http://197.159.135.214/jspui/handle/123456789/54 Thu, 23 Apr 2026 15:06:33 GMT 2026-04-23T15:06:33Z http://197.159.135.214/jspui/handle/123456789/1154 Enhancing Urban Greenery Planning in the Changing Climate in Africa: Addressing Porto-Novo and Parakou in Benin Republic Akakpo, Bokon A.; Okhimamhe, Appollonia A.; Orekan, Vincent A. O. Tailored strategies are needed to address the functional decimation of different green spaces, particularly in peri-urban areas. Promoting the replacement of impervious surfaces with vegetation and trees can mitigate urban climate issues, fostering a greener environment. Maintenance and conservation of existing ecological zones, along with the creatin of new ones, should be prioritized for sustainable urban development A Publication submitted to the West African Science Service Centre on Climate Change and Adapted Land Use and the Federal University of Technology, Minna, Nigeria, in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Climate Change and Human Habitat Wed, 03 Jan 2024 00:00:00 GMT http://197.159.135.214/jspui/handle/123456789/1154 2024-01-03T00:00:00Z http://197.159.135.214/jspui/handle/123456789/1153 Building Resilience of Coastal Communities to the Impacts of Sea Level Rise in Ghana: A gap in policy Adade, Richard; Jaiye, Dukiya; Brown Klutse, Nana Ama; Thiel, Michael; Okhimamhe, Appollonia Aimiosino Ghana's coastal zone faces a looming crisis from sea-level rise, demanding urgent adaptation measures. Despite government initiatives, rural communities are disproportionately affected and underserved. Through a novel approach integrating FIS, UAV tech, ethnography and expert insights, this study examines adaptation dynamics in three coastal villages, exposing gaps in current strategies. The findings underscore the imperative of tailored, community-centered interventions to fortify resilience and bridge policy-practice divides. A Policy brief submitted to the West African Science Service Centre on Climate Change and Adapted Land Use and the Federal University of Technology, Minna, Nigeria, in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Climate Change and Human Habitat Wed, 03 Jan 2024 00:00:00 GMT http://197.159.135.214/jspui/handle/123456789/1153 2024-01-03T00:00:00Z http://197.159.135.214/jspui/handle/123456789/1106 Fine particulate air pollution estimation in Ouagadougou using satellite aerosol optical depth and meteorological parameters Amooli, Joe Adabouk The main sources of fine particles in our cities are the exhausts of cars, trucks, buses, and offroad vehicles as well as other processes that involve the burning of fuels like wood, heating oil, or coal, and natural sources like dust storms from the Sahara Desert and forest fires. Fine particles tend to worsen conditions such as asthma, and other forms of respiratory diseases. Since the sources of these particles are a result of our daily activities it is urgent to measure their levels so we can plan outdoor activities safely and reduce their impact on our health. This work used satellite and weather information to develop four (4) models to help estimate Ouagadougou’s fine particles as a way of contributing to solving air pollution problems in African cities. The photo proves the sources of fine particles in the city of Ouagadougou and how residents breathe them without wearing air filters/nose marks. A Policy brief submitted to the West African Science Service Center on Climate Change and Adapted Land Use and Université Joseph KI-ZERBO, Burkina Faso in partial fulfillment of the requirements for the Master of Science Degree in Informatics for Climate Change Mon, 04 Sep 2023 00:00:00 GMT http://197.159.135.214/jspui/handle/123456789/1106 2023-09-04T00:00:00Z http://197.159.135.214/jspui/handle/123456789/1105 Agricultural soil characterization and crop recommendation using deep learning algorithms: Model Selection and AI Application Development Ali Abdou, Moussa Agriculture is vital, and soil is a fundamental component with unique characteristics for different crops. This thesis research aimed to develop a deep learning-based system for soil type classification. It explores the performances of eight CNNs architectures namely, DenseNet201, MobileNetV3Large, VGG16, VGG19, InceptionV3, ResNet50, Xception, and a novel architecture referred to as simple architecture, for classifying agricultural soil types found in Maradi, Niger. The research methodology encompasses data collection, cleaning, preprocessing, model building, hyperparameter optimization, model compilation, and the development of an AI-based application. The findings highlight that ResNet50 and DenseNet201 were better than other models for all performance metrics. Thus, the developed application is meant to empower farmers to optimize their practices in the face of land degradation and climate change challenges. A Policy Brief submitted to the West African Science Service Center on Climate Change and Adapted Land Use and Université Joseph KI-ZERBO, Burkina Faso in partial fulfillment of the requirements for the Master of Science Degree in Informatics for Climate Change Fri, 01 Sep 2023 00:00:00 GMT http://197.159.135.214/jspui/handle/123456789/1105 2023-09-01T00:00:00Z