Historical Risk Explorer

A Streamlit-based tool developed for the NASA Earth Observation Challenge, enabling users to analyze historical environmental data and assess risk probabilities through interactive visualizations.

Overview

Historical Risk Explorer is a modular application that allows users to:

• Select any geographic location and date for analysis
• Explore multiple environmental variables
• Visualize trends and distributions
• Calculate risk indices and exceedance probabilities

Setup

1. Clone the repository:

   git clone https://github.com/your-username/Nasa-hacthon.git
   cd Nasa-hacthon

2. (Optional) Create and activate a virtual environment:

   python3 -m venv .venv
   source .venv/bin/activate

3. Install dependencies:

   pip install -r requirements.txt

4. Configure credentials:

   Create a file at .streamlit/secrets.toml in the project root with the following structure:

   [meteomatics]
   username = "your_meteomatics_username"
   password = "your_meteomatics_password"

   This file is used by Streamlit to securely provide credentials to the app. Do not use a .env file.

Directory Structure

src/
├── frontend/
│   ├── app.py              # Main Streamlit app entry point
│   ├── ui_helpers.py       # UI components and input widgets
│   └── visualizations.py   # Plotting and visualization utilities
├── data_engine/
│   └── main.py             # Mock data generation logic
└── modeling/
    └── main.py             # Statistical analysis and modeling

Getting Started

Prerequisites

• Python 3.8+
• pip

Installation

Install the required dependencies:

pip install -r requirements.txt

Launching the App

Start the Streamlit application with:

streamlit run src/frontend/app.py

The app will be accessible at http://localhost:8501 in your browser.

Supported Environmental Variables

• Temperature (°C)
• Precipitation (mm)
• Wind Speed (km/h)
• Humidity (%)
• Air Quality Index (AQI)
• Sea Level (m)
• CO₂ Levels (ppm)

Data Source

Some data is mock-generated using NumPy for demonstration. For Meteomatics, you must provide credentials in .streamlit/secrets.toml as described above.

Key Features

• Flexible Location & Date Selection
• Multi-variable Environmental Analysis
• Interactive Charts & Maps
• Risk Probability Calculations
• CSV Export of Results

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Developed for the NASA Earth Observation Challenge.