File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Conference Paper: Estimation of crop yield at the regional scale from MODIS observations

TitleEstimation of crop yield at the regional scale from MODIS observations
Authors
Liang, S.Fang, HongliangTeasdale, JohnCavigelli, MichelHoogenboom, Gerrit
KeywordsCrop yield
Data assimilation; modis
Remote sensing
Issue Date2004
Citation
International Geoscience and Remote Sensing Symposium (IGARSS), 2004, v. 3, p. 1625-1628 How to Cite?
DOI: http://dx.doi.org/10.1109/IGARSS.2004.1370640
AbstractThis study presents some preliminary results on estimating crop yield at the regional scale from MODIS (Medium resolution imaging spectroradiometer) data using the data assimilation method. MODIS data products include leaf area index (LAI) and enhanced vegetation index (EVI). The crop growth models of DSSAT were used in this study, which are driven by weather, soil and crop management data. Some of the variables of the models were adjusted through data assimilation algorithms for accurate prediction of crop yields.
Persistent Identifierhttp://hdl.handle.net/10722/321951

 

DC FieldValueLanguage
dc.contributor.authorLiang, S.-
dc.contributor.authorFang, Hongliang-
dc.contributor.authorTeasdale, John-
dc.contributor.authorCavigelli, Michel-
dc.contributor.authorHoogenboom, Gerrit-
dc.date.accessioned2022-11-03T02:22:35Z-
dc.date.available2022-11-03T02:22:35Z-
dc.date.issued2004-
dc.identifier.citationInternational Geoscience and Remote Sensing Symposium (IGARSS), 2004, v. 3, p. 1625-1628-
dc.identifier.urihttp://hdl.handle.net/10722/321951-
dc.description.abstractThis study presents some preliminary results on estimating crop yield at the regional scale from MODIS (Medium resolution imaging spectroradiometer) data using the data assimilation method. MODIS data products include leaf area index (LAI) and enhanced vegetation index (EVI). The crop growth models of DSSAT were used in this study, which are driven by weather, soil and crop management data. Some of the variables of the models were adjusted through data assimilation algorithms for accurate prediction of crop yields.-
dc.languageeng-
dc.relation.ispartofInternational Geoscience and Remote Sensing Symposium (IGARSS)-
dc.subjectCrop yield-
dc.subjectData assimilation; modis-
dc.subjectRemote sensing-
dc.titleEstimation of crop yield at the regional scale from MODIS observations-
dc.typeConference_Paper-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/IGARSS.2004.1370640-
dc.identifier.scopuseid_2-s2.0-15944403130-
dc.identifier.volume3-
dc.identifier.spage1625-
dc.identifier.epage1628-

Export via OAI-PMH Interface in XML Formats

OR

Export to Other Non-XML Formats