ee-wildfire 2025.1.4

Pulls data from Google Earth Engine, syncs it to Google Drive, and downloads files.

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.

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1. ✅ Create a Service Account

In the Google Cloud Console, do the following:

• Go to IAM & Admin → Service Accounts → Create Service Account
• Assign the following roles to the Service Account:
  • Owner
  • Service Usage Admin
  • Service Usage Consumer
  • Storage Admin
  • Storage Object Creator

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2. 🔑 Assign Roles to Your Personal Account

Make sure your main Google Cloud account (the one you'll log in with) has these roles:

• Owner
• Service Usage Admin
• Service Usage Consumer

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3. 🧭 Create OAuth Credentials (for Google Drive Access)

Still in the Google Cloud Console:

• Go to APIs & Services → Credentials → + Create Credentials → OAuth Client ID
• If prompted, configure the OAuth consent screen:
  • Choose Desktop App
  • Provide a name (e.g., "Drive Access")
• Once created:
  • Download the JSON file (this is your OAuth credentials)
  • Save the client_id and client_secret (you’ll use these in your config)

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4. 🚀 Enable Required APIs

In the left-hand menu:

• Go to APIs & Services → Library
• Enable the following APIs:
  • Google Drive API
  • Google Earth Engine API

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5. 👤 Add Test Users (Required for OAuth)

• Go to APIs & Services → OAuth consent screen
• Scroll to the Test Users section
• Click + Add Users and add your personal Google account (the one you'll use for authentication)

Install Instructions

For the stable build:

pip install ee-wildfire

For the experimental build:

git clone [e-mail]:KylesCorner/Earth-Engine-Wildfire-Data.git
cd Earth-Engine-Wildfire-Data
pip install -e .

Configuration

Template for configuration:

project_id: YOUR PROJECT ID # google cloud api project id for earth engine
data_dir: ~/ee_wildfire_data/ # Directory to store all the data for this program.
year: '2021' # year to batch
month: '1'
min_size: 10_000_000 # minimum size of fire image
download: false # flag to download data?
export: false # flag to export data?
force_new_geojson: false # some times when attempting to export large amounts of data it fails and corrupts the geojson param file. This regenerates it.

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

Command-Line Interface (CLI)

Argument	Description
-config PATH	Loads a YAML config file located at PATH.
-show-config	Prints current config to command line.
-export	Export data from Google Earth Engine to Google Drive.
-download	Downloads data from Google Drive to your local machine.
-force-new-geojson	Forces the creation of new geojson fire parameters.

Basic Usage

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

ee-wildfire -force-new-geojson -export -download

Acknowledgements

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