Application of GIS and Remote Sensing for Delineation of Food Insecure Areas in South Omo Administrative Zone SNNPRS/Ethiopia

Abstract

Food insecurity is a matter of both limited food availability and restricted access to food. Food availability is the availability of sufficient quantities of food of appropriate quality, supplied through domestic production or imports. The main objective of this study is to detect and delineate of food insecure areas in South Omo Administrative Zone using remote sensing and GIS. The necessary information was generated from satellite images, meteorological data and other ground data. The data analysis technique evolved generation of major parameters to detect drought prevalence that determining food insecurity. Because there are numerous factors determining food insecurity, the researcher selected drought and land use land cover change as determinant factors from crop production. Deviations of NDVI from the long term mean and anomalies derived from Landsat 5 and 8 NDVI images for 12 different years were used for drought detection. The results were validated using ground truth data such as crop production, food aid beneficiaries and the amount of food aid distributed including the number. The drought severity level in the study area was detected by using Index's like Standard Precipitation index, Normalized Difference Vegetation Index and anomalies. These determinant factors were then weighted and overlaid in the ArcGIS environment to generate a map indicating food insecure areas. Of the total areas of the Zone 11.6 % is found to be generally food secure, 19 % moderately food insecure, 29.4% highly food insecure and 39.9 % is chronically food insecure for the existing Drought year. The result of the research indicated that food insecure areas can be mapped by both Administrative and ecological boundary, which could be very important during area targeting for food aid and solve the problem under of area targeting only traditional view. In the research it is recommended that delineation of food insecure areas using Remote Sensing and GIS at local level should be encouraged. This system could be scaled up at zonal and regional level after incorporating other factors determining food insecurity. In doing so, Wastage of resource was controlled and Facilitate Emergency response for real targeted areas and peoples what was there in the area before.