Bonface-Osoro/geosafi-consav

This is a repositary for geospatial viability assessment of satellite and fiber connectivity options for Sub-Sahara African Vulnerable Population (Geosafi-consav)) # A geospatial Assessment of Fiber, Mobile and Satellite Connectivity Options for Sub-Sahara African Vulnerable Population (geosafi-consav) Evidently, several broadband options exist to connect the unconnected. Mobile broadband provides a cheaper way of connecting the unconnected as is currently the most popular option in SSA. However, the challenging business times and market failure in sparsely populated regions with low ARPU hinders its deployment in those areas. Satellites provide an alternative means of covering all the remote areas at no additional investment cost, but the user terminal and monthly charges may limit its applicability unless government steps in through subsidies and incentives. Furthermore, the growing number of LEO constellations raises the key concerns on environmental impacts associated with launching of thousands of satellites for achieving global coverage. Alternatively, fixed fiber provides an option for connecting some of the unconnected areas through innovative network layout such as Fiber-to-the Neighborhood (FTTnb) architecture. Unlike satellite, fixed fiber is considered as one of the greenest forms of broadband capable of providing descent speeds. In this dissertation an open source integrated geospatial model is developed for estimating the capacity, coverage, cost and emissions of satellite, fiber, and mobile broadband systems in connecting the population below the poverty line and uncovered by 2G, 3G and 4G mobile network in SSA. Therefore, the research questions are articulated as follows: 1) What is the number of people living below US$ 1.9, US$, 3.2 and US$ 5.5 a day in SSA? 2) What is the number of people uncovered by 2G, 3G and 4G mobile network signal in SSA? 3) What is the number, location and spatial distribution of people living below the poverty line (US$ 1.9, US$ 3.2, and US$ 5.5 a day) and simultaneously uncovered by mobile network signal (2G, 3G and 4G) in SSA. Methodology ============== Integrated modeling metho …