Assessing the conditions of rural road networks in South Africa using visual observations and field-based manual measurements: A case study of four rural communities in Kwa-Zulu Natal

Abstract

The prioritization and improvement of rural road networks is important in developing countries in order to uplift the socioeconomic conditions experienced by communities. So far, limited information exists on the conditions of unpaved or gravels roads, particularly in rural areas and the associated implications to rural economies. The present study therefore used visual observations and field-based measurements to assess the physical, environmental and anthropogenic factors affecting Minor roads (R3), Collector roads (R4) and Local roads (R5) in four rural communities in the KwaZulu-Natal Province, South Africa. The function of these road classes is to provide access from homesteads to main roads that connect rural areas to towns. In this study, two classification methods were used to rate the severity and extent of each surface distress on each road class. Results indicate that there was more than one surface distresses identified and assessed on each road class within the selected communities. It was noted that all the road classes had moderate to severe surface distress, except for the R3 road class in Emazabekweni community, reflecting problems associated with poor drainage systems and maintenance. Visual observation and field-based methods are useful tools that can aid in identifying and assessing the physical conditions of unpaved roads, as well as possible environmental, physical and anthropogenic factors at interplay, especially in resource limited regions. This study recommended that road authorities should ensure that proper drainage systems should be well designed; constructed and maintained on all gravel roads in order to reduce surface deterioration associated with runoff.

Assessing the surface material quality of unpaved rural roads to understand susceptibility to surface deterioration. A case study of four rural areas in KwaZulu-Natal, South Africa

“…The findings of this study only provide results, which were obtained from an investigation conducted to assess surface material quality on unpaved rural roads in order to understand their susceptibility to surface deterioration. A study by Nkomo et al (2016) was recently conducted using visual observation and field-based measurements in order to assess the type, severity and extent of surface deterioration on the road classes, which were investigated in this research paper. The findings of this current paper forms part of the follow-up research conducted by Nkomo et al (2016).…”

Factor analysis of quality assurance practices in small and medium-sized road-construction projects: A South African perspective

“…These findings are consistent with similar results obtained for qualityassurances practices incorporated in the construction SMEs such Mofokeng & Thwala (2012); Obare et al (2016). Van Wyk (2003 summarised that, while project success still depends on formal project-management systems (project planning, cost control, and so on) and the availability of skilled people, the key point is that team members need to work with each other in a supportive setting in order to achieve successful project outcomes (Arditi & Gunaydin, 1997;Aigbavboa & Thwala, 2014); this leads to an increased ability for the designer and client to develop a shared understanding (Nkomo, Desai & Peerbhay, 2016). Leadership skills are important in leading the workforce (Kerzner, 2013).…”

Analysis of Free Road Data in Tanzania, Uganda and Kenya Using Free and Open Source Software

“…While several studies had the main focus just on the completeness (Zielstra et al 2011) other compared geometries, thematic attributes of road network data and their positional differences (Ludwig et al, 2011 Some researches were focused on the analysis of attributes assigned to road data (Leitner and Arsanjani, 2017). For instance, features referring to the seasonality of roads were useful while investigating access of population to these roads (Nkomo et al, 2016). According to Vincent (2018), missing that piece of information partially caused the failure of study, conveyed by The World Bank Group, that developed Rural Access Index (equal to SDGs indicator 9.1.1) in 2006.…”