Abstract

Abstract. Informal settlements, also known as slums or shanty towns, are characterised by rapid and unstructured expansion, poorly constructed buildings, and in some cases, they are on disputed land. Such settlements often lack basic services, such as electricity. As a result, informal settlement dwellers turn to hazardous alternative sources of energy, such as illegal electricity connections and paraffin. Solar power is a clean and safe alternative. However, informal settlements are often located on undesirable land on the urban fringe where the topography may hinder the use of solar energy. The high density of dwellings could also be a hindrance. Therefore, the solar potential needs to be assessed before any implementations are planned. Solar potential assessment functionality is generally available in geographic information system (GIS) products. The nature, cost and accessibility of datasets required for the assessment vary significantly. In this paper, we evaluate the results of solar potential assessments using GRASS (Geographic Resources Analysis Support System) for a number of different datasets. The assessments were done for two informal settlements in the City of Tshwane (South Africa): Alaska, which is nestled on a hill; and Phomolong, a densely populated settlement with a rather flat topography. The results show that solar potential assessments with open source GIS software and freely available data are feasible. This eliminates the need for lengthy and bureaucratic procurement processes and reduces the financial costs of assessing solar potential for informal settlements.

Highlights

  • In South Africa, informal settlements are a common occurrence due to rapid urbanization and lack of affordable housing (Richards et al, 2006)

  • Resampled to a 2m and 10m digital surface model (DSM) respectively, both including building footprints digitized from aerial photographs; and a 1m LiDAR dataset procured by the City of Tshwane Metropolitan Municipality

  • We evaluated the results of solar potential assessments using GRASS for four different datasets: a freely available 30m digital elevation model (DEM); the 30m DEM resampled to a 2m and 10m DSM respectively, both including building footprints digitized from aerial photographs; and a 1m LiDAR dataset procured by the City of Tshwane Metropolitan Municipality

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Summary

Introduction

In South Africa, informal settlements are a common occurrence due to rapid urbanization and lack of affordable housing (Richards et al, 2006). These settlements are often located in areas that are unoccupied and/or difficult to develop, and the dwellings are constructed from any available material, such as corrugated iron (Rautenbach et al, 2015). Informal settlement dwellers turn to hazardous alternatives, such as illegal electricity connections, which frequently result in electrocutions (Fuzile, 2017; Moodley, 2016). The removal of illegal connections has led to service delivery protests (Dawood, 2015; Khubisa, 2017)

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