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1. Identity statement
Reference TypeJournal Article
Sitemtc-m21b.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W34P/3LG39AB
Repositorysid.inpe.br/mtc-m21b/2016/04.11.19.00
Last Update2016:04.11.19.02.00 (UTC) administrator
Metadata Repositorysid.inpe.br/mtc-m21b/2016/04.11.19.00.49
Metadata Last Update2018:06.04.02.40.42 (UTC) administrator
DOI10.3390/rs8010022
ISSN2072-4292
Citation KeyZhuLuVictDutr:2016:MaFrCr
TitleMapping fractional cropland distribution in Mato Grosso, Brazil using time series MODIS enhanced vegetation index and Landsat Thematic Mapper data
Year2016
Access Date2024, May 18
Type of Workjournal article
Secondary TypePRE PI
Number of Files1
Size5407 KiB
2. Context
Author1 Zhu, Changming
2 Lu, Dengsheng
3 Victoria, Daniel
4 Dutra, Luciano Vieira
Resume Identifier1
2
3
4 8JMKD3MGP5W/3C9JHMA
Group1
2
3
4 DPI-OBT-INPE-MCTI-GOV-BR
Affiliation1 Jiangsu Normal University
2 Michigan State University
3 Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA)
4 Instituto Nacional de Pesquisas Espaciais (INPE)
Author e-Mail Address1 zhuchangming@jsnu.edu.cn
2 luds@zafu.edu.cn
3 daniel.victoria@embrapa.br
4 dutra@dpi.inpe.br
JournalRemote Sensing
Volume8
Number1
PagesNumber 22
Secondary MarkB3_GEOGRAFIA B3_ENGENHARIAS_I B4_GEOCIÊNCIAS B4_CIÊNCIAS_AMBIENTAIS B5_CIÊNCIAS_AGRÁRIAS_I
History (UTC)2016-04-11 19:00:49 :: simone -> administrator ::
2018-06-04 02:40:42 :: administrator -> simone :: 2016
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
KeywordsCrop phenology analysis
Fractional cropland distribution
Landsat
Mato grosso
MODIS EVI
Seasonal dynamic index
AbstractMapping cropland distribution over large areas has attracted great attention in recent years, however, traditional pixel-based classification approaches produce high uncertainty in cropland area statistics. This study proposes a new approach to map fractional cropland distribution in Mato Grosso, Brazil using time series MODIS enhanced vegetation index (EVI) and Landsat Thematic Mapper (TM) data. The major steps include: (1) remove noise and clouds/shadows contamination using the Savizky-Gloay filter and temporal resampling algorithm based on the time series MODIS EVI data; (2) identify the best periods to extract croplands through crop phenology analysis; (3) develop a seasonal dynamic index (SDI) from the time series MODIS EVI data based on three key stages: sowing, growing, and harvest; and (4) develop a regression model to estimate cropland fraction based on the relationship between SDI and Landsat-derived fractional cropland data. The root mean squared error of 0.14 was obtained based on the analysis of randomly selected 500 sample plots. This research shows that the proposed approach is promising for rapidly mapping fractional cropland distribution in Mato Grosso, Brazil.
AreaSRE
Arrangementurlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDPI > Mapping fractional cropland...
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4. Conditions of access and use
data URLhttp://mtc-m21b.sid.inpe.br/ibi/8JMKD3MGP3W34P/3LG39AB
zipped data URLhttp://mtc-m21b.sid.inpe.br/zip/8JMKD3MGP3W34P/3LG39AB
Languageen
Target Filezhu_mapping.pdf
User Groupsimone
Reader Groupadministrator
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Visibilityshown
Archiving Policyallowpublisher allowfinaldraft
Update Permissionnot transferred
5. Allied materials
Mirror Repositoryurlib.net/www/2011/03.29.20.55
Next Higher Units8JMKD3MGPCW/3EQCCU5
Citing Item Listsid.inpe.br/mtc-m21/2012/07.13.14.53.50 1
sid.inpe.br/bibdigital/2013/09.09.15.05 1
DisseminationWEBSCI; PORTALCAPES; MGA; COMPENDEX; SCOPUS.
Host Collectionsid.inpe.br/mtc-m21b/2013/09.26.14.25.20
6. Notes
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