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Please use this identifier to cite or link to this item: http://117.252.14.250:8080/jspui/handle/123456789/4836
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dc.contributor.authorBoken, Vijendra K.-
dc.contributor.authorHaque, C. E.-
dc.date.accessioned2020-09-15T20:20:57Z-
dc.date.available2020-09-15T20:20:57Z-
dc.date.issued2009-
dc.identifier.urihttp://117.252.14.250:8080/jspui/handle/123456789/4836-
dc.description.abstractAn early warning model had been developed using two variables derived from rainfall data to predict agricultural drought for Jodhpur district of Rajasthan, India. The model explained up to 74.1% of the variation in the pearl millet's yield (i.e., the production per unit area). This model was later modified by including a variable derived from a soil moisture index. In this paper, an approach is described to further improve the model by including a variable derived from the MODerate Imaging Spectroradiometer (MODIS) satellite data. It was found that the 16 day Normalized Difference Vegetation Index (NDVI) derived from the MODIS data acquired during May—June could be a potential variable for further improving the model and drought management.en_US
dc.language.isoenen_US
dc.publisherAllied Publishers Pvt. Limited, New Delhien_US
dc.subjectFlooden_US
dc.subjectDraughten_US
dc.subjectMODIS Satellite Dataen_US
dc.title84-Modifying a Drought Early Warning Model Using MODIS Satellite Data.en_US
dc.typeOtheren_US
Appears in Collections:Proceedings of the International Conference on Water, Environment, Energy and Society (WEES-2009), 12-16 January 2009 at New Delhi, India, Vol.-2

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