Linear regression relationships between NDVI, vegetation and rainfall in Etosha National Park, Namibia

Estimations of 10-day interval green vegetation cover and biomass, 10-day interval cumulative rainfall, as well as annual rainfall are compared with 10-day interval and rainy season NDVI and MVC using linear regression analysis. Raw data were smoothed by averaging and removing dry season outliers. Results indicate that the ability of NDVI and MVC to predict green vegetation cover, cumulative rainfall and annual rainfall is poorer for raw data than for averaged, outlier-removed data. It is recommended that the standard error of the raw data predictions are used to indicate the fundamental error in these relationships, and that the equations of the averaged, outlier-removed data are used to indicate the fundamental strength of NDVI or MVC in predicting vegetation or rainfall. The practical use of integrated rainy season MVC images are discussed.