http://197.159.135.214/jspui/handle/123456789/35 2026-05-06T00:16:59Z http://197.159.135.214/jspui/handle/123456789/1131 Title: Spatio-temporal land use and land cover change assessment: Insights from the Ou´em´e River Basin Authors: Annan, Ernestina; Amponsah, William; Adjei, Kwaku Amaning; Disse, Markus; Hounkpe, Jean; Biney, Ernest; Agbenorhevi, Albert Elikplim; Agyare, Wilson Agyei Abstract: The rapid increase in population and urban development are exacerbating the transformation of natural environments into unnatural forms. While detailed assessment of the environment is beneficial for efficient ecosystem system management, it can also be time and resourcesconsuming. This study aimed to map and quantify the spatio-temporal changes in land use and land cover (LULC) using the Ou´em´e River Basin as a case study. The supervised classification in Google Earth Engine (GEE) cloud-computing platform was employed to distinguish Landsat images for 1986, 2000, 2015 and 2023 into forest areas, settlements/bare lands, savanna areas (woodlands), agricultural lands and water bodies. Analysis of the LULC changes revealed that savanna areas and woodlands which were predominant in the basin in 1986 have steadily declined by 24 % in area in 2023. Forest areas have diminished by 4.3 % at an annual rate of 4 %. Agricultural lands have however grown exponentially by 28 % since 1986, with a more rapid increase between 2015 and 2023 at an annual rate of 3.7 %, driven by rising food demand due to population growth within and around the basin. Settlements and bare areas tripled in area, reflecting a similar trend to Benin’s urban population growth. Accuracy statistics of the LULC classification showed overall accuracy and kappa statistic values above 90 % and 86 %, respectively, indicating the admirable performance and reliability of the Simple Composite Landsat algorithm for image composition, and the Random Forest Classifier for LULC classification approach applied in this study. The approach also demonstrates the robustness and potential of LULC mapping in large and complex ecosystems using the GEE cloud-based remote sensing tool, which is underutilized in the study area. Overall, the LULC trends provide beneficial insights useful to policy-makers and any other stakeholders involved in sustainable ecosystem management planning in the basin. Description: A Publication submitted to the West African Science Service Centre on Climate Change and Adapted Land Use and the Kwame Nkrumah University of Science and Technology, Kumasi, Ghana, in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Climate Change and Land Use 2024-05-27T00:00:00Z http://197.159.135.214/jspui/handle/123456789/1129 Title: Risks and Influences of Climate Hazards for Agro-Pastoral Development and Strategies Adopted by Agro-Pastoralist Communities in the Bougouni District, Mali Authors: Sanogo, Tidiani; Sokemawu, Koudzo; Karembe, Moussa Abstract: In the southwest of Mali, pastoral resources play an important role in the production and reproduction of livestock. These pastoral resources are very sensitive to climatic hazards and negatively affected their availability in quantity and quality. The main objective of this study was to analyze the risks and influences of climate hazards on pastoral resources and the strategies taken by agropastoralists to cope with them. To achieve this objective, meteorological data trends from 1950 to 2022 were analyzed. The socio-economic data were collected through a semi-structured survey administered to 404 head households, from focus groups through discussion with local stakeholders by using climatic risks matrix. The results obtained indicate a concordance between agropastoralists perception on climate change and meteorological observations concerning the decrease of rainfall (−213 mm; 63.3%), the increase of maximum and minimum temperature (+1.33˚C, +1.24˚C; 93.1%), and the increase of wind speed (+0.59 m/s; 97%) over the past 70 years. Respondents noted a deterioration in the conditions of pastoral resources due to climatic hazards compared to the last 40 years (44.8% for watering points; 23.5% for pastures; 63.1% for salty lands). Agro pastoralists have adopted measures that allow them to be resilient. These include the collection and storage of crop residues (49.5%), regular watering of animals (39.6%), changing of animals rhythms driving (35.9%), protection of pruning species (31.7%), and concerted reforestation (37.9%). Climatic risk-related hazards constitute a real threat to pastorals resources in the district of Bougouni. Description: A Publication submitted to the West African Science Service Centre on Climate Change and Adapted Land Use, the Université de Lomé, Togo in partial fulfillment of the requirements for the requirements for the degree of Doctor of Philosophy Degree in Climate Change and Disaster Risk Management 2023-06-21T00:00:00Z http://197.159.135.214/jspui/handle/123456789/1128 Title: State of Knowledge on Beekeeping Practices in Côte d'Ivoire in the Face of Challenges and Opportunities in the Context of Climate Change Authors: Ouattara, Salimata; Assi-Kaudjhis, Chimène; Adjonou, Kossi; Kouamé, Koffi Félix; Koudegnan, Comlan Mawussi; Kokou, Kouami Abstract: Beekeeping plays an important role in socio-economic development and environmental conservation. This sector is developing in Côte d'Ivoire even if it is an ancient practice. Based on available scientific data, this study aims to take stock of the Ivorian beekeeping sector and its melliferous potential. The aim is to gain a better understanding of the difficulties faced by this sector and to contribute to its sustainable development in the current context of climate change. Côte d'Ivoire’s honey is of good quality and very rich in nutrients: pollen grains, minerals, etc. A part Apis mellifera, other species of bees are present and could be used in keeping. Despite favorable climatic and floristic conditions, beekeeping in Côte d'Ivoire is still in its infancy caused by several challenges: Environmental conditions, lack of training of beekeepers, and weak commitment of stakeholders. To modernize the sector, we need to combine the efforts of the authorities, take into account the recommendations of scientific publications, and encourage the population to understand the importance of preserving plants and bees by practicing modern beekeeping. Description: A Publication submitted to the West African Science Service Centre on Climate Change and Adapted Land Use, the Université de Lomé, Togo in partial fulfillment of the requirements for the requirements for the degree of Doctor of Philosophy Degree in Climate Change and Disaster Risk Management 2023-10-31T00:00:00Z http://197.159.135.214/jspui/handle/123456789/1127 Title: Toward understanding land use land cover changes and their effects on land surface temperature in yam production area, Côte d’Ivoire, Gontougo Region, using remote sensing and machine learning tools (Google Earth Engine) Authors: Aka, Kadio S. R.; Akpavi, Semihinva; Dibi, N’Da Hyppolite; Bah, Amos T. Kabo-; Gyilbag, Amatus; Boamah, Edward Abstract: 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. Description: A Publication submitted to the West African Science Service Centre on Climate Change and Adapted Land Use, the Université de Lomé, Togo in partial fulfillment of the requirements for the requirements for the degree of Doctor of Philosophy Degree in Climate Change and Disaster Risk Management 2023-08-30T00:00:00Z