Exposure Index for Maize yield vulnerability Modelling for Nigeria

Published: 8 Jul 2019 | Version 1 | DOI: 10.17632/7hnbgpkdc7.1

Description of this data

Exposure capture factors which could be manifested in the magnitude and intensity of long-term changes in climate (Intergovernmental Panel on Climate Change, 2007) and in this context factors with impact on agricultural production. Temperature and rainfall were used to capture the extent to which Maize is exposed to climate change. Data was sourced from the Centre for Environmental Data Analysis (CRU TS release 4), with data extracted for 1941 - 2015. The data were processed within R (Version 3.4.2), within this environment the mean (temperature and rainfall) for northern and southern parts of the country were computed. The growing season for Maize in the north spans from May to September while in the south it starts from March and ends in August (FAO, 2018). Furthermore, long (1941 – 2015) and short (1961 – 2015) term averages for the respective growing season were computed for each of the regions. Following the computation of the long and short-term averages, exposure was computed as the ratio of the long-term to the short-term averages. With exposure index for rainfall and temperature computed separately, the two were added to get the combined exposure index. A high value indicates high exposure to climate variability.
In this dataset, the exposure index is presented in raster format (Geotiff) to allow for easy processing across GIS software. In addition, the boundaries of the northern and the southern regions were also included as shapefiles.

Experiment data files

Latest version

  • Version 1


    Published: 2019-07-08

    DOI: 10.17632/7hnbgpkdc7.1

    Cite this dataset

    Lawal, Olanrewaju (2019), “Exposure Index for Maize yield vulnerability Modelling for Nigeria”, Mendeley Data, v1 http://dx.doi.org/10.17632/7hnbgpkdc7.1


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University of Port Harcourt Faculty of Social Sciences


Spatial Analysis, Climate Change Impact, Modelling, Crop Yield


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