Akajiaku11/Assessing-the-impact-of-climate-change-on-flood-patterns-downstream-Nigeria-using-machine-learning

Assessing the impact of climate change on flood patterns in downstream Nigeria using machine learning and geospatial techniques (2018–2024) Flood Mapping and Monitoring in Nigeria Welcome to the repository for Flood Mapping and Monitoring in Nigeria, a project aimed at using geospatial technology to analyze and visualize flood-prone areas in the Niger Delta, Nigeria. This project leverages Google Earth Engine (GEE) and Sentinel-1 Synthetic Aperture Radar (SAR) data for accurate flood detection and monitoring. Introduction Flooding is a major environmental and socio-economic challenge in Nigeria, particularly in the Niger Delta region. This region experiences frequent flooding due to its low-lying terrain, poor drainage systems, and high rainfall during the rainy season. Flooding leads to displacement, destruction of property, and disruption of livelihoods. To mitigate and manage the effects of floods, there is a need for continuous monitoring, early warning systems, and accurate mapping of flood-prone areas. The Flood Mapping and Monitoring in Nigeria project aims to provide a comprehensive framework for flood detection and mapping using satellite imagery, which can be integrated into disaster management systems to enhance flood prediction, preparedness, and response. Project Overview This project uses Sentinel-1 SAR data from the European Space Agency's Copernicus program, processed within the Google Earth Engine (GEE) environment. Sentinel-1's SAR capabilities are especially useful for flood detection as it can capture imagery regardless of cloud cover or light conditions, making it ideal for real-time flood monitoring. Objectives To detect and map flooded areas in the Niger Delta region using Sentinel-1 SAR imagery. To calculate the extent of flooded and non-flooded areas. To create visualizations that can help policymakers and disaster management agencies understand the flood dynamics. To export flood and non-flood data as GeoTIFF files for further analysis. Key Features Flood Detection: Identification of flood-prone areas using SAR data. Visualization: Visual representation of flooded vs. no …