/landsat-bigquery

Summarizing 51 years of Landsat data using Earth Engine and BigQuery

Primary LanguagePython

Summarizing Landsat with BigQuery

This is a demo project using the Earth Engine-BigQuery connector to export every Landsat scene to a BigQuery table where they can be queried, summarized, and visualized to create the animation below.

clear_scenes_1972-2023.mp4

Check out the accompanying blog post for more details.

Setup

Install Python dependencies from PyPI.

python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt

You'll need gcloud to authenticate BigQuery. If you have snap, you can install it with:

sudo snap install google-cloud-cli --classic

Otherwise, follow the instructions here.

Then run:

gcloud init && gcloud auth application-default login

Set the following in src/config.py:

  • CLOUD_PROJECT: The name of the Google Cloud Project to store tables under.
  • DATASET_ID: The name of the BigQuery dataset that you manually created in that cloud project.
  • TABLE_ID: The name of the table that will be generated on export.

Usage

  1. Run python export.py to generate the BigQuery table with all Landsat scenes. Wait for the task to complete.
  2. Run python queries.py to execute queries and generate outputs.