GEOGRAPHIC INFORMATION SYSTEM

Land use and land cover (LULC) changes significantly influence urban planning, environmental management, and sustainable development. This study examines LULC dynamics in Delta State, Nigeria, over multiple years using Sentinel-2 satellite imagery and Geographic Information System (GIS) techniques. As one of Nigeria’s rapidly urbanizing regions, Delta State has witnessed extensive land cover transformations, driven by urban expansion, infrastructure growth, and economic activities.
Utilizing Sentinel-2 images from 2018, 2021, and 2024, alongside a projected land-cover model for 2030, this study employs supervised classification techniques to analyze land-cover transitions over time. Findings reveal that built-up areas increased by approximately 29% from 2018 to 2024, largely driven by urban expansion and infrastructural development. Conversely, dense vegetation cover declined by about 10.6%, primarily due to deforestation and land conversion for agricultural and residential purposes. Cropland expanded significantly by 27.8%, reflecting the ongoing transformation of vegetated areas into farmland, while bare land rose by 43%, associated with vegetation degradation and construction activities. Water bodies exhibited a moderate increase of 33.6%, likely influenced by expanded reservoirs and hydrological variations. Future projections for 2030 suggest that built-up areas will continue expanding at an accelerated rate, with a potential 31.7% increase from 2024, further intensifying pressure on natural ecosystems. Dense vegetation is expected to decline slightly, while cropland continues to expand, underscoring
growing agricultural demands. Bare land may decrease as some areas transition to built-up or reclaimed zones, and water bodies are projected to increase marginally. These trends, if sustained, could exacerbate environmental challenges such as biodiversity loss, flooding, and urban heat island effects, emphasizing the need for sustainable land-use planning and effective conservation
measures

This project investigates improving pathfinding algorithms in Geographic Information Systems (GIS) by optimizing the calculation of geodesics. Geodesics refer to the shortest paths along the curved surface of the Earth, as opposed to straight lines drawn on a flat map. This is crucial for accurate navigation, especially over long distances. Traditional GIS pathfinding algorithms often rely on simpler Euclidean distance calculations, which can lead to significant errors.The objective of this study is to develop or improve upon existing methods for finding optimal geodesics paths within a GIS environment. This will enable more accurate and efficient navigation for various applications, such as: route planning for vehicles, pedestrians, and drones, search and rescue operations, ecological studies analyzing animal movement patterns. The study will explore different algorithms for calculating geodesics on a geoid (Earth's mathematical representation). This could involve techniques like Dijkstra's algorithm adapted for curved surfaces or A* search with appropriate heuristics for geodesic distances. The study might explore methods to optimize the pathfinding process. This could involve strategies like pre-computing geodesics for frequently used routes or implementing techniques to reduce computational complexity. This study by optimizing geodesics paths for navigation has the potential to significantly enhance the capabilities of GIS for various applications requiring accurate and efficientpathfinding.