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dc.contributor.authorKiruki, Emily W
dc.description.abstractSolar energy is the cleanest source of renewable energy and has good prospects for future sustainable development. More also photovoltaic (PV) systems have become less costly and building rooftops have become attractive for local power production. Identifying rooftops suitable for solar energy systems over large geographic areas is needed for countries to obtain more accurate assessments of production potential and likely patterns of development. This project presents a method of estimating the optimal rooftop sites for off grid - connected solar panel cells in Nairobi using LIDAR data and high resolution satellite imagery. Roof aspect and slope was examined using ArcGIS. The methodology is semi-automatic since it was implemented as an ArcGIS model in Model Builder. In order to show its validity the model was applied in Parts of Ngara ward in Nairobi County with the criteria of slope and aspect used to locate suitable areas for installation of Photovoltaic system. The resultant suitable cells that met the conditions were combined to determine the most suitable rooftop to mount PV solar panels. Within my study area it was found that 53% of rooftop areas had suitable aspect, 31% of roof areas had suitable slope and overall 48% rooftop areas are suitable for PV systems. The result presented is a map showing the most suitable rooftop locations within the study area for solar panels installations. Other key factors to determine a suitable rooftop to mount photovoltaic solar panels i.e. shadow analysis and solar radiation were not considered in this study. It is therefore recommended that in a future study they could be incorporated.en_US
dc.publisherUniversity of Nairobien_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.subjectA Geospatial Approach for Estimating Optimalen_US
dc.titleA Geospatial Approach for Estimating Optimal (Rooftop) Sites for Off –grid Connected Photovoltaic (Pv) Cells in Part of Nairobi Central and Ngara, Nairobien_US

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Attribution-NonCommercial-NoDerivs 3.0 United States
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 United States