Penjani Hopkins Nyimbili

This study explores the feasibility of a rapid transit railway system to address Lusaka City's growing transportation challenges caused by rapid urbanization and population growth. The research proposes the Chongwe-Kafue line through Lusaka to enhance urban mobility. Using Google Earth and QGIS for station identification, mapping and distance analysis, the study delineates a 92.8 km main corridor with 13 branch-off lines spanning 51.6 km, including two direct airport connections, designed to enhance accessibility and efficiency. Travel time analysis, based on Delhi Metro’s operational model, estimates a 105.6-minute journey with an average speed of 60 km/h. Additionally, fare structures and construction costs were evaluated. The findings demonstrate the system's viability as an efficient alternative to minibus-dominated transport, offering reduced travel times and improved connectivity, stimulating economic growth and supporting sustainable urban development. This research provides a practical framework for policymakers and urban planners to implement a feasible transit solution in Lusaka.

This study presents a flood modelling approach aimed at enhancing planning strategies to mitigate flooding impacts in LusakaCity. By integrating factors such as slope, hydrostatic potential surface, and the built environment, a predictive flood modelwas developed. The methodology involved using Geographic Information System (GIS) techniques and digital elevationmodels (DEMs) to assess geological features and manmade structures. Precipitation patterns and water demand analysesaided in computing a hydrostatic potential surface through watershed delineation. The generated flood model producedcomprehensive flood maps illustrating water drainage in Lusaka, identifying vulnerable areas using Multi-Criteria DecisionAnalysis (MCDA) techniques. Results highlight the complex interaction between geographical features and humaninfrastructure in flood dynamics. This study contributes to informing zoning policies and disaster response planning, aimingto reduce the impact of future flooding events.

Infrastructure is closely linked to socio-economic development and research based on historical data has shown asignificant positive association between economic growth and infrastructure in the long run. Infrastructuredevelopments come with a range of social and economic benefits, however, it is not a panacea without side effects,having a range of negative effects on the environment owing to the fact that it is embedded in the natural system.Using the deductive approach to qualitative analysis, an extensive review of the literature was conducted. Theresearch determines several factors that can be considered in mitigating the adverse effects of infrastructuredevelopment on the environment such as the use of green building and low-carbon infrastructure, sustainablebuilding practices, renewable energy, waste management during construction and environmental legislation.Decision-making should therefore be guided by these factors established and incorporated into public policiesnecessary to promote sustainable economic development and environmental protection.

Effective land resource management and sustainable development, particularly in urban green spaces, rely on strategicland planning and mapping techniques such as Remote Sensing. This study utilises object-based classification techniques,employing Google Earth Engine and Quantum Geographic Information Systems (QGIS), to examine Lusaka City's greenspace encroachment. Findings reveal a 59% increase in built-up areas towards the north-east direction and a 2% declinein green spaces towards the south-east part of Lusaka. The implications are significant, highlighting the urgent need forintervention to preserve the city's environmental balance. Immediate action is essential, requiring rigorous regulations,community engagement, and stakeholder collaboration. Furthermore, the study underscores the critical role of remotesensing in monitoring urban green spaces and identifying sustainability threats, emphasising the importance of prioritisingthe protection and improvement of green spaces through comprehensive land use planning and land use land covermapping through the use of object-based classification techniques.

Radar and Optical based satellite sensors were used in the study of the Mumbwa flood of December 2020. The Synthetic Aperture Radar (SAR) based Sentinel-1B was processed in Google Earth Engine (GEE) and utilized to generate an image mosaic from December 2020 to May 2021 to delineate flood extent. A local water histogram threshold change detection approach by image ratio was utilized to determine the flood extent with an intensity value of 1.26 dB as it fitted the study area uniquely as opposed to the global value of 1.25 dB. After extracting the initial flood water extent, it was necessary to filter out regions which inundated during the flood period. This was carried out using the following datasets and parameters: The HydroSHEDS Digital Elevation Model (DEM) was used to filter out regions with a slope value of greater than 7% and the Global Surface Water Layer was used to clip out regions with existing permanent surface water. Once the flooded areas were identified, the Optical based Sentinel-2 was used in the production of a Land Use Land Cover (LULC) Map for August 2020 in order to superimpose the flooded areas with existing land features over the study area. The map also under went pre and post processing in GEE using the Random Forest Classification Algorithm that achieved an Overall Accuracy and Kappa Coefficient of 0.957 and 0.91519 respectively. Thereafter the flood analysis and damage assessment were carried out. The quantitative damages to Landcover were found to be: Wetland 6,338.97 Ha (33.27%), Shrubland 5,117.75 Ha (26.89%), Biochar Soil 3,660.47 Ha (19.21%), Trees 3,466.37 Ha (18.19%), Bare soil 273.47 Ha (1.44%), Crop Fields 190.69 Ha (1%) and Built-Up 4.13 Ha (0.02%). Therefore the use of SAR by local histogram threshold approach with Optical datasets for LULC map production proved successful in the study of flood damage.