A simple Flask web application for performing change detection tasks with Google Earth Engine imagery *.

The AppEngine version (web version) is for demonstration only and has very limited functionality. Exporting results to Google Drive or to Earth Engine assets is in particular not possible.

The local version runs in a Docker container serving the Flask web application on localhost:5000. Assuming you have been authenticated (see below) to the Earth Engine, you can carry out the following tasks:

1. Run the iMAD (iteratively re-weighted MAD) algorithm on Landsat 5, 7, 8 and Sentinel-2 optical/infrared bitemporal imagery.

   A. A. Nielsen (2007). The Regularized Iteratively Reweighted MAD Method for Change Detection in Multi- and Hyperspectral Data.

   M. J.Canty (2014). Image Analysis, Classification and Change Detection in Remote Sensing, 3rd Ed., CRC Press 2014;

2. Run the (sequential) omnibus algorithm on polarimetric SAR multitemporal data on Sentinel-1 dual pol, diagonal only, or single pol images.

   K. Conradsen et al. (2016). Determining the points of change in time series of polarimetric SAR data. IEEE TGRS 54 (5) 3007-3024.

3. Export imagery to your Earth Engine assets folder or to Google Drive for off-line local processing, for example with SARDocker.

1. Install Docker

2. In a command window execute the command

   docker run -it -p 5000:5000 --name=ee mort/eedocker 
   

   or, if you are on a Raspberry Pi

   docker run -it -p 5000:5000 --name=ee mort/rpi-eedocker		
   

3. If the container is not found it will be automatically downloaded from Dockerhub and started. At the container prompt execute the command

   earthengine authenticate
   

   and follow the instructions. You will have to copy the given URL and paste it into your local browser.

4. After successful authentication the credentials are saved to the container. Now run the command

   ./app.py
   

   and point your browser to

   localhost:5000
   

   to start work.

5. When finished, hit

   Ctrl C 
   

   in the command window to stop the Flask application server and

   exit 
   

   to leave the container. The container will then stop.

6. Re-start and enter the container with

   docker start -ai ee
   

7. Run the command

   ./app.py
   

   to re-start the server.