The relevance of accessibility in shaping transport planning has often been neglected, hampering on decisions to improve transport efficiency. This is increasingly becoming problematic, as they often impede on economic and technological developments. Many studies on accessibility assert that it is easier for public transport to reach an activity centre than it is for private transport. For this reason, the research compares travel time forecast and accessibility levels with private and public transports en route to commercial centres. The research involves a 21-day transport survey for private cars and public shuttles in Oforikrom district using Global Positioning System (GPS) probe to record the traffic performance indicators to be analyzed in a GIS environment. The results of the study display on a map the level of accessibility via the modes, and a comparative line plot of travel time with private and public transport. The study reveals that private cars in the district generally perform better than public shuttles on the level of accessibility, and travel time. The execution of the research shows that the convergence of choice of transport mode and travel time dynamics is crucial for policymakers to implement diverse transport modes and commuters to choose a mode that has low accessibility cost.
Forests provide immeasurable merits for the economies of most developing countries. Forests in developing countries experience harmful human-induced impacts such as unregulated removal of biodiversity and unsustainable land conversion. The Sefwi Wiawso District (SWD) located in Ghana, which includes portions of six protected forest reserves (FRs) such as Muro, Tano Suhien, Tano Suraw, Suhuma, Sui River, and Krokosua, is the subject of this study. The impacts of selected spatial variables on forest losses were examined using retrospective and predictive approaches. Past deforestation patterns were analyzed using classified Landsat 5 and 7 imagery from 1984 to 2017. Pixel areas in hectares (ha) from land use land cover (LULC) classifications were used to detect land cover classes that were vulnerable to potential loss. The study also carried out a simple forest prediction using the simple moving averages (SMA) forecasting model based on the past and present deforestation patterns from LULC classification. The results showed that 3587.49 hectares (ha) of protected forest cover was converted into agricultural lands and barelands. In addition, 2532.96 hectares (ha) was converted from close forest to nonforest land cover from 2000 to 2017, which is equivalent to a 16% reduction in close forest cover within the FRs in the SWD. This loss was also 11% higher than close forest areas between 2000 and 2010. SMA forecasting showed that from 2017 to 2024, 877.38 hectares (ha) of close forest resources will convert to open forest resources and other nonforest land cover. Subtle accessibility routes such as navigable rivers and unofficial roads are the key instigators of protected forest clearance in the Sefwi Wiawso Forest District (SWFD). The SWFD is surrounded by many communities and is susceptible to uncontrollable biodiversity removal due to lack of proper monitoring of agricultural practices, mining operations, fuelwood collection, and illegal hunting, which represents a means of livelihood for the forest fringe community dwellers. The research serves as a benchmark for similar studies in efforts to investigate, measure, and project land cover change in protected forest areas.
There has been an increasing concern about effects of global warming on rainfall. Negative impacts on rainfall affect the environment and socio-economic activities of nations, globally. Rainfall characteristics at the Upper East Region (UER) of Ghana in terms of temporal and spatial variability are investigated from 1981 to 2016 using rainfall data from Ghana Meteorological Agency (GMet) and Climate Hazards Group Infrared Precipitation with Station. Using cumulative residual analysis, Mann-Kendall (MK), Sen's slope, wavelet transform (WT) and principal component analysis (PCA) tests, the rainfall variability in UER was examined. Results showed that 1981, 1999, 2002 and 2013 were years of major changes in rainfall variation. The MK and Sen's slope showed that 55.71% of UER have decreasing monthly rainfall with 27.34% significant trend. Months April, May and June showed decreasing rainfall trends. Months July, August and September showed significant increasing rainfall trend. WT revealed a significant variation in the annual rainfall. PCA revealed that the spatial variability of rainfall in UER is very diverse with 33.76% of the variability located in the northeastern part. The findings serve as benchmark in providing in-depth understanding of rainfall variation in UER for water resource managers, agriculturalists and drought mitigation.
Background Breast lumps or lumpiness are a prevalent issue among women seeking guidance, with 40–70% reporting lumps or lumpiness. Any woman, regardless of age, who discovers a breast lump by self-examination, screening, or medical intervention begins to worry about developing breast cancer. Late stage of reporting suspected lumps is on the rise and this was hitted by the pandemic. The study examined factors that are associated breast lump and the risk on women who ever had breast lump. Method An institutional-based cross-sectional study was conducted on women who visited the facility for breast screening or other medical consultation. Closed-ended questionnaire was used to solicit information from 301 women within a period of six weeks. Chi-square and binary logistic regression model was used to determine the association and the risk respectively. Results Breast lump was dominant in women between 41–50 years and in those who do not have family history of breast cancer. The findings reveal that educational level [χ2 = 11.170; p = 0.011] and the practice of breast self-examination [χ2 = 7.998; p = 0.005] were significantly associated with breast lump. Married women were 0.764 less likely to have breast lump than those who are singles. Women between 31–40 years were 2 times more likely [AOR = 2.061, CI = 0.876–4.846] and those between 41–50 years 1 time more likely [AOR = 1.131,CI = 0.451–2.837] to have breast lump than women between 18–30 years. Conclusion Breast lump is predominant in women between 31–50 years. Factors associated with a woman having breast lump are educational background and the practice of breast self-examination. Surgeon managing a breast lump in women over 30 years old are encouraged to be extremely suspicious and cautious in order to detect and treat malignant lumps early.
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