Project Summary

Earth-Engine-Wildfire-Data is a Python command-line utility and library for extracting and transforming wildfire-related geospatial data from Google Earth Engine. It supports:

• Access to MODIS, VIIRS, GRIDMET, and other remote sensing datasets.

• Filtering wildfire perimeters by date, size, and region.

• Combining daily and final fire perimeters.

• Generating YAML config files for use in simulation or prediction tools.

• Command-line configurability with persistent YAML-based settings.

• This tool is intended for researchers, data scientists, or modelers working with wildfire data pipelines, particularly those interested in integrating Earth Engine datasets into geospatial ML workflows.

• The Trello page contains the current development status.

Prerequisite

Requires at least python 3.10.

As of mid-2023, Google Earth Engine access must be linked to a Google Cloud Project, even for free/non-commercial usage. So sign up for a non-commercial earth engine account.

🔐 Google API Setup Instructions

To run this project with Google Earth Engine and Google Drive access, follow the steps below to create and configure your credentials.

Step 1. Create a Google Cloud Project

• Go the Google Cloud Console.
• Click the project drop-down (top bar) -> New Project.
• Name your project (eg., ee-wildfire) and click Create.

Step 2. Enable Required APIs

• Earth Engine API
• Google Drive API

Step 3. Create a Service Account

• In the left sidebar: IAM & Admin → Service Accounts.
• Click + Create Service Account.
• Name it (e.g., wildfire-access) and click Create and Continue.
• Assign the following roles to the service account:
  • Owner
  • Service Usage Admin
  • Service Usage Consumer
  • Storage Admin
  • Storage Object Creator
• On the list, find your service account → Click Actions (⋮) → Manage keys.
• Under Keys, click Add Key → Create new key → JSON.
• Save the downloaded JSON file somewhere safe (e.g., service_account.json).

Step 4. Share Google Drive Folder

If your code needs to read/write to Google Drive:

• Create a folder in Google Drive.
• Right-click → Share.
• Share it with your service account email (e.g., your-sa@your-project.iam.gserviceaccount.com).
• Grant Editor permission.

Install Instructions

For the stable build:

pip install ee-wildfire

For the experimental build:

git clone git@github.com:KylesCorner/Earth-Engine-Wildfire-Data.git
cd Earth-Engine-Wildfire-Data
pip install -e .

Configuration

This program uses a YAML file for user configuration.

Template for configuration:

# NEEDED

# You need a google cloud service account JSON, if not provided here the program
# will prompt you for one
credentials: ~/ee_wildfire_data/OAuth/credentials.json

# OPTIONAL
# These items have default values if not provided in YAML file.

# Fire query
min_size: 10000000.0

max_size: 1000000000.0

start_date: 2021-01-01 00:00:00

end_date: 2021-04-20 00:00:00

# Directories
tiff_dir: ~/ee_wildfire_data/tiff

data_dir: ~/ee_wildfire_data

log_dir : ~/ee_wildfire_data/logs

google_drive_dir: GoogleEarthEngine

# Pipeline
purge_before: false

download: false

export: false

retry_failed: false

purge_after: false

# Logs
no_log: false

log_level: info # levels: debug, info, warn, error

# Misc
silent: false

To finish configuration you will need to use the -config command line argument.

Command-Line Interface (CLI)

You can also edit configuration on the fly with command line arguments:

Basic Usage

ee-wildfire --config /path/to/some/config.yml

ee-wildfire --credentials PATH_TO_CREDS --export --download --min-size 10 --log-level warn

Acknowledgements

This project builds on work from the WildfireSpreadTSCreateDataset. Credit to original authors for providing data, methods, and insights.