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

Project description

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.


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

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

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)

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

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 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
# These items are necessary to function.
project_id: YOUR PROJECT ID
credentials: ~/ee_wildfire_data/OAuth/credentials.json

# OPTIONAL
# These items have default values if not provided in YAML file.
data_dir: ~/ee_wildfire_data
start_date: 2021-01-01 00:00:00
end_date: 2021-04-20 00:00:00
tiff_dir: ~/ee_wildfire_data/tiff/2021
drive_dir: EarthEngine_WildfireSpreadTS_2021
download: false
export: false
min_size: 10000000.0
max_size: 1000000000.0

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

Command-Line Interface (CLI)

Argument Parameters Description
-config PATH Loads a YAML config file located at PATH. This will overload any other command-line arguments.
-show-config None Prints current config to command line.
-export None Export data from Google Earth Engine to Google Drive.
-download None Downloads data from Google Drive to your local machine.

Basic Usage

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

Acknowledgements

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

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