Geospatial Data Science project predicting flood vulnerability and socio-economic impact in Kenya using Satellite Imagery (CHIRPS/SRTM) and Machine Learning.
# Kenya Flood Risk & Socio-Economic Impact Analysis 🇰🇪🌊
## Project Overview
I have observed the devastating impact of seasonal flooding in Kenya. This project integrates **Environmental Science** with **Data Science** to identify high-risk flood zones and quantify the population at risk using satellite data and Machine Learning.
## The Data Stack
- **Rainfall:** CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data).
- **Terrain:** NASA SRTM Digital Elevation Model (DEM).
- **Human Impact:** WorldPop & Humanitarian Data Exchange (HDX).
- **Tools:** Python (GeoPandas, Rasterio, Scikit-Learn), QGIS.
## Project Structure
1. **Notebook 01:** Data Acquisition & Geospatial Wrangling.
2. **Notebook 02:** Exploratory Data Analysis & Hydrological Feature Engineering.
3. **Notebook 03:** Predictive Modeling (Random Forest) & Impact Assessment.
## How to Run
1. Clone the repo: `git clone
github.com`
2. Install dependencies: `pip install -r requirements.txt`