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This study examines the collaborative approach in China-Africa satellite remote sensing initiatives based on solutions of satellite data acquiring, sharing and application experiences. It specifically addresses the data coverage requirements and current coverage scenarios of China's natural resources land satellites in Africa. By establishing the China-Africa Cooperation Centers on Satellite Remote Sensing Application, adopting a multi-level distributed technology center model, and implementing cross-continental remote sensing cloud services through an internet-based cloud platform, this initiative aims to enhance the direct utilization of satellite data in Africa. Furthermore, strategic satellite observation window designs tailored to seasonal changes have increased the frequency of valid coverage over the entire African continent to at least once a year. Such advancements pave the way for real-time monitoring applications, particularly in crucial areas such as sustainable development projects and disaster response efforts. Therefore, the study also provides some useful case studies that are anchored on the Sustainable Development Goals.

Abstract This study evaluates flood susceptibility and risk on Bulk Supply Points in the Greater Accra region (GAR) using a Frequency Ratio model based on 15 flood conditioning factors. The model explores the influence of natural, meteorological and anthropogenic factors on flooding occurrences under the Shared Socioeconomic Pathway (SSP) scenarios and assesses flood risks at Bulk Supply Points (BSPs). Flood susceptibility mapping was conducted for both current and future periods under various SSP scenarios. Results reveal that elevation, slope, soil type, distance from urban areas, and SPI are the most influential factors contributing to flooding susceptibility in the region. The current flood map, about 37% of the total area of GAR categorized under the moderate flood-susceptible zone category followed by about 30% categorized under the low flood-vulnerable zone. However, about 16% was categorized under the very high flood-vulnerable zone. The study projects increasing flood susceptibility under the SSP scenarios with intensification under SSP2 and SSP3 scenarios. For instance, the areas categorized as high and very high flood susceptibility zones are projected to expand to approximately 32% and 26% each by 2055 under SSP3. The study also assesses flood risks at Bulk Supply Points (BSPs), highlighting the escalating susceptibility of power assets to flooding under different scenarios. For instance, in the very high scenario, flooding is estimated to reach 640 h in 2045 and exceed 800 h in 2055—more than double the 2020 baseline. The analysis shows the bulk supply points face increasing flood susceptibility, with risks escalating most sharply under the severe climate change SSP3 and SSP5 scenarios. Over 75% of BSPs are expected to fall in the low- to medium-risk categories across SSPs while more than 50% of BSPs are within medium- to high-risk categories in all scenarios except SSP1, reflecting the impact of climate change. SSP3 and SSP5 stand out with over 60% of BSPs facing high or very high flooding risks by 2055. It indicates moderate resilience with proper adaptation but highlights potential disruptions in critical infrastructure, such as BSPs, during persistent flooding. The findings of the study are expected to inform Ghana’s contributions towards addressing Sustainable Development Goals (SDGs) 7, 11 and 13 in Ghana.

Background/objectives: Ghana, a major travel hub in West Africa, faces a high risk of infectious disease transmission due to frequent travel and cross-border movement. The 2019 coronavirus pandemic, like the 1918 influenza pandemic, highlighted gaps in infectious disease surveillance and outbreak response systems. This study aimed to assess how Ghana can better monitor and respond to emerging and re-emerging infectious diseases (ERIDs) by evaluating its existing surveillance infrastructure. Method: Focusing on Influenza-Like Illness (ILI) and Severe Acute Respiratory Infections (SARI) - key targets for pandemic surveillance - the study analysed the diffusion patterns of the 1918 influenza and 2019 coronavirus in Ghana. Existing surveillance sites were reviewed to identify potential new sites for optimal sentinel surveillance. Results: The first month of the 1918 influenza and 2019 coronavirus outbreaks in Ghana covered 31.8 % and 22.2 % of districts, with full-country spread taking 15 and 13 weeks respectively. The analysis further revealed that towns, villages, and socio-economic routes, particularly in the middle belt and Accra, were high-risk areas. Based on the findings, an additional 369 primary, 610 secondary, and 3176 tertiary surveillance sites were proposed to supplement the current 31 ILI and SARI sites. Conclusion: Expanding the current surveillance system to include ERIDs will enhance Ghana's capacity to efficiently monitor and respond to future outbreaks, improving health security in resource-limited settings.

The study investigated the determinants of adopting E-commerce among maize traders, focusing on the Savings Grains App. E-commerce implications on marketing effectiveness and the value co-creation opportunities were also analyzed. Primary data was sourced from 130 maize traders. Descriptive statistics, probit regression, and inverse probability weighted regression adjustment (IPWRA) were applied to analyze the data. Perceived usefulness, perceived cost, perceived ease of use, perceived innovativeness, perceived complexity, and household size were identified as factors that significantly influence traders’ adoption of E-commerce. These findings reinforce and expand existing theories on adoption intentions within agripreneurship. Moreover, traders using the e-commerce platform reported an increase of 4702 kg in sales volume and GH¢ 239.1 (US$ 26.8) in sales revenue compared to non-adopters. The study further highlighted value co-creation as a catalyst for enhanced sales volume, revenue, and user satisfaction, underscoring its potential as a sustainable strategy within e-commerce frameworks. The insights gained contribute to understanding the transformative role of sustainable technology in boosting growth and resilience in agricultural trade.

AbstractClimate change effects are expected to be profoundly local and region-specific, underlining the urgent need for local-level assessments. This study emphasizes the agriculturally important Zanzan region of northeastern Côte d’Ivoire and examines future changes in precipitation, temperature, and resultant drought conditions based on six global climate models (GCMs) from the Coupled Model Intercomparison Project 6 (CMIP6) under shared socioeconomic pathways (SSPs) scenarios - SSP2-4.5 and SSP5-8.5. We integrate data from 12 stations within the Zanzan region, applying CMhyd software to correct model biases. Key statistical metrics confirm the well-calibrated nature of the corrected GCMs vis-à-vis observed data. Projections show a decrease in annual precipitation by an average of 133 mm and 177 mm under SSP2-4.5 and SSP5-8.5 scenarios respectively by 2100. Future precipitation patterns suggest a shift towards the prevalent dry season. Tmax and Tmin are projected to increase by +3 °C and +4.8 °C (SSP2-4.5 and SSP5-8.5) and +3.3 °C (both scenarios) respectively, by the end of the century. These changes suggest an intensification of severe droughts, particularly in the 2050s and 2080s, as assessed by the SPEI. Additionally, extreme temperatures (TX90p) and consecutive dry days (CDD) are projected to intensify, posing imminent threats to food security, water resources, and public health in the Zanzan region. This study bridges a critical gap by offering localized insights into future climate scenarios, thereby enhancing our understanding of the region-specific impacts of climate change. The research also underscores the urgency of adaptation and mitigation strategies tailored to the Zanzan region’s vulnerabilities.

The United Nations Sustainable Development Goals (SDGs) establish a fresh global framework for evaluating the development agenda, emphasizing prosperity, growth, inclusivity, and transparency while safeguarding our planet Earth. Land Degradation Neutrality (LDN) represents a clear target for assessing the achievement of SDG 15.3. In response to the shortcomings of the African Great Green Wall initiative with respect to LDN monitoring, reporting, and intervention, we developed an online tool, the Great Green Wall Big Data Facilitator (GGW-BDF), based on earth observation data (e.g. SDGSAT-1), cutting-edge big data analysis technologies, and Chinese experience in combating desertification, to support the implementation of the African Great Green Wall initiative. The GGW-BDF comprises an LDN data portal, desertification control knowledge, and e-learning resources. This study highlights the functionality of this tool to support stakeholders across countries in monitoring LDN while providing the successful technoloiges to restore degraded or barren land. The contributions of the GGW-BDF are very useful in supporting the Pan-African Agency of the Great Green Wall (PAGGW), and will hopefully be continuously upgraded for being a part of the federated toolbox of the Group on Earth Observation (GEO) LDN Flagship.

Increasing energy demand has become a major issue of concern globally. Addressing the issue requires the sustainable development of the transportation sector of every nation. Sustainable transport system will meet basic and developmental needs while ensuring equity within and between generations. Fuel consumption and emissions are key issues of importance when considering the sustainability of road transportation. In order to actualize the SDGs, overarching factors impacting on transport vehicle fuel consumption and emissions should not be compromised. Weather being one of such factors is understudied especially in Africa based on the authors knowledge from literature. Consequently, the review accentuates on how weather parameters affect fuel consumption and emissions throwing more light on similar studies that have already been conducted to facilitate cholar and literature database from 2000-2022. In total, 111 articles were systematically reviewed, out of which 41 were from Europe, 38 from America, 23 from Asia and 7 from Africa. Among the weather parameters reviewed, temperature was the most pronounced with percentage share of 46 % followed by air pressure 16%, precipitation 15%, humidity 12%, wind 11%. All the weather factors strongly impacted on vehicular fuel consumption and its concomitant greenhouse gases emissions based on the results depicted by the review. Climate variability and change is detrimental to fuel consumption and emissions and should not be overemphasized when making road transport policies and decisions.

AbstractThe failure of sewage and drainage systems in SubSaharan African cities is frequent and can be considered as a critical issue, both from an environmental standpoint and in terms of associated maintenance costs. This study analyzes the state of the sanitation systems, the elements behind the failures, the environmental concepts used to classify the problems, and the tools and methodological alternatives for ranking the various management solutions. This research illustrates the causes that contribute to the dysfunctions in the sewage systems of Abidjan as a typical example of sewerage systems management challenges in SubSaharan Africa’s large cities. Poor solid waste and wastewater management practices by residents, e.g., illegal dumping of solid waste into the sewers, unauthorized and defective connections to the network, structural dysfunctions related to the age of the network (cracked, denuded, or broken), urban agriculture in the vicinity of the channels, natural phenomena such as erosion, landslides in the undeveloped parts, and the high concentration of vegetation in the network, wholly contribute to the degradation of the network. A variety of decision support systems for the management of the assets of the urban sewage network were presented. The instruments have been categorized based on their capacity and functionality. The operating concept of each of these tools has been outlined, as well as their respective data needs. In addition, the study analyzes challenges related to the usage of existing decision support systems and provides an outlook on future research requirements in this area. This study offers a detailed analysis of the issues of sanitation management and could serve as a reference for other emerging nations in SubSaharan Africa.

Land use and land cover (LULC) changes are one of the main factors contributing to ecosystem degradation and global climate change. This study used the Gontougo Region as a study area, which is fast changing in land occupation and most vulnerable to climate change. The machine learning (ML) method through Google Earth Engine (GEE) is a widely used technique for the spatiotemporal evaluation of LULC changes and their effects on land surface temperature (LST). Using Landsat 8 OLI and TIRS images from 2015 to 2022, we analyzed vegetation cover using the Normalized Difference Vegetation Index (NDVI) and computed LST. Their correlation was significant, and the Pearson correlation (r) was negative for each correlation over the year. The correspondence of the NDVI and LST reclassifications has also shown that non-vegetation land corresponds to very high temperatures (34.33°C–45.22°C in 2015 and 34.26°C–45.81°C in 2022) and that high vegetation land corresponds to low temperatures (17.33°C–28.77°C in 2015 and 16.53 29.11°C in 2022). Moreover, using a random forest algorithm (RFA) and Sentinel-2 images for 2015 and 2022, we obtained six LULC classes: bareland and settlement, forest, waterbody, savannah, annual crops, and perennial crops. The overall accuracy (OA) of each LULC map was 93.77% and 96.01%, respectively. Similarly, the kappa was 0.87 in 2015 and 0.92 in 2022. The LULC classes forest and annual crops lost 48.13% and 65.14%, respectively, of their areas for the benefit of perennial crops from 2015 to 2022. The correlation between LULC and LST showed that the forest class registered the low mean temperature (28.69°C in 2015 and 28.46°C in 2022), and the bareland/settlement registered the highest mean temperature (35.18°C in 2015 and 35.41°C in 2022). The results show that high-resolution images can be used for monitoring biophysical parameters in vegetation and surface temperature and showed benefits for evaluating food security.

The management of domestic wastewater and rainwater is a major concern for the population of Yopougon. The study presents the causes of wastewater discharge from dysfunctional sewers and their health impacts on the population. It also highlights the environmental and health risk associated with poor solid and liquid waste management. This was based on literature search, semi-participatory workshop, physicochemical and bacteriological characterization of wastewater and finally through a household survey. The field survey was conducted on 245 household heads obtained using the Canadian statistical guidelines. The results obtained indicated that all main pollution indicators were; total nitrogen (TN, 525 ± 0.02 to 3077 ± 0.3 mg/l), nitrates (NO3, 146 ± 0.01 to 1347 ± 0.12 mg/l), biochemical oxygen demand (BOD, 278 ± 195.16 to 645 ± 391.74 mg/l), chemical oxygen demand (COD, 940 ± 650.54 to 4050.5 ± 71.42 mg/l) and total dissolved solids (TDS, 151 ± 9.9 to 766 ± 237.59 mg/l) which were above the values recommended by the World Health Organization (WHO) and Cote d'Ivoire national policy guidelines standards for the discharge of effluents into the environment. The analysis of the bacterial flora of the effluents revealed that the concentrations of Total Coliforms and fecal streptococci exceeded the values recommended by the WHO and national policy guidelines standards. This means that the populations of this area are prone to infectious diseases. Diseases such as malaria (84.53%), respiratory infections (61%), diarrhea (48.66%), intestinal diseases (44.5%), and typhoid fever (28.84%) were prevalent in the surveyed households.

In Cote d'Ivoire, the failure of urban sewage systems is a crucial problem for the drainage of wastewater and rainwater. This failure is due to many factors and therefore, calls for diagnostic studies. The present study aimed at analyzing these networks in order to identify the different factors that contribute to the operational and structural degradation in selected sewerage and drainage networks in Abidjan, Cote d'Ivoire. The method used in the study involved semi-structured interviews, video camera inspection and socio-environmental field surveys (geographical survey and household survey), followed by descriptive statistics. The results revealed that many structural, environmental and behavioral practice contribute to the progressive degradation of urban sewage systems. These factors are essentially those that prevent the normal flow of wastewater in the pipes such as the illegal dumping of solid waste, the unauthorized connection of wastewater networks, unsustainable urban agricultural practices, as well as the high concentration of vegetation on both sides of the network and the dilapidated infrastructure of the wastewater and rainwater networks. It was found that these factors are at the origin of the clogging and degradation of the sewers since 85% of the residents used these sewers as a dumping ground for solid waste.

Introduction Ghana is the first country in sub-Saharan Africa (SSA) to aim for universal health coverage (UHC). Based on Ghana’s UHC system, the accessibility and distribution of healthcare facilities were evaluated for 2020. Projecting into 2030, this study aimed at providing geographical information data for guiding future policies on siting required healthcare facilities. Ghana as a precedent for SSA was evaluated and proposed to “leave no disease behind” in the surveillance of infectious diseases (IDs). This is to reinforce the sustainable development goals (SDG) 3 agenda on health that underpins monitoring equity in “leaving no one behind.” Methods Geospatial accessibility, travel time data, and algorithms were employed to evaluate the universality and accessibility of healthcare facilities, and their future projections to meet UHC by 2030. Healthcare facilities as surveillance sites were compared to community-based surveillance to identify which would be more applicable as a surveillance system to leave no disease behind in Ghana. Findings Ghana has 93.8%, 6.1% and 0.1% as primary, secondary and tertiary healthcare facilities respectively. It has 26.1% of healthcare facilities remaining to meet the SDG 3 health target by 2030. In terms of providing quality healthcare, 29.3% and 67.2% of the additional required healthcare facilities for optimal allocation and achieving the UHC target need to be secondary and tertiary respectively. In assessing the broad spectrum of IDs studied from 2000 to 2020, an average of 226 IDs were endemic or potentially endemic to Ghana. The majority of the studies carried out to identify these IDs were done through community-based surveillance. Conclusion Establishing community-based surveillance sites to leave no disease behind and also providing the required healthcare facilities to reinforce leaving no one behind will enhance the universal health security of Ghana as a precedent for SSA.

Groundwater (GW) is a key source of drinking water and irrigation to combat growing food insecurity and for improved water access in rural sub-Saharan Africa. However, there are limited studies due to data scarcity in the region. New modeling techniques such as Machine learning (ML) are found robust and promising tools to assess GW recharge with less expensive data. The study utilized ML technique in GW recharge prediction for selected locations to assess sustainability of GW resources in Ghana. Two artificial neural networks (ANN) models namely Feedforward Neural Network with Multilayer Perceptron (FNN-MLP) and Extreme Learning Machine (FNN-ELM) were used for the prediction of GW using 58 years (1960–2018) of GW data. Model evaluation between FNN-MLP and FNN-ELM showed that the former approach was better in predicting GW with R2 ranging from 0.97 to 0.99 while the latter has an R2 between 0.42 to 0.68. The overall performance of both models was acceptable and suggests that ANN is a useful forecasting tool for GW assessment. The outcomes from this study will add value to the current methods of GW assessment and development, which is one of the pillars of the sustainable development goals (SDG 6).

Abstract Floods in Ghana have become a perennial challenge in the major cities and communities located in low-lying areas. Therefore, cities and communities located in these areas have been classified as potential or natural flood-prone zones. In this study, the Digital Elevation Model (DEM) of the Accra Metropolis was used to assess the drainage density and elevation patterns of the area. The annual population estimation data and flood damages were assessed to understand the damages and population trend. This research focused primarily on the elevation patterns, slope patterns, and drainage density of the Accra Metropolis. Very high drainage density values, which range between 149 and 1117 m/m2, showed very high runoff converging areas. High drainage density was also found to be in the range of 1117–1702 m/m2, which defined the area as a high runoff converging point. The medium and low converging points of runoff were also found to be ranging between 1702–2563 m/m2 and 2563–4070 m/m2, respectively. About 32% of the study area is covered by natural flood-prone zones, whereas flood-prone zones also covered 33% and frequent flood zones represent 25%. Areas in the Accra Metropolis that fall in the Accraian and Togo series rock types experience high floods. However, the lineament networks (geological structures) that dominate the Dahomeyan series imply that the geological structures in the Dahomeyan series also channel the runoffs into the low-lying areas, thereby contributing to the perennial flooding in the Accra Metropolis.

This study evaluates flood susceptibility and risk on Bulk Supply Points in the Greater Accra region (GAR) using a Frequency Ratio model based on 15 flood conditioning factors. The model explores the influence of natural, meteorological and anthropogenic factors on flooding occurrences under the Shared Socioeconomic Pathway (SSP) scenarios and assesses flood risks at Bulk Supply Points (BSPs). Flood susceptibility mapping was conducted for both current and future periods under various SSP scenarios. Results reveal that elevation, slope, soil type, distance from urban areas, and SPI are the most influential factors contributing to flooding susceptibility in the region. The current flood map, about 37% of the total area of GAR categorized under the moderate flood-susceptible zone category followed by about 30% categorized under the low flood-vulnerable zone. However, about 16% was categorized under the very high flood-vulnerable zone. The study projects increasing flood susceptibility under the SSP scenarios with intensification under SSP2 and SSP3 scenarios. For instance, the areas categorized as high and very high flood susceptibility zones are projected to expand to approximately 32% and 26% each by 2055 under SSP3. The study also assesses flood risks at Bulk Supply Points (BSPs), highlighting the escalating susceptibility of power assets to flooding under different scenarios. For instance, in the very high scenario, flooding is estimated to reach 640 h in 2045 and exceed 800 h in 2055—more than double the 2020 baseline. The analysis shows the bulk supply points face increasing flood susceptibility, with risks escalating most sharply under the severe climate change SSP3 and SSP5 scenarios. Over 75% of BSPs are expected to fall in the low- to medium-risk categories across SSPs while more than 50% of BSPs are within medium- to high-risk categories in all scenarios except SSP1, reflecting the impact of climate change. SSP3 and SSP5 stand out with over 60% of BSPs facing high or very high flooding risks by 2055. It indicates moderate resilience with proper adaptation but highlights potential disruptions in critical infrastructure, such as BSPs, during persistent flooding. The findings of the study are expected to inform Ghana's contributions towards addressing Sustainable Development Goals (SDGs) 7, 11 and 13 in Ghana. [ABSTRACT FROM AUTHOR]

Land Use/Land Cover (LULC) change is a major global concern and a topic of scientific debate. In West Africa, the key trend among the changes of the past few years is the loss of natural vegetation related to changes in different LULC categories, e.g., water bodies, wetland, and bare soil. However, not all detected changes in these LULC categories are relevant for LULC change management intervention in a resource-constrained continent, as a massive change in the dominant LULC types may be due to errors in the LULC maps. Previous LULC change analysis detected large discrepancies in the existing LULC maps in Africa. Here, we applied an open and synergistic framework to update and improve the existing LULC maps for West Africa at five-year intervals from 1990 to 2020—updating them to a finer spatial resolution of 30 m. Next, we detected spatial–temporal patterns in past and present LULC changes with the intensity analysis framework, focusing on the following periods: 1990–2000, 2000–2010, and 2010–2020. A faster annual rate of overall transition was detected in 1990–2000 and 2010–2020 than in 2000–2010. We observed consistent increases in shrubland and grassland in all of the periods, which confirms the observed re-greening of rangeland in West Africa. By contrast, forestland areas experienced consistent decreases over the entire period, indicating deforestation and degradation. We observed a net loss for cropland in the drought period and net gains in the subsequent periods. The settlement category also gained actively in all periods. Net losses of wetland and bare land categories were also observed in all of the periods. We observed net gains in water bodies in the 1990–2000 period and net losses in the 2010–2020 period. We highlighted the active forestland losses as systematic and issued a clarion call for an intervention. The simultaneous active gross loss and gain intensity of cropland raises food security concerns and should act as an early warning sign to policy makers that the food security of marginal geographic locations is under threat, despite the massive expansion of cropland observed in this study area. Instead of focusing on the dynamics of all the LULC categories that may be irrelevant, the intensity analysis framework was vital in identifying the settlement category relevant for LULC change management intervention in West Africa, as well as a cost-effective LULC change management approach.

The current epidemiological transition makes us wonder how the parallel of infectious diseases (IDs) might be at the end of each passing year. Yet, the surveillance of these IDs continues to focus on high-profile diseases of public health importance without keeping track of the broad spectrum of the IDs we face. Here, we presented the prevalence of the broad spectrum of IDs in Ghana. Data from the annual reports on Gold Coast now Ghana, Global Infectious Diseases and Epidemiology Network (GIDEON), and the District Health Information Management System II (DHIMS2) databases were examined for records of ID prevalence in Ghana. Using the IDs from these databases, the paper assessed the epidemiological transition, pathogen-host interactions, spatiotemporal distribution, transmission routes, and their potential areas of impact in Ghana. The topmost ID recorded in health facilities in Ghana transitioned from yaws in the 1890s to malaria in the 1950s through 2020. We then presented the hosts of a pathogen and the pathogens of a host, the administrative districts where a pathogen was found, and the pathogens found in each district of Ghana. The highest modes of transmission routes were through direct contact for bacteria and airborne or droplet-borne for viral pathogens. From GIDEON, 226 IDs were identified as endemic or potentially endemic in Ghana, with 42% cited in peer-reviewed articles from 2000 to 2020. From the extent of risk of endemic or potentially endemic IDs, Ghana faces a high risk of ID burden that we should be mindful of their changing patterns and should keep track of the state of each of them.