Ndemera, Rudo Hilda2024-11-162024-11-162023Ndemera, Rudo Hilda. (2023). Estimating rooftop solar energy potential using spatial radiation models and thermal remote sensing: The case of Witwatersrand University. [Master's dissertation, University of the Witwatersrand, Johannesburg]. https://hdl.handle.net/10539/42620https://hdl.handle.net/10539/42620A research report submitted in fulfilment of the requirements for the degree of Master of Science (in Geographical Information Systems and Remote Sensing), to the Faculty of Science, School of Geography, Archaeology & Environmental Studies, University of the Witwatersrand, Johannesburg, 2023.The main purpose of this research was to estimate the University of Witwatersrand building’s rooftop solar energy potential using the GIS-based solar Area Solar Radiation (ASR) analyst upward hemispherical view shed algorithm. The two major datasets used in this research for rooftop solar energy potential modelling are building footprint data and the Digital Surface Model. Building footprint data, specifically rooftop area was extracted using machine learning CNTK unified toolkit and deep neural networks. The data was presented as individual polygon shape files for each building. The high-resolution Digital Surface Model imagery was sourced from the Advanced Land Observation Satellite. Pre-processing of the imagery was done for atmospheric correction. The DSM was then used in the Area Solar Radiation model to create an upward view shed for every point on the study area which is essential for computing solar radiation maps. The efficiency of using this algorithm is that it considers the shading effects caused by surrounding topography and surrounding man-made features, alterations in the azimuth angle and the position of the sun. Apart from the incoming solar radiation reaching the rooftops, the elevation and orientation of the rooftop cells limit the solar panel tilt angle and intensity of the incoming solar radiation, respectively. These factors were used in setting the suitability criteria together with solar radiation for the identification of suitable rooftop cells in this research. The relationship between land surface temperature and solar radiation values was assessed to determine if it can be used as an indicator for solar panel efficiency. Results from this research indicate that the University of Witwatersrand receives high levels of incoming solar radiation and has a high solar energy rooftop generation capacity that can meet the energy demand on campus. To improve accuracy of the research results, a drone could have been used to measure insolation across the study area to improve the spatial resolution. However, this was not possible due to various restrictions.en©2023 University of the Witwatersrand, Johannesburg. All rights reserved. The copyright in this work vests in the University of the Witwatersrand, Johannesburg. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of University of the Witwatersrand, Johannesburg.Solar energyGIS-based solar Area Solar Radiation (ASR)Digital Surface model (DS)Area Solar Radiation model (ASR)University of the Witwatersrand, JohannesburgUCTDSDG-13: Climate actionDissertationUniversity of the Witwatersrand, Johannesburg