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KOBRA - Dokumentenserver der Universität Kassel  → Fachbereiche  → FB 11 / Ökologische Agrarwissenschaften  → Wirtschafts-, Sozial- und Lebensmittelwissenschaften  → Fachgebiet Ökologische Lebensmittelqualität und Ernährungskultur  → Future of Food: Journal on Food, Agriculture & Society  → Vol 4, No 3 (2016) 

Please use this identifier to cite or link to this item: http://nbn-resolving.de/urn:nbn:de:hebis:34-2016061350401

Title: Assessing the impact of agricultural drought on maize prices in Kenya with the approach of the SPOT-VEGETATION NDVI remote sensing
Authors: Shuaibu, Sakirat M.Ogbodo, John A.Wasige, Ejiet J.Mashi, Sani A.
???metadata.dc.subject.ddc???: 630 - Landwirtschaft, Veterinärmedizin (Agriculture)
Issue Date: 23-Dec-2016
Publisher: Department of Organic Food Quality and Food Culture at the University of Kassel, Germany and Federation of German Scientists (VDW)
Citation: In: Future of Food: Journal on Food, Agriculture and Society. Witzenhausen : University of Kassel, Department of Organic Food Quality and Food Culture. - Vol. 4, No. 3 (2016), S. 8 - 18
Abstract: The high cost of maize in Kenya is basically driven by East African regional commodity demand forces and agricultural drought. The production of maize, which is a common staple food in Kenya, is greatly affected by agricultural drought. However, calculations of drought risk and impact on maize production in Kenya is limited by the scarcity of reliable rainfall data. The objective of this study was to apply a novel hyperspectral remote sensing method to modelling temporal fluctuations of maize production and prices in five markets in Kenya. SPOT-VEGETATION NDVI time series were corrected for seasonal effects by computing the standardized NDVI anomalies. The maize residual price time series was further related to the NDVI seasonal anomalies using a multiple linear regression modelling approach. The result shows a moderately strong positive relationship (0.67) between residual price series and global maize prices. Maize prices were high during drought periods (i.e. negative NDVI anomalies) and low during wet seasons (i.e. positive NDVI anomalies). This study concludes that NDVI is a good index for monitoring the evolution of maize prices and food security emergency planning in Kenya. To obtain a very strong correlation for the relationship between the wholesale maize price and the global maize price, future research could consider adding other price-driving factors into the regression models.
URI: urn:nbn:de:hebis:34-2016061350401
ISSN: 2197-411X
Appears in Collections:Vol 4, No 3 (2016)

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