Influence of Building Information Modelling (BIM) on Engineering Contract Management in Nairobi, Kenya

Building Information Modelling (BIM) is a technology and a process that has brought changes in the construction’s traditional procurement system. Kenya lacks contractual guidelines on implementation of BIM;this makes the adoption of BIM slow and difficult. Previous research has identified a gap in contractual relationships, roles and resulting risks. The objectives of this study were to investigate BIM adoption in Nairobi and to investigate the influence of BIM on Engineering Contract Management (ECM) in Nairobi Kenya. The survey research was a descriptive study with 175 responsive questionnaires. Respondents comprised of Civil Engineers, Construction Project Managers, Architects, Quantity Surveyors, Contractors and Facility Managers. Data was collected through self-administered questionnaire and in-depth interview. Descriptive analytics, correlation and Exploratory factor analysis methods were used to analyse quantitative data. Qualitative data was analysed thematically. It emerged that adoption level was at 56.6% and shallow understanding of BIM capabilities remains to be a barrier to its adoption and implementation. It also emerged that BIM improves ECM;when time, cost, quality, collaboration and return on investment improve, ECM becomes easier. Latent factors found in BIM and ECM relationship were Legal Implications, awareness and knowledge, efficiency, versatility, mandate and leadership, and competitiveness. Further, the study found out that BIM influence on ECM demands for establishment of standards, guidelines, policy, legal framework, and regulations, which can be achieved by amending the public procurement act which dictates the operation of all the other standard forms of contract. Further research should be conducted to measure whether the understanding of BIM had positively improved.

Examining Rate of Built-Up Areas on the Vegetation Cover along River Riara Riparian within Kiambu Town, Kenya

Urban river riparian spaces and their natural systems are valuable to urban dwellers;but are increasingly affected and ruined by human activities and in particular, urbanization processes. In this research, land sat and sentinel satellite imagery apt for change detection in vegetation cover, both landsat and sentinel imagery, covering the period between 1970 and 2021 in epochs of 1973, 1984, 1993, 2003, 2015 and 2021 years were used to establish the correlation between vegetation cover and built-up area along River Riara river reserve. The images were analysed to extract the built-up areas along the river reserve, including the buildings, and the rate of human settlements, which influenced vegetation cover. Normalized Difference Built-Up Index (NDBI) and Normalized Difference Vegetation Index (NDVI) were computed using the Short-Wave Infrared (SWIR) and the Near Infra-Red (NIR) bands to show the rate of change over the years. Results indicate NDVI values were high, compared to NDBI values along river Riara in the years 1973 and 1993 implying that there was more vegetation cover then. However, in the year 2021, the NDVI indicated the highest value at 0.88, with the complementary NDBI indicating the highest NDBI value at 0.47. This represents a significant increase in built-up areas since 2015 more than in previous epochs. Either, there was a significant increase in NDBI values, from 0.24 in 1993 to 0.47 in 2021. More so, the R-squared value at 0.80 informed 80% relationship between NDBI and NDVI values indicating a negative correlation.