Refereed Journals

The construction industry plays an important role in contributing to the economy and development worldwide. The state of affairs concerning health and safety in the construction industry needs attention. In most countries, the industry is the second largest contributor to Gross Domestic Product (GDP) after agriculture. However, despite the importance of the construction industry for the national economy, the activities in the industry sadly pose serious health and safety risks to workers and users of construction facilities. The study therefore aims to examine the health and safety management practices relating to construction operatives. A comprehensive review was conducted using Scopus, Web of science, Litmaps and Research Rabbit databases to examine the health and safety management practices of construction operatives in the last two decades. Content analysis was conducted using the 17 documents retrieved from the database search. The study identified behaviour and attitude of workers towards safety, communication, training and safety programmes as the main findings. The study provides practical knowledge to construction stakeholders in minimising health and safety risk to construction operatives to ensure sustainability. It will also help the scientific community to know what still needs to be done to further advance knowledge on health and safety management practices.

The use of models for predicting asphalt pavement temperature tends to have limited applicability in regions with environmental conditions significantly different from those under which the models were developed. This study developed two asphalt pavement temperature prediction models for the West African tropical country of Ghana. The study locations were Kumasi and Tamale, in the Forest and Savannah climatic zones, respectively. Mid-depth asphalt layer and surface temperature data were measured in both cities for 1 year (May 2022–April 2023). Two non-linear regression models were calibrated using data collected on two newly rehabilitated asphalt roads and validated using an independent dataset collected on two different roads in the same cities. The validated models predicted asphalt pavement temperatures with a high level of accuracy, as indicated by the low model errors (root mean square error ranged from 1.924 to 2.679 °C and mean percentage error from 0.037 to 0.295%) and high adjusted coefficient of determination values, which ranged from 0.919 to 0.920. Future research efforts in improving the proposed models should include data collected at additional locations and over a longer duration.

Incorporating smart methodologies in cadastral surveying is improving the land acquisition system in Ghana. Traditional cadastral surveying is time-consuming and, if not planned out well, could cost a fortune to survey larger land areas. In a recent project, a cadastral map was produced for a large area in just 20% of the proposed duration thanks to the use of mobile applications by local townsfolk in the cadastral surveying process.

The aim was to prepare a cadastral plan for 21,000 acres (approx. 8,500 hectares) of land situated at Jomoro in the Western Region of Ghana. The land to be surveyed is generally mountainous with lush green vegetation, farms, towns, villages and roads, and is bounded on the south by the Atlantic Ocean. The main occupations of inhabitants are coconut farming and fishing.

The traditional way of preparing a cadastral plan would have involved sending a survey party ahead of the actual survey to locate and clear the entire boundary in order to mount pillars. This would have been an arduous task, possibly involving the use of handheld GPS to locate the boundary points and the deployment of labourers to clear the line of sight where necessary. In an area with dense vegetation, it could take a whole day or more to survey 1km of boundary. The survey party would be made up of surveyors, local guides and labourers only; any other accompanying persons would be of little to no help in locating boundary pillars. The other time-consuming challenge would have been to identify the best and fastest accessible route to arrive at a boundary point. When it comes to routing, even experienced local guides are no match for today’s tools such as Google Earth.

This study investigated lane flow distribution on selected sections on the Kumasi – Accra multilane highway, with a specific focus on a section located in a built-up area, characterized by side frictions and driveways, and another in a non-built up area, characterized by flat terrain with no access or side friction. The study sought to (1) explore the lane flow distribution patterns under varying traffic conditions and roadway environmental types (urban and non-urban), and (2) investigate the combined effect of roadway and traffic conditions on lane flow distribution. Traffic volume data was extracted from video recordings made at the two study sites for two days. At the same time, vehicular speeds were measured with the use of a radar speed gun. The data were explored descriptively, after which multiple linear regression was employed to model the lane flow distribution in the median lane. The results indicated pronounced disparities in lane utilization between the two sites with different vehicle categories exhibiting distinct lane preferences. The model suggested that roadway environment type, proportion of motorcycles in the traffic stream, and total link flow significantly determine the proportion of traffic flow that travel in the median lane whereas the proportion of trotros and the average link speed have marginal influence. The findings emphasize the importance of considering local contextual factors and driver behaviors in modelling lane flow distribution, particularly in developing countries with heterogeneous roadway and traffic conditions.