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Wildfire Monitoring -- Portugal (ETL Workflow)

This repository contains an end-to-end workflow for extracting, transforming, and loading (ETL) Earth observation data to support wildfire monitoring and environmental analysis in Portugal.

The project integrates multiple geospatial datasets from Google Earth Engine (GEE) and Meteostat to generate per-tile environmental indicators (NDVI, soil moisture, brightness temperature, and local weather conditions).

Note:

  • All heavy computations are performed on servers such Google Earth Engine or Meteostat.
  • You can reproduce the environment using.
conda env create -f environment.yml -n fire-etl
conda activate fire-etl

Project Structure

├── data/
│   ├── csv/          # Processed exports from Earth Engine & Meteostat
│   ├── geojson/      # Country grid and geometry inputs
│   └── ...
├── extract_transform_load_data_1.ipynb
├── extract_transform_load_data_2.ipynb
├── environment.yml   # Conda environment definition
├── .gitignore        
└── README.md

Data Sources

Dataset Description Source
MODIS MOD13Q1 v6.1 16-day NDVI, 250 m resolution NASA / MODIS
SMAP SPL3SMP_E (v005–v006) 9 km enhanced soil moisture, merged across versions NASA SMAP
FIRMS / MODIS T21 Brightness temperature per detected fire pixel NASA FIRMS
Meteostat Daily Local weather (temperature, precipitation, etc.) Meteostat API

Setup

1. Run the ETL notebooks

Execute the notebooks in order:

  • extract_transform_load_data_1.ipynb: Create the grid and export NDVI, SMAP, FIRMS data per tile.
  • extract_transform_load_data_2.ipynb: Retrieve weather conditions from Meteostat for each tile.