The study examined urban warming in Port Harcourt Metropolis and Environs. The data used for this study were generated from field observation at fixed points on different land use types in the urban canopy between January to December 2017. Analysis of Variance was used to determine the differences in temperature across the various land use types. Thus, the temperature across different land use types from the city center to the rural fringes varied at the range of 4.8°C with a mean temperature value of 30.1°C. Urban warming was higher on the first three days of the week with a variation of 3.3°C and mean value of 5°C across the weekdays. However, urban warming increased at the rate of 0.1-0.20C per decade with 3.5% rise in population contributed by poor vegetation of the area. As a result, the city exceeded the recommended heat comfort threshold of 27°C temperature and +0.5°C-2.5°C urban warming value indicating that human comfort was compromised. Commercial and high residential areas had the highest urban heat effect across the different land use types. The result indicated that there was significant temperature variation across the different land use types. It was observed that increase in temperature does not imply a proportional increase in urban warming across different land use types. It is, therefore, recommended that policymakers, environmental practitioners as well as friends of the earth should adopt urban planning and management strategies using tree planting and general urban-greening approach in order to intervene urban warming in Port Harcourt Metropolis and Environs without further delay.
This study analysed the land-use and land-cover transition of Warri vegetation zone of the Niger Delta Region over the last four decades using Landsat imageries of 1975, 1987 and 2015 with the aid of Remote Sensing (RS) techniques and Geographic Information System (GIS). The study area covered 187 km2 and four land use/land cover types where analysed: Mangrove, non-mangrove, water body, and Urban area. The results show that as at 1975, out of the total area of 187 km2, mangrove-covered 63.28 km2 which was 33.8%, non-mangrove covered 87.01 km2 which was 46.5%, water bodies covered 9.7 km2 which was 5.2% and Urban settlements covered 27.01 km2 which was 14.4%. By 2015, Mangrove covered 37.5 km2 which was 20.1%, non-mangrove covered 45.7 km2 which was 24.4%, water bodies covered 19 km2 which was 10% and Urban settlements covered 84.7km2 which were 45.3%. The results show a rapid and haphazard increase in urban areas, while a reduction in mangrove and non-mangrove vegetation. This is as a result of Urbanization, oil and gas exploration and other anthropogenic activities. Kappa coefficient was used to estimate the accuracy of the classification process and an average of 93% accuracy was recorded for the three years of study. The annual rate of change was calculated and used to project the likely state of land-use and land-cover in Warri metropolis by the year 2030 if current trends and practices are not hindered. The annual rate of change for mangrove was -0.64km2 per annum and Non-mangrove was -1.03 km2 per annum while Urban settlement experienced an increase and an annual rate of change of 1.44 km2 per annum. The rate of vegetation loss over the past four decades and the annual rate of change is of notable concern and the need to implement conservation strategies, urban planning and sustainable development practices is paramount to prevent a complete loss of vegetation sometime in the future.
Every society has certain groups of people who are more susceptible to risk due to lack of capacity to prevent it, which makes them vulnerable. Malaria is one of such infectious diseases that imposes a substantial burden on vulnerable populations. The objectives of this study is to map and analyze spatial pattern of sub-domains of social vulnerability to malaria risk in Katsina-Ala Local Government Area (LGA) of Benue State Nigeria, model and analyze areas of social vulnerability based on the sub-domains. Based on the review of related literature, a holistic risk and vulnerability framework was adopted to guide the assessment of social vulnerability to malaria risk in the study area. Stratified systematic non-aligned sampling technique was used to collect data on social vulnerability to malaria risk from three hundred and ten (310) households using structured questionnaire and GPS device. Empirical Bayesian Kriging model tool of Geostatistical analyst and Zonal statistical extension tools of ArcGis 10.2 were used for the model. Results revealed a heterogeneous spatial pattern of social vulnerability to malaria across the entire study area, Lack of capacity to anticipate malaria has highest influence with mean value of 0.70 on a scale of 0 to 1; social vulnerability to malaria risk in the study area is high with mean value of 2.51 on a scale of 1 to 4. The study recommends a holistic approach that focuses on the vulnerable group and a paradigm shift in attacking the anopheles mosquito that causes the disease and increasing the capacity of the victims to withstand malaria risk.
An Agro-ecological (AEZ) zone describes it’s all characteristics about those phenomena which are related with agriculture such as temperature, rainfall, humidity, soil quality, soil fertility, crop pattern of a specific region. This study was done to find out irrigation distribution, crop pattern, and a relation between them. 12 AEZ units divided in a study area on the basis of topography, soil characteristics and development possibility from H. Brammer’s research “Agroecological aspects on agricultural research of Bangladesh”. In this study, data were collected by questionnaire survey, official documents and irrigation machine's locations data were collected by using GPS machine and Google earth. Irrigation distribution maps were created by inserting location data into XY data input on ArcGIS 10. Comparing satellite images of different time of a year from Google earth, Crop pattern map has produced. The result here shown in Domar upazila found 4242 irrigation machines including electric pump, diesel pump and deep tubewell and also found relation between irrigation systems and crop pattern. In findings, there mainly diesel pump used in AEZ unit 1, AEZ unit 5 and AEZ Unit 12 and these AEZ units are dominated by Potato, Maize, Groundnut, Chili and Tobacco cultivation and rest AEZ units are dominated by Boro cultivation where used deep tubewell and electric pump. This research helps to compare irrigation systems of different AEZ units and ensure the proper irrigation system. Proper distribution of irrigation systems according to AEZ units improve the agricultural production and also improve the socio-economic condition.
Aims: The study aims to identify wetlands from different study epochs using remote sensing images and also detect any changes in their extent or existence; correlate changes with nearby land use and land cover over time; identify wetland losses within the stipulated epochs; and, also project future levels of degradation (up to 2026) based on the trend observed between 1996 and 2016.
Place and Duration of Study: The study area covers Makurdi LGA in Benue State, Nigeria. The study focused between the periods 1996 through 2016 to 2026.
Methodology: To estimate the land use/cover change in Makurdi, Landsat ETM, ETM+ and OLI satellite data for 1996, 2006 and 2016, were respectively utilised. The study adapted the Kappa index for assessing the accuracy of the land use/cover maps generated from the analysis to improve the efficiency of results. An accuracy level of 80 to 91% was achieved. The land consumption rate (LCR) and land absorption coefficient (LAC) were applied to establish the role population increase plays in the rate of land consumption over specific spatio-temporal scales.
Results: The results reveal an overall significant increase in built-up area and other land uses at the expense of wetlands from 26.3% in 1996 to 18.1% in 2016. Further analysis includes the land consumption rate (LCR) and land absorption coefficient (LAC) which reveals the role of population expansion in the recorded levels of wetland losses recorded in this study. The study projects a further decline of wetland cover by 33.15 km2 (or by 22.57%) in 2026 if steps are not instituted to control the current rate of decline.
Conclusion: Given the findings and limitations of the study, some critical suggestions are made for further studies in line with the red list index (RLI) and to align with and incorporate into policy the strategic need to adopt the provisions of the SDGs (especially goal 15) at the level of Makurdi.