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bychahinez/Wildfire-Vegetation-Analysis-Tizi-Ouzou-August-2021-

Domaine:

environment and energygeospatial

Type de record:

project
Créateur:
byc
Hôte:
This project uses Google Earth Engine and geemap in Google Colab to analyze wildfire impact and vegetation health in Tizi Ouzou, Algeria during August 2021. It calculates: NBR (Normalized Burn Ratio) → highlights burned areas and burn severity. NDVI (Normalized Difference Vegetation Index) → assesses vegetation health. # Wildfire Analysis: Tizi Ouzou (August 2021) This project uses Google Earth Engine and geemap in Google Colab to analyze wildfire impact and vegetation health in Tizi Ouzou, Algeria during August 2021. # Project Overview This project analyzes and classifies burned vs. unburned areas caused by the August 2021 wildfires in Tizi Ouzou, Algeria using satellite imagery and machine learning. Using Sentinel-2 satellite data from the European Space Agency and Google Earth Engine, we compute multiple spectral indices and train a Random Forest classifier to automatically detect burned areas. The result is an interactive map showing Burned vs Unburned Areas # 🌍 Study Area ## 📍 Tizi Ouzou, Algeria ## Wildfire period: August 20 – September 10, 2021 # 🛰️ Data Source Satellite Imagery: European Space Agency Sentinel-2 Dataset: Google Earth Engine – COPERNICUS/S2_SR_HARMONIZED # Spectral Indices Computed To improve burn detection accuracy, multiple indices were calculated: • NBR – Normalized Burn Ratio (burn severity detection) • NDVI – Vegetation health • NDWI – Water/moisture detection • MSAVI – Soil-adjusted vegetation index • SWIR/NIR Ratio – Fire damage sensitivity These indices enhance separability between burned and unburned surfaces. # Machine Learning Model Algorithm: Random Forest 100 trees

Visit

github.com

Tasks

computer visionimage classification

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