/RS_of_Land_Surfaces_laboratory

Notebooks that use Google Earth Engine and CUAHSI to teach and develop remote sensing projects

Primary LanguageJupyter NotebookGNU General Public License v3.0GPL-3.0

Python supported

RS_of_Land_Surfaces_laboratory

This is a series of Jupyter notebooks that integrate Google EarthEngine (GEE) API funtionality into HydroShare in Python 3.x language for the Utah State University CEE/PSC/WATS 5003/6003 Remote Sensing of Land Surfaces Spring class.

Objectives of this git repository:

  • Use HydroShare to teach remote sensing under limited local computing (cloud resources).

  • Showcase ways to do research by combining Google EarthEngine API, Google Drive API, and HydroShare.

  • Bring into Python language available online GEE JavaScript/Python examples.

Current operational status:

This is a funtional version of the repository (April 2020).

How to use this repository:

  1. Open an account in Google Earth Engine https://earthengine.google.com/. It is free.
  2. Open an account in HydroShare https://www.hydroshare.org/ It is free.
  3. In your Hydroshare account, select the "CUAHSI JupyterHub" app and follow instructions.
  4. In server options, select "Python 3.x Scientific" and continue.
  5. Once in JupyterLab, launch a terminal and pass the following command (copy and paste):

git clone https://github.com/torresrua/CEE5003_RS_of_Land_Surfaces_lab_material.git

  1. This repository files will appear in JupyterLab FileBrowser.
  2. Open notebook "Installing Google Earth Engine In HydroShare.ipynb" and follow instructions. You have to do this just the first time.
  3. You can start running the notebooks included in this repository.

NOTE

CUASHI JupyterHub "Python 3.x Scientific" Server option has been tested to be compatible with Qiusheng Wu's GEEMAP tools https://github.com/giswqs/geemap . This repository takes advantage of GEEMAP python implementation.

Best,

2019 Alfonso Torres-Rua

Utah State University

https://cee.usu.edu/people/faculty/torres-alfonso