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1. Identity statement
Reference TypeJournal Article
Sitemtc-m21c.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W34R/3SMPMRB
Repositorysid.inpe.br/mtc-m21c/2019/02.07.15.51   (restricted access)
Last Update2019:02.07.15.51.06 (UTC) simone
Metadata Repositorysid.inpe.br/mtc-m21c/2019/02.07.15.51.06
Metadata Last Update2020:01.06.11.42.09 (UTC) administrator
DOI10.18637/jss.v088.i05
ISSN1548-7660
Citation KeyMausCamaAppePebe:2019:TiDyTi
TitledtwSat: time-weighted dynamic time warping for satellite image time series analysis in R
Year2019
MonthJan.
Access Date2024, May 18
Type of Workjournal article
Secondary TypePRE PI
Number of Files1
Size1066 KiB
2. Context
Author1 Maus, Victor Wegner
2 Camara, Gilberto
3 Appel, Marius
4 Pebesma, Edzer
Resume Identifier1
2 8JMKD3MGP5W/3C9JHB8
Group1
2 DIDPI-CGOBT-INPE-MCTIC-GOV-BR
Affiliation1 University of Münster
2 Instituto Nacional de Pesquisas Espaciais (INPE)
3 University of Münster
4 University of Münster
Author e-Mail Address1 vwmaus1@gmail.com
2 gilberto.camara@inpe.br
JournalJournal of Statistical Software
Volume88
Number5
Pages1-31
History (UTC)2019-02-07 15:51:27 :: simone -> administrator :: 2019
2019-03-11 12:09:42 :: administrator -> simone :: 2019
2019-06-18 17:19:22 :: simone -> administrator :: 2019
2020-01-06 11:42:09 :: administrator -> simone :: 2019
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
Keywordsdynamic programming
MODIS time series
land cover changes
crop monitoring
AbstractThe opening of large archives of satellite data such as LANDSAT, MODIS and the SENTINELs has given researchers unprecedented access to data, allowing them to better quantify and understand local and global land change. The need to analyze such large data sets has led to the development of automated and semi-automated methods for satellite image time series analysis. However, few of the proposed methods for remote sensing time series analysis are available as open source software. In this paper we present the R package dtwSat. This package provides an implementation of the time-weighted dynamic time warping method for land cover mapping using sequence of multi-band satellite images. Methods based on dynamic time warping are flexible to handle irregular sampling and out-of-phase time series, and they have achieved significant results in time series analysis. Package dtwSat is available from the Comprehensive R Archive Network (CRAN) and contributes to making methods for satellite time series analysis available to a larger audience. The package supports the full cycle of land cover classification using image time series, ranging from selecting temporal patterns to visualizing and assessing the results.
AreaSRE
Arrangementurlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDPI > dtwSat: time-weighted dynamic...
doc Directory Contentaccess
source Directory Contentthere are no files
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4. Conditions of access and use
Languageen
Target Filemaus_dtwsat.pdf
User Groupsimone
Reader Groupadministrator
simone
Visibilityshown
Read Permissiondeny from all and allow from 150.163
Update Permissionnot transferred
5. Allied materials
Next Higher Units8JMKD3MGPCW/3EQCCU5
Citing Item Listsid.inpe.br/bibdigital/2013/09.09.15.05 6
DisseminationWEBSCI; PORTALCAPES; SCOPUS.
Host Collectionurlib.net/www/2017/11.22.19.04
6. Notes
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7. Description control
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