mayank-kumar03/FWI_calculator_algerian_forest

# 🔥 Forest Fire Area Prediction --- ## 🌱 About the Project **Forest Fire Area Prediction** is a machine learning web application that predicts the **area affected by a forest fire** based on several environmental and regional parameters. ### R2 Score : 0.9842993364555512 🔗 **Live App**: Click Here to Use the Application ## 🎯 Real-World Use Case Forest fires are becoming more frequent due to climate change. Early prediction of the **scale of destruction** helps stakeholders take preventive actions. This system: - 📈 Predicts **how much area might burn** under specific weather conditions. - ⚠️ Aims to **assist forest departments, environmental agencies**, and **disaster response units**. - 🌱 Helps preserve **biodiversity**, **forests**, and **minimize CO₂ emissions**. ## 🖼 Screenshots --- ## 🚀 Tech Stack - 🐍 Python 3.8+ - 🌐 Flask (Web Framework) - 🤖 Scikit-learn (Machine Learning) - 📦 Pickle for model storage - 🧪 Ridge Regression - 🖥️ HTML (Jinja templates) --- ## 🧠 How It Works 1. User inputs weather and fire parameters in the web form. 2. Data is normalized using `StandardScaler`. 3. A trained Ridge Regression model predicts the affected area. 4. The result is displayed on a separate webpage. --- ## 🔍 Interpreting FWI Values | **FWI Value** | **Fire Danger Level** | **Meaning** | |-----------------|------------------------|-------------| | 0.0 – 5.0 | 🔵 **Low** | Fires are unlikely or easily controlled. | | 5.1 – 12.0 | 🟡 **Moderate** | Fires may start and require attention. | | 12.1 – 30.0 | 🟠 **High** | Fires spread quickly and require active suppression. | | 30.1 – 50.0 | 🔴 **Very High** | Fires ignite easily, spread rapidly. | | > 50.0 | ⚫ **Extreme** | Explosive fire behavior; immediate emergency action needed. | --- ## 📥 Input Parameters | Feature | Description | |------------|------------------------------------| | Temperature| …