Integrated Climate–Vegetation–Agricultural Dataset for Maize Yield Modeling in West Africa (2010–2022)

This dataset provides a fully integrated climate–vegetation–agricultural dataset for maize yield modeling across five West African countries (Ghana, Burkina Faso, Nigeria, Côte d’Ivoire, and Mali) from 2010 to 2022. The dataset integrates FAOSTAT agricultural data, NASA POWER climate variables, and MODIS NDVI satellite observations. It includes maize yield, vegetation condition (NDVI), rainfall indicators, temperature variables, irrigation, and pesticide use. Variables:- maize_yield_kg_ha (maize productivity)- ndvi (vegetation condition)- rain_total (annual rainfall proxy)- wet_days and heavy_rain_days (rainfall intensity indicators)- temp_mean, temp_max, temp_min, temp_std (temperature dynamics)- irrigation_ha (irrigated area)- pesticides_tonnes (input intensity) The dataset is structured for econometric modeling, machine learning, and explainable AI (e.g., SHAP) to analyze climate–vegetation–yield relationships in Sub-Saharan Africa. All variables are harmonized at country-year level and cleaned for analysis.