6 0000-0001-5760-556X 7 0000-0002-8246-5666 |
Group | 1 DIDSR-CGOBT-INPE-MCTIC-GOV-BR 2 DIDSR-CGOBT-INPE-MCTIC-GOV-BR 3 DIDSR-CGOBT-INPE-MCTIC-GOV-BR 4 SER-SRE-SESPG-INPE-MCTIC-GOV-BR 5 SER-SRE-SESPG-INPE-MCTIC-GOV-BR 6 7 SER-SRE-SESPG-INPE-MCTIC-GOV-BR |
Affiliation | 1 Instituto Nacional de Pesquisas Espaciais (INPE) 2 Instituto Nacional de Pesquisas Espaciais (INPE) 3 Instituto Nacional de Pesquisas Espaciais (INPE) 4 Instituto Nacional de Pesquisas Espaciais (INPE) 5 Instituto Nacional de Pesquisas Espaciais (INPE) 6 Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA) 7 Instituto Nacional de Pesquisas Espaciais (INPE) |
Author e-Mail Address | 1 yosio@dsr.inpe.br 2 egidio@dsr.inpe.br 3 valdete.duarte@inpe.br 4 andeise.dutra@inpe.br 5 henrique@dsr.inpe.br 6 edson.sano@embrapa.br 7 tania.hoffmann@inpe.br |
Journal | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Volume | 13 |
Pages | 3409-3420 |
History (UTC) | 2020-09-02 13:17:01 :: simone -> administrator :: 2022-01-04 01:35:20 :: administrator -> simone :: 2020 |
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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 | —Fraction images image processing linear spectral mixing model (LSMM) random forest (RF) |
Abstract | Brazil, with more than 8 million km2, presents six different biomes, ranging from natural grasslands (Pampa biome) to tropical rainfall forests (Amazônia biome), with different land-use types (mostly pasturelands and croplands) and pressures (mainly in the Cerrado biome). The objective of this article is to present a new method to discriminate the most representative land use and land cover (LULC) classes of Brazil, based on the PROBA-V images. The images were converted into vegetation, soil, and shade fraction images by applying the linear spectral mixing model. Then, the pixel-based, highest proportion, annual mosaics of the fraction images, and their corresponding standard deviation images were derived and classified using the random forest algorithm. The following LULC classes were considered: forestlands, shrublands, grasslands, croplands, pasturelands, water bodies, and others. An agreement analysis was conducted with two available LULC maps derived from the Landsat satellite, the MapBiomas, and the Finer Resolution Observation and Monitoring-Global Land Cover (FROM-GLC) projects. Forestlands (412 million ha) and pasturelands (242 million ha) were the two most representative LULC classes; and croplands accounted for 30 million ha. The results presented an overall agreement of 69% and 58% with the MapBiomas and FROM-GLC projects, respectively. The proposed method is a good alternative to support operational projects of LULC map production that are important for planning biodiversity conservation or environmentally sustainable land occupation. |
Area | SRE |
Arrangement 1 | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDSR > Discriminating land use... |
Arrangement 2 | urlib.net > BDMCI > Fonds > Produção pgr ATUAIS > SER > Discriminating land use... |
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 | en |
Target File | shimabukuro_discriminating.pdf |
User Group | simone |
Visibility | shown |
Archiving Policy | denypublisher allowfinaldraft |
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/3ER446E 8JMKD3MGPCW/3F3NU5S |
Dissemination | WEBSCI; IEEEXplore. |
Host Collection | urlib.net/www/2017/11.22.19.04 |
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6. Notes | |
Empty Fields | alternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel e-mailaddress format isbn label lineage mark mirrorrepository month nextedition notes number parameterlist parentrepositories previousedition previouslowerunit progress project readergroup rightsholder schedulinginformation secondarydate secondarykey secondarymark session shorttitle sponsor subject tertiarymark tertiarytype url |
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7. Description control | |
e-Mail (login) | simone |
update | |
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