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Despite the conservation importance of the Keta Lagoon Complex Ramsar Site (KLCRS), obtaining information on the extent and distribution of mangroves is challenging due to the unavailability of optical satellite data. This research explored Sentinel-1 radar data to provide information on mangrove distribution in the KLCRS. Global positioning system points from 443 training and 196 validation sites were used. In addition, focus group discussions and key informant interviews were used to corroborate information on mangrove distribution. Sentinel-1 data were processed for backscatter coefficients and two backscatter derivatives. These were stacked into a four-layer image composite and classified using a support vector machine. An overall classification accuracy of 89.28% was obtained. In addition, user and producer accuracies of 100 and 97.3% respectively were obtained for the mangrove class. The results show that mangroves occupy a total area of 41.02 km2 in the KLCRS and are mostly found around the Salo, Bomigo, Anyanui and Dzita communities. This study demonstrates the possibility of using Sentinel-1 imagery to map mangroves within the KLCRS. Thus, this study serves as a guideline for other data-constrained mangrove landscapes to map and monitor mangroves for conservation and restoration actions.

Solid waste receptacles siting is becoming increasingly difficult due to increase in population and infrastructure development that has limited available space for waste collection. This study focused on selection of environmentally friendly sites for waste receptacle placement in Kwame Nkrumah University of Science and Technology (KNUST) based on multi-criteria decision analysis in a geographic information system (GIS) environment. ArcGIS software was used in overlaying different thematic maps in order to generate suitable areas for siting communal containers and small bins. Environmental criteria considered include river bodies, vegetation, road network, buildings, car park and slope. The analytical hierarchy procedure was used to determine the weight of each criterion used in finding the suitable sites. The final suitability maps generated showed areas deemed suitable for siting communal containers and small bins. Out of the total land area of KNUST (10.35 km2), 0.86 km2 representing 8.31% was suitable for siting small bins. For communal containers, the final suitability map indicated that 1.69 km2 (16.33%) and 0.73 km2 (7.05%) of the total land area were suitable and most suitable sites respectively. The findings from this study serve as guidance tool for environmentally friendly solid waste receptacle siting and good health promotion with efficient land use planning.

Solid waste collection constitutes 60-80% of the total solid waste management cost. Reduction of solid waste collection cost can be achieved through route optimization in a geographic information system (GIS) environment. The purpose of this study was to generate optimized routes for solid waste collection on Kwame Nkrumah University of Science and Technology campus in Kumasi, Ghana. The study modelled the existing routes for a complete collection cycle using travel time criteria and generated optimized routes for same using an ArcGIS software. Validation of the optimized outcome (travel distance and travel time) was done by subjecting the solid waste collection trucks to the optimized routes. The results from the study showed significant reduction in total travel time from 1,000.75 mins to 855.70 mins for existing and optimized routes respectively, translating into saving of 14.5%. Total travel distance significantly reduced from 367.30 km to 334.20 km for existing and optimized routes respectively, representing saving of 9.0%. Significant savings in travel time and travel distance have implications on reduction of fuel and maintenance cost of institutional solid waste collection trucks. The results indicate that the application of GIS-based route optimization in solid waste collection can provide significant improvement in reduction of operating cost.

The Landsat mission which has existed over five decades has remained at the forefront of providing consistent moderate spatial and temporal resolution optical images of the earth. The failure of th...

Purpose The purpose of this paper was to determine the effect of route optimization on travel distance, travel time and fuel consumption of municipal solid waste (MSW) collection trucks. Design/methodology/approach The study modeled the existing waste collection routes in three local authorities in Ghana and proposed optimal routes using Esri’s ArcGIS Network Analyst Extension. The system generated optimal distances and times were validated by subjecting collection trucks to the optimal routes. Paired sample t-test was used to analyze the differences in means of the existing and optimal outcomes. The collected data were subjected to correlation and uncertainty analyses. Findings Results from the study indicated that weekly travel distance reduced by 81.27 km, translating into saving of 4.79 percent when trucks used the optimal routes. Travel time and fuel consumption reduced by 853.59 min and 145.86 L, making savings of 14.21 and 10.81 percent, respectively. Significant differences occurred between the means of the existing and optimal routes for travel time and fuel consumption, for each of the three local authorities. Research limitations/implications The study was conducted in Ghana using data collected from three local authorities. Practical implications Significant reduction of MSW collection cost can be achieved by waste management practitioners through route optimization. Originality/value The effect of route optimization on travel distance, travel time and fuel consumption has been established. Statistical analyses of the existing and optimal outcomes of the three local authorities have been provided. The findings from this study support the hypothesis that optimal routes reduce operating cost through savings in travel distance, travel time and fuel consumption.

Quantitative data on geographical accessibility to healthcare remain generally limited in sub-Saharan Africa. This study sought to generate quantitative evidence regarding health care access in the Ashanti region of Ghana. Dasymetric mapping technique and GIS tools were used to estimate the total population living within the World Health Organization (WHO)'s recommended 5 km distance to the nearest health facility. An estimated 81.4% of the population had access to general primary health care, 61.4% to secondary-level health care and, only 14.3% to tertiary health care. Despite the high levels of accessibility to general primary health care, accessibility remains poor in some selected districts, especially rural districts in the region. About 30% of the population are more likely to have to travel long distances to access healthcare, particularly specialist services which are available only at secondary and tertiary centres. There is the need for intensified efforts to address inequities in geographic accessibility to healthcare so as to minimise inequalities in health outcomes as well as achieve the desired improvements in population health.

This paper reviews the effect of applying optimization methods on the collection process of solid waste, with particular interest in mathematical programming and geographic information system approaches in developing countries. Mathematical programming approaches maximize or minimize an objective function for improvement in procedure, to ensure operational efficiency and also serve as decision support tools. They however provide partial solutions when implemented in reality and cannot fully handle road network constraints. Geographic information system approaches allow processing of additional considerations, often ignored in other methods, such as the street network modeling. Incorporating environmental pollution consideration is very challenging in this approach, the vehicle routing problem solver encountering limits for large data. For enhanced efficiency of the vehicle routing systems, studies should further focus on incorporating all network constraints, environmental pollution considerations, and impact of land use changes on routing.

Small reservoirs provide vital ecosystem services in the semi-arid part of Ghana. Their main role is the provisioning of water for irrigation in this water-scare part of the country. They also serve as source of water for fishing, recreation, drinking, and other domestic uses and play crucial roles in evaporation, water productivity, water scarcity mitigation and climate modulation in this area. As such, their accessibility by the populace is vital to their well-being. Also, their locations, surface area and capacity (volume) are required for water resources assessments and hydrological modelling. This work was done to map the distribution of the small reservoirs in the White Volta sub-basin in Ghana. The work assessed the accessibility of artificially built small reservoirs in the relevant communities using satellite images and ground information. The study used six Landsat 8 Operational Land Imager images covering the study area. Histogram thresholding technique was used to delineate the waterbodies from their adjacent uplands. Accuracy assessments were done through field observed data and Google Earth images. The method used produced a positional accuracy of 94%. The study estimated that there are approximately 254 small reservoirs of surface areas between 1 and 53 ha in the sub-basin. The combined surface area and volume of the small reservoirs were estimated to be 1585.265 ha and 21.154×106 m3 respectively. The study estimated only 35% of communities within the sub-basin have access to small reservoirs. The study concluded that cluster of communities and population density are the general determinants of the distribution of small reservoirs in the sub-basin. However, rainfall distribution and suitability of soil for large-scale crop production may also be some important factors dictating the distribution of small reservoirs in the White Volta sub-basin in Ghana.

The objective of this paper is to analyze the land surface temperatures (LST) derived from three satellite images as a proxy for urban heat island potential, through a peri-urban heat troughs (PuHT) to rural cool troughs (RuCT) continuum, concepts largely overlooked in the literature, in the Bosomtwe district of the Ashanti region of Ghana. Four Landsat satellite images from 2002, 2008 Enhanced Thematic Mapper+ (ETM+) and 2014 Landsat 8 Operational Land Imager and Thermal Infrared Sensor (OLI/TIRS) were geo-referenced and processed for classification using the maximum likelihood classifier algorithm in ERDAS Imagine 13. Land Use and Land Cover (LULC) transition analysis was performed in ArcMap for ArcGIS 10.2. Results indicate that, in order of importance, recent fallows and grasslands along with built up/bare land and concrete surfaces have been increasing in terms of coverage. A corresponding surface reflectance translated into LST values ranging between a minimum of 24oC (297K) to a maximum of 53oC (326K). Changing LULC types correlated with the land surface temperature fluxes, creating the RuCT and PuHT. This result explains the relatively substantial peri-urban land use dynamics in the district. Future studies should develop threshold values for RuCT and PuHT temperatures.

A wall-to-wall Earth observation (EO) data is required, as recommended by the Intergovernmental Panel on Climate Change, private sector organizations and major development partners, to allow for the implementation of forest monitoring commitments, and also to monitor commodity-led deforestation. However, a major limitation associated with the use of optical EO data in the high forest zone of Ghana is the presence of persistent cloud cover and the spectral limitations of segregating agroforestry cocoa (AFC) from open canopy forest (OCF) cover. The aim of the study was to investigate the synergistic use of Sentinel-1 (S1) and Sentinel-2 (S2) EO data to produce a Land Use Land Cover map which shows AFC and OCF as different land cover classes. It was hypothesized that, a hybrid method of spectral, radar and image objects will accurately segregate the different cocoa system from forest and other land use classes. The research was conducted in the Bia-Juaboso REDD + Hotspot Intervention Area in the cocoa-forest mosaic landscape within the High forest zone of Ghana. The S1 and S2 datasets were freely acquired for the periods January to March 2018. The S1 datasets were pre-processed from backscatter intensity values to the VV and VH bands. The S2 datasets were corrected for atmospheric effects, and cloud pixels were masked and filled using a temporal gap-filling method. Six vegetation indices (VIs) were extracted, and the Multiresolution Segmentation algorithm was used to derive image objects (IOs). The S2 bands, the six VIs, the S1 VV + VH data, and the IOs were stacked into 3 different multi-layer image dataset denoted with D (i.e. D1 = S2 + VIs; D2 = S2 + VIs + S1; and D3 = S2+VIs + S1+IOs). The three datasets were classified using Random Forest and 1228 training points. Overall accuracy (OA) and kappa (k) were calculated for the classification outcome using 615 independent validation points. McNemar's test ( χ ) was used to access the statistically significant difference between D1, D2 and D3. The results of the study show that, D3 significantly improved the overall classification output (OA = 89.76%, k = 0.877) compared to D1 (OA = 79.02%, k = 0.748; χ = 5.56, p-value = 0.018) and D2 (OA = 80.49%, k = 0.765; χ = 5.50, p-value = 0.019). Combining spectral pixels with image objects increases overall classification accuracy and specifically, the accuracy of isolating AFC from OCF. This research is significant because it will provide an improved decision support to government-led monitoring and the private sector's commitment to halt cocoa-driven deforestation. Furthermore, and most importantly, the map shows agroforestry cocoa separated from monoculture cocoa, which provides a tremendous boost to monitoring landscape-level improvements associated with the promotion and adoption of agroforestry in cocoa landscapes, as a climate-smart practice and also for monitoring various off-reserve landscape forest restoration activities.

The unfavorable effect of human disturbances in major river basins resulting in extensive variations in the ecosystem has necessitated this research within the Pra River Basin of Ghana. Knowledge about how individual land use influences water balance components will massively improve natural resources planning, management and sustainable development. Land use/cover change in the basin was evaluated by the assessment of six historical and one future land use/cover maps relating to the land use/cover stages in 1986, 2000, 2004, 2008, 2013, 2016 and 2025. The land use/cover maps were deployed to generate seven land use/cover scenarios relating to diverse states of land use/cover change in the basin which were then deployed to simulate the hydrological components. The Soil and Water Assessment Tool was deployed for hydrological simulation. The results revealed that there was a continuous increase in cropland, settlement and mining at the detriment of forest areas from 1986 to 2016, which is expected to continue into 2025. The variations in land use/land cover brought about increment of surface runoff (124.51%) and water yield (40.13%), and reduced baseflow (30.08%) and ET (13.248%). Conversely, the results showed a reduction in surface runoff and water yield during dry season and increased baseflow and evapotranspiration during wet season. These trends are expected to further increase in 2025. Moreover, settlement and mining are the major contributors to changes in water balance components. These results show how important control of land use/cover is in order to maintain water balance components to guarantee water accessibility for all generations.

The Lower Pra River Basin (LPRB), located in the forest zone of southern Ghana has experienced changes due to variability in precipitation and diverse anthropogenic activities. Therefore, to maintain the functions of the ecosystem for water resources management, planning and sustainable development, it is important to differentiate the impacts of precipitation variability and anthropogenic activities on stream flow changes. We investigated the variability in runoff and quantified the contributions of precipitation and anthropogenic activities on runoff at the LPRB. Analysis of the precipitation–runoff for the period 1970–2010 revealed breakpoints in 1986, 2000, 2004 and 2010 in the LPRB. The periods influenced by anthropogenic activities were categorized into three periods 1987–2000, 2001–2004 and 2005–2010, revealing a decrease in runoff during 1987–2000 and an increase in runoff during 2001–2004 and 2005–2010. Assessment of monthly, seasonal and annual runoff depicted a significant increasing trend in the runoff time series during the dry season. Generally, runoff increased at a rate of 9.98 × 107m3yr−1, with precipitation variability and human activities contributing 17.4% and 82.3% respectively. The dominant small scale alluvial gold mining activity significantly contributes to the net runoff variability in LPRB.

Recently, peri-urbanisation has led to the transformation of the rural landscape, changing rural land uses into peri-urban land uses, under varying driving factors. This paper analyzes the dynamic transitions among identified land use and land cover (LULC) types in the Bosomtwe district of Ghana, from 1986 to 2014. An integrated approach of geo-information tools of satellite remote sensing in Earth Resource Data Analysis System (ERDAS) Imagine 13 and ArcMap 10.2 Geographic Information System (GIS), with Markov chain analytical techniques were used to examine the combined forest land cover transitions, relative to build-up, recent fallows and grasslands and projected possible factors influencing the transitions under business as usual and unusual situations. Statistical analyses of the classified Landsat TM, ETM+ and Landsat 8 Operational Land Imager and Thermal Infrared Sensor (OLI/TIS) indicated that over the period of 24 years, the Bosomtwe district has undergone a series of land use conversions with remarkable forest losses especially between 2002 and 2010. In 2010 dense forest cover was degraded to low forest by 4040 ha indicating 0.40% transition probability in the future. There was a remarkable increase of built-up/bare and concrete area with a 380% increment in the 1986–2002 transition periods. The application of the Markov futuristic land use dynamics by the years 2018 and 2028, projected from the 2014 LULC indicated a future steady decline in the area coverage of the dense forest to low forest category. This is currently being driven (as at the 2017 LULC trends), by the combined effects of increasing build up bare and concrete surface land uses as well as the expanding recent fallows and grassland. The paper concluded that the health of the ecosystem and biodiversity of the lake Bosomtwe need to be sustainably managed by the Bosomtwe district assembly.

An article published by Journal of Scientific Research & Reports 5(1): 16-31, 2015; Article no.JSRR.2015.071

The outcome reveal that as the land use in the catchment areas change from mixed agricultural to cassava cultivation, the simulated loads and concentrations of nitrogen species from cassava land-use scenario recorded reduction. The resultant concentrations of nitrate and nitrite for both current and future land-use scenarios are all below the daily limit suggested by the WHO, (World Health Organization). For the phosphate concentration, an increase of 4.21% was depicted under cassava land-use scenario. The results show that SWAT is a reliable water quality model, capable of simulating accurate information for developing environmental management plans.

Reducing emissions from deforestation and forest degradation with other benefits (REDD+) mechanism is supposed to address the reversal of forest-based land degradation, conservation of existing carbon stocks, and enhancement of carbon sequestration. The Bosomtwe District is predominantly agrarian with potentials for climate change mitigation through REDD+ mechanism among smallholder farmers. The limited knowledge and practices of this strategy among farmers are limiting potentials of mitigating climate change. This paper assesses the REDD+ potentials among smallholder farmers in the district. Using a triangulation of quantitative and qualitative design, 152 farmer-respondents were purposively sampled and interviewed, using snowballing method from 12 communities. Quantitative data gathered were subjected to the tools of contingency and frequencies analysis, embedded in the Statistical Package for Social Sciences (SPSS) v.16. The qualitative data were analyzed thematically. Results indicate that respondents have knowledge of REDD+ but not the intended benefit sharing regimes that can accrue to the smallholder farmers. Farmers’ willingness to practice REDD+ will be based on the motivation and incentive potentials of the strategies. The Forestry Services Division should promote the practice of REDD+ among smallholder farmers through education, to whip and sustain interest in the strategy.

Using Satellite Remote Sensing and Geographic Information System, this paper analyzes the land use and land cover change dynamics in the Bosomtwe District of Ghana, for 1986, 2010 thematic mapper and enhanced thematic Mapper+ (TM/ETM+) images, and 2014 Landsat 8 Operational Land Imager and Thermal Infrared Sensor (OLI/TIS) image. The three images were geo-referenced and processed for classification, using the maximum likelihood classifier algorithm. A Jeffries-Matusita’s separability check was used in confirming the degree of spectral separation acceptability of the bands used for each of the land use and land cover classes. The best Kappa hat statistic of classification accuracy was 83%. Land Use and Land Cover (LULC) transition analysis in Environmental Systems Research Institute ESRI’s ArcMap was performed. The results of the classification over the three periods showed that built up, bare land and concrete surfaces increased from 1201 in 1986 to 5454 ha in 2010. Dense forest decreased by 2253 ha over the same period and increased by 873 ha by the 2014. Low forest also decreased by 1043 ha in 2010, however, it increased by 13% in 2014. Our findings showed some of the important changes in the land use and land cover patterns in the District. After the urbanization process, coupled with farmland abandonment, between 1986 and 2010, substantial increments in urban land and clear increments in farmland coverage between 1986 and 2014were found to be the reason for vegetation cover decreases. This suggests that major changes in the socio-ecological driving forces affecting landscape dynamics have occurred in the last few decades.

The main aim of this paper is to examine the effects of peri-urbanization on peri-urban land use change patterns, using a binary logistic regression model, in the Bosomtwe district of the Asante region, Ghana. The decision to convert from agricultural land uses to residential and commercial land uses are driven by a myriad of factors, ranging from social to economic in the Bosomtwe District. A triangulation of qualitative and quantitative design was used. Household questionnaires were proportionately administered to 270 respondents in 14 communities, on the basis of population. The data was subjected to the Pearson’s Chi-square, Nigelkerk R2 and Cramer’s V test of strength of association. Astep-wise binary logistic regression modeling was performed using the PASW v.17. Pearson chi-square value of ?2 = 73.546 at 26 degrees was significant at p< .000,athough the Cramer’s V test of the strength of the association was moderate at V = 0.37. The logistic regression model reported an overall significance of the model at p< .000 with ?2 = 24.453, at 4 degrees of freedom. The confidence intervals of (CIs) of (CI: 1.358—4.517) and (CI: 1.039—11.486) for the two main predictors of the outcome, and a B(Exp) values ranging between 2.477 and 3.455 were also reported. This means the odds of respondents being more likely to change their land uses is about 66%. Increasing rate of peri-urbanization is caused by increasing demand for residential, recreational (Hotels and Guest houses) and commercial land uses at the expense of agro-forest land uses. These have some negative implications on local climate and food security. The District assembly should strictly monitor physical development in line with planning schemes.

Using time series of Normalized Difference Vegetation Index (NDVI) and rainfall data, we investigated historical vegetation productivity trends from 1982 to 2011 over the Bani River Basin in Mali. Statistical agreements between long-term trends in vegetation productivty, corresponding rainfall and rate of land cover change from Landsat time-series imagery was used to discern climate versus human-induced vegetation cover change. Spearman correlation was used to investigate the relationship between metrics of vegetation, rainfall trends and land cover change categories. The results show there is a positive correlation between increases in rainfall and some land cover classes, while some classes such as settlements were negatively correlated with vegetation productivity trends. Croplands and Natural Vegetation were positively correlated (r=0.89) with rainfall while settlements have a negative correlation with NDVI time series trend (r=-057). Despite the fact that rainfall is the major determinant of vegetation cover dynamics in the study area, it appears that other human-induced factors such as urbanization have negatively influenced the change in vegetation cover in the study area. The results show that a combined analysis of NDVI, rainfall and spatially explicit land cover change provides a comprehensive insight into the drivers of vegetation cover change in semi-arid Africa.

Digital elevation model (DEM) in recent times has become an integral part of national spatial data infrastructure of many countries world-wide due to its invaluable importance. Although DEMs are mostly generated from contours maps, stereo aerial photographs and air-borne and terrestrial laser scanning, the stereo interpretation and auto-correlation from satellite image stereo-pairs such as with SPOT, IRS, and relatively new ASTER imagery is also an effective means of producing DEM data. In this study, terrain elevation data were derived by applying photogrammetric process to ASTER stereo imagery. Also, the quality ofDEMs produced from ASTER stereo imagery was analysed by comparing it with DEM produced from topographic map at a scale of 1:50,000. While analyzing the vertical accuracy of the generated ASTER DEM, fifty ground control points were extracted from the map and overlaid on the DEM. Results indicate that a root-mean-square error in elevation of +/- 14 m was achieved with ASTER stereo image data of good quality. The horizontal accuracy obtained from the ground control points was 14.77, which is within the acceptable range of +/- 7m to +/- 25 m. The generated (15 m) DEM was compared with a 20m, 25m, and a 30 m pixel DEM to the original map. In all, the results proved that, the 15 m DEM conform to the original map DEM than the others. Overall, this analysis proves that, the generated digital terrain model, DEM is acceptable.

This paper is a critical review, which synthesizes the theory-application linkage of peri-urban land use and land cover changes (LULCC) using the Bosomtwe District in the Ashanti Region of Ghana as the case. From abstractive thinking to empirical possibility, we conjecture human decisions within agent-based modeling (ABM) perspective. The key question the paper has tried to answer is: what are the probable future land use conversion and modification potentials in the district? LULCC in peri-urban areas respond to social and biophysical dynamics. These control spatial distribution of populations, infrastructure, and the space economy. Under systemic laxity of controls, peri-urban land uses deviate from effective land use plans.