Early warning systems development for agricultural drought assessment in Nigeria
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Early warning systems development for agricultural drought assessment in Nigeria Oluwatola Adedeji & Adeyemi Olusola & Godstime James & Halilu Ahmad Shaba & Israel Ropo Orimoloye & Sudhir Kumar Singh & Samuel Adelabu
Received: 14 July 2020 / Accepted: 3 November 2020 # Springer Nature Switzerland AG 2020
Abstract The existing drought monitoring mechanisms in the sub-Saharan Africa region mostly depend on the conventional methods of drought monitoring. These methods have limitations based on timeliness, objectivity, reliability, and adequacy. This study aims to identify the spread and frequency of drought in Nigeria using Remote Sensing/Geographic Information Systems techniques to determine the areas that are at risk of drought events within the country. The study further develops a web-GIS application platform that provides drought early warning signals. Monthly NOAA-AVHRR Pathfinder NDVI images of 1 km by 1 km spatial resolution and MODIS with a spatial resolution of 500 m by 500 m were used in this study together with rainfall data from O. Adedeji : G. James : H. A. Shaba Department of Strategic Space Applications, National Space Research and Development Agency (NASRDA), Abuja, Nigeria
25 synoptic stations covering 32 years. The spatiotemporal variation of drought showed that drought occurred at different times of the year in all parts of the country with the highest drought risk in the northeastern parts. The map view showed that the high drought risk covered 5.98% (55,312 km2) of the country’s landmass, while low drought risk covered 42.4% (391,881 km2) and very low drought risk areas 51.5% (476,578 km2). Results revealed that a strong relationship exists between annual rainfall and seasonintegrated NDVI (r2 = 0.6). Based on the spatiotemporal distribution and frequency of droughts in Nigeria, drought monitoring using remote sensing techniques of VCI and NDVI could play an invaluable role in food security and drought preparedness. The map view from the web-based drought monitoring system, developed in this study, is accessible through localhost.
A. Olusola (*) : S. Adelabu Department of Geography, University of the Free State, Bloemfontein, South Africa e-mail: [email protected]
Keywords Drought . NOAA-AVHRR . NDVI . MODIS . Spatio-temporal
I. R. Orimoloye Centre for Environmental Management, University of the Free State, Bloemfontein, South Africa
Introduction
I. R. Orimoloye Department of Geography and Environmental Science, University of Fort Hare, Alice, South Africa S. K. Singh K. Banerjee Centre of Atmospheric & Ocean Studies, IIDS, Nehru Science Centre, University of Allahabad, Prayagraj, Uttar Pradesh 211002, India
Early warning systems are globally becoming a prerequisite for an effective disaster reduction implementation plan. These are ensembles of toolkits needed to ensure a proactive design that could tackle headlong the impact of natural disasters be it flood, fire, hurricane, drought, dust storm, pest and diseases, etc. The design of early warning systems varies and the components are
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