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Spatial data management for livestock distribution in Ethiopia

Abstract

Ethiopia has the largest livestock population in Africa. It is estimated at 105 million tropical livestock units, which includes 49.3 million heads of cattle, 47 million heads of sheep and goat, 8.3 million equines, 760 thousand camels and a poultry population of 38.13 million. The sector contributes to the livelihood of 60-70% of the Ethiopian population - this translates into approximately 44-52 million people whose subsidiary needs and economic activities rely on livestock production. Understanding the spatial distribution of livestock species is crucial in order to devise a feasible and geographically targeted livestock development policy. The aim of this study is to identify the research gap on the spatial distribution of livestock in LIVES project and to fill the gap by reviewing different literatures and related works. Besides, we proposed and developed a web-based spatial data management application for the LIVES project that makes use of researchers and academicians to have a ground reference to make further research and improve the internal operations of the organization, raises community satisfaction, and simplifies spatial data management and exchange. In order to conduct and justify this project we reviewed different journal articles and related works. In addition we have discussed with the GIS expert of LIVES project. In the mean time we have also collected livestock shape files from the LIVES project so as to use as an input to the proposed prototype web based application. Through the course of this project we were able to observer and identify that the LIVES project handles and manages their spatial data using ArcGIS Desktop application that lacks to handle and render up-to-date and quality livestock information via the web. We believed that having a web based application is necessary to permit timely livestock information dissemination, easy access, and render up-to-date livestock information to the ix public. Furthermore, it improves the efficiency of spatial data management and provides quality of services through the web

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