Assessing the spatio-temporal variability of NDVI and VCI as indices of crops productivity in Ethiopia: a remote sensing approach

This study aims at characterizing agricultural drought in Ethiopia and understanding the effects of on crop yield. Monthly, seasonal annual Normalized Difference Vegetation Index (NDVI) Condition (VCI) values were calculated using MODIS (MOD13Q1) from year 2003 to 2017. The relationships between NDVI, VCI, yield examined predict possibility impacts productivity. We found that VCI NDVI data provides consistent spatially explicit information for operational monitoring Ethiopia. Results also indicated most extreme recent years occurred 2003, 2004, 2008, 2009, 2015. These findings show mild severe droughts have a great chance occurrence However, only has significant crops. food crops used this include cereals, legumes, tubers. It was observed cereals such as (Zea mays), teff (Eragrostis tef), haricot beans (Phaseolus vulgaris) are more sensitive when compared tubers sweet potato (Ipomoea batatas) taro (Colocasia esculenta). Thus, preparedness programs need pay attention cultivation these under conditions. HighlightsNDVI patterns easily discriminate legumes tuber crops.45% 43% variability respectively maize is explained by patterns.The studied (Teff, Maize, Sweet Taro) less discriminable variation.Drought strategies should encourage farmers cultivate instead cereals.The PMARE value Taro exceeded model acceptable range.