African Journal of Earth and Environmental Science

Assessment of Industrialized Building System (IBS) Skill-sets for Quality Housing in Kano Municipal, Kano State, Nigeria

2025-01-03T16:33:50+00:00

The slow pace and quality of housing delivery using the conventional approach is seen as setback in minimizing the housing deficit in Nigeria. The primary success parameters of every project are time, cost and quality.. The adoption of new technological advancement in the construction sector is seen as a key factor for achieving timely project delivery within budget. The aim of this study was to identify the challenges for adopting Industrial Building System (IBS) for Quality low-cost housing delivery in Kano Municipal construction sector. A quantitative approach was employed with a Delphi technique as a method of data collection to achieve research. The experts were identified through a snowball sampling technique. Twenty (20) questionnaires were administered to Delphi experts and 16 were returned (80%) in the construction industry. Descriptive statistics and mean score ranking was used to analyse the data using SPSS 22. Findings of the study indicates that poor skills and supervision by the developers, lack of availability of skilled labour, poor communication of design requirements by client are among the key factors that affect the quality of housing delivery through the use of conventional castin-situ. The challenges of IBS adoption identified were, high financial cost, lack of direct financial grants, lack of practical technical training, inadequate suppliers of prefabrication, no policy to promote prefabrication, due to the production process, it possess great potential for higher quality than the conventional method. Interestingly, stakeholders recommend the need to explore the application of IBS, as it is seen as a better technology that will minimize the huge Nigerian housing deficit and facilitate the industrialization of the construction industry.

Multi-Criteria Analysis for Flood Vulnerability in Auyo Local Government Area, Jigawa State, Nigeria

2025-01-03T17:11:29+00:00

Flood disaster is one of the multidimensional issues impacting on the physical, social, economic, and political lives of Auyo people. The aim of this study is to map out flood vulnerability in Auyo Local Government using Geographic Information System (GIS) Multi-criteria analysis with a view to evolving efficient adaptation strategies for sustainable development. ASTER Digital Elevation Model (DEM) was used for the generation of slope and elevation. Land use of the area were extracted from landsat image (2020), while data on soil types and texture based on FAO were sourced at the Centre for Dryland Agriculture Bayero University Kano. Weighted Overlay Analysis was conducted to integrate all the input parameters. The finding shows that about 29% (15512 ha) of the total area falls within the zones of high of flood vulnerability level especially dominating in the eastern part flowing onto most the rice cultivation lands. While about 40% (21040 ha) of the area falls within the moderate zone, 31% (16169 ha) falls within the low vulnerable zones especially on the western part of the area (mainly on the upland). The study concluded that apart from rainfall, slope and elevation are the major factors that triggers flooding in the area. The study recommends for pre-flood preparedness, proper planning by the policy makers and the development of sub-stations for monitoring of river flow both up and downstream areas.

Inter-Residential Cluster Variability and Deprivation Index for urban Green Spaces Distribution within Kano Metropolis

2025-01-03T18:14:51+00:00

Unequal distribution and exposure to urban green spaces in urban areas is receiving growing attention about its impact on human wellbeing. This researched is aimed at examining the interresidential cluster variability, deprivation and spatial injustice in the distribution of urban green spaces within Kano metropolis. Geospatial analysis was used in fishing out and computing the total area of green spaces within each residential cluster of Kano metropolis. Average green space are was used to determine areas experiencing deprivation. Cluster with above average green space area are not experiencing deprivation and those with below average are experiencing deprivation. The findings of the research revealed that there is unevenness in the distribution of urban green spaces within five residential clusters of Kano metropolis. Very High and Very Low Residential Clusters are experiencing serious deprivation in the distribution of urban green spaces. High, Medium and Low Residential Clusters are not experiencing deprivation. Medium Residential Cluster is found to be enjoying the highest green space extent amounting to 222 hectares. Very low Residential Cluster is the most deprived cluster with just 8.6 hectares of green spaces. Based on the findings of this research, it is found that majority of the people living within the metropolis are exposed to risks associated with lack of green spaces. It is recommended that Kano Metropolitan Development Authority should establish greenery at different places within the deprived clusters in order to ensure spatial justice in the distribution of urban green spaces.

Downscaling Rainfall at a Small Watershed Level in a Data Scarce Dryland Woodland Using the Regression Model

2025-09-18T14:43:14+00:00

Using a regression model, this study proposes a statistical strategy for downscaling rainfall data at a small watershed level in data-scarce dryland woods. Because dryland ecosystems are especially vulnerable to changes in precipitation patterns, accurate rainfall estimation is critical for successful water resource management and ecosystem conservation. Obtaining trustworthy rainfall data at small scales in a data-scarce environment, on the other hand, remains a difficulty. To overcome this issue, we offer a downscaling strategy that uses regression models' power to estimate rainfall at the local watershed level with readily available parameters. The study region is in dryland woods with few rainfall monitoring stations. Global Precipitation Climatology Centre (GPCC) data were downloaded from 1986 – 2005 to test the validity of the regression model in downscaling the rainfall. The regression model implemented in a stepwise operation uses auxiliary data such as locational and topographic features (altitude, latitude, and longitude) extracted from 90 m Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM), to establish a statistical link between large-scale rainfall measurements and local-scale factors. The trained regression model performance was then assessed using cross-validation procedures. The results show that the suggested downscaling method is excellent at capturing the spatiotemporal variability of rainfall within the small watershed. The predicted rainfall data were validated with the original gridded GPCC points, and the observed result shows that there was a very strong correlation for all the years at p > 0.05 significant level. The regression model successfully converts large-scale rainfall patterns into localized estimates, allowing for more accurate precipitation representation at a finer resolution. This data can help decision-makers in the dryland woodland with water distribution, land management, and ecological planning. This research advances the subject of hydrological modeling in dryland ecosystems by presenting a realistic method for downscaling rainfall data at the watershed level. The suggested regression model is a useful tool for filling data gaps, especially among conservationist who may not have the luxury of using complex tools for estimating rainfall

An Assessment of Woody Vegetation Structure in Protected Area Versus Farmed Parkland: A Case Study of Closed Settled Zone in Kano, Northern Nigeria.

2025-09-18T14:46:26+00:00

This article presents a comprehensive assessment of the woody vegetation structure in protected areas and farmed parklands in the Kano Closed Settled Zone, located in northern Nigeria. The study aims to investigate the impact of ownership on vegetation protection and conservation efforts. Through rigorous field surveys and data collection, various aspects of woody vegetation structure, including tree density, species composition, and canopy cover, were analyzed and compared between protected areas and farmed parklands. The results reveal a surprising trend, challenging the conventional understanding of protected areas as being superior in terms of conservation efforts. Contrary to expectations, the study finds that farmed parklands exhibit higher levels of vegetation protection compared to protected areas. This discrepancy is primarily attributed to the factor of ownership. Unlike protected areas that are often managed by external entities or government agencies, farmed parklands are owned and cared for by local communities or individuals. The sense of ownership and the need for sustainable resource utilization have fostered a higher level of vegetation protection and conservation efforts in the farmed parklands. The findings emphasize the significance of considering ownership and community involvement in conservation strategies. They suggest that traditional models of protected areas may not always be the most effective approach for sustainable vegetation management in certain contexts. Collaborative efforts between local communities, landowners, and conservation organizations should be prioritized to foster a sense of ownership and promote responsible resource utilization. This study contributes to the understanding of woody vegetation structure and conservation practices in the Kano Closed Settled Zone, highlighting the importance of integrating local communities and landowners into conservation initiatives. The findings provide valuable insights for policymakers, land managers, and conservationists in designing effective strategies that balance the needs of local communities with long-term ecological sustainability