Please use this identifier to cite or link to this item: http://repository.kln.ac.lk/handle/123456789/13994
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dc.contributor.authorGamanayake, B.G.N.N.-
dc.contributor.authorKadupitiya, H.K.-
dc.contributor.authorWeerasinghe, V.P.A.-
dc.date.accessioned2016-08-15T06:30:29Z-
dc.date.available2016-08-15T06:30:29Z-
dc.date.issued2016-
dc.identifier.citationGamanayake, B.G.N.N., Kadupitiya, H.K., and V.P.A. Weerasinghe 2016. Agricultural drought assessment using MODIS satellite data in Kurunegala District. In: Proceedings of the International Symposium on Information and Communication Technology for Sustainable Development, 10-12 August 2016, V.P.A. Weerasinghe and W.M.D.N. Wijeyaratne (Eds.), p 46, Department of Zoology and Environmental Management, University of Kelaniya, Kelaniya, Sri Lanka 57pp.en_US
dc.identifier.isbn978-955-4563-83-4-
dc.identifier.urihttp://repository.kln.ac.lk/handle/123456789/13994-
dc.description.abstractDrought is a climatic anomaly characterized by long spell scarcity of water. Agricultural drought is usually defined by less availability of soil water to maintain crop and forage growth by the deficiency of normal precipitation over an identified period of time. Since drought is a creeping phenomenon which appears slowly and resulting web of impacts not only to agriculture but also for all other aspects, monitoring, forecasting, evaluating impact and proposing solutions to drought hit areas are challenging than other disasters. Distinct to point observations of ground data, remote sensing provides direct spatial information on vegetation stress that occur due to drought conditions. This facilitates the utilization of time series Vegetation Indices derived using time series satellite data for continuous monitoring of vegetation conditions and tracking drought occurrences. MOD13Q1 (250m, 16-day) satellite images, which contain NDVI (Normalized Difference Vegetation Index), were used in this study and Vegetation Condition Index (VCI) was calculated using ENVI 4.5 Remote Sensing software for agricultural drought monitoring in Kurunegala District during the year 2000-2015. Spatial variability of drought frequencies was evaluated and mapped using ILWIS 3.4 free software. Map accuracy was assessed using actual drought data available for Kurunegala district in the database of Disaster Management Center. According to the results, North and North-West parts of Kurunegala District were identified as severe agricultural drought prone areas. In order to enhance the accuracy, water mask was recommended.en_US
dc.language.isoenen_US
dc.publisherDepartment of Zoology and Environmental Management, University of Kelaniya, Kelaniya, Sri Lanka.en_US
dc.subjectAgricultural droughten_US
dc.subjectMODISen_US
dc.subjectNDVIen_US
dc.subjectVCIen_US
dc.subjectKurunegala Districten_US
dc.titleAgricultural drought assessment using MODIS satellite data in Kurunegala Districten_US
dc.typeArticleen_US
Appears in Collections:International Symposium on ICT for Sustainable Development (ICTSD 2016)

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