/ee-atmcorr-timeseries

Atmospherically Corrected Time Series using Google Earth Engine

Primary LanguagePythonApache License 2.0Apache-2.0

Introduction

Atmospherically corrected, cloud-free, time series of satellite imagery from Google Earth Engine using the 6S emulator.

Installation

Recommended: Docker

The following Docker container has all dependencies to run the code in this repository

docker pull samsammurphy/ee-python3-jupyter-atmcorr-timeseries:v1.7

Alternative: Conda

Install Anaconda.

Install the Earth Engine API:

pip install google-api-python-client
pip install earthengine-api 

Usage

Recommended: Docker

Run the docker container with access to a web browser

docker run -i -t -p 8888:8888 samsammurphy/ee-python3-jupyter-atmcorr-timeseries:v1.7

Once inside the container, authenticate Earth Engine

earthengine authenticate

(tip: you can save your credentials, and avoid repeating this step, using docker commits)

Run the example jupyter notebook

cd ee-atmcorr-timeseries/jupyter_notebooks/
jupyter-notebook ee-atmcorr-timeseries.ipynb --ip='*' --port=8888 --allow-root

this will print out a URL that you can copy/paste into your web browser to run the code.

Alternative: Conda

If necessary, create a python3 environment

conda create -n my_python3_env

and activate it..

source activate my_python3_env

.. if on Windows the command is a bit shorter:

activate my_python3_env

Authenticate the Earth Engine API.

earthengine authenticate

clone this repository

git clone https://github.com/samsammurphy/ee-atmcorr-timeseries.git

run the jupyter notebook

cd ee-atmcorr-timeseries/jupyter_notebooks
jupyter-notebook ee-atmcorr-timeseries.ipynb