Skip to content

The EAMENA machine learning automated change detection (EAMENA MLACD) is a tool developed by EAMENA researchers to rapidly monitor the changes at and around archaeological sites using satellite images.

License

Notifications You must be signed in to change notification settings

eamena-project/EAMENA-MachineLearning-ACD

 
 

Repository files navigation

EAMENA-MachineLearning-ACD

The EAMENA machine learning automated change detection (EAMENA MLACD) is a tool developed by EAMENA researcher Dr Ahmed Mahmoud to rapidly monitor the changes at and around archaeological sites using satellite images.

The tool uses the cloud computing service Google Earth Engine (https://earthengine.google.com/). It was developed using JavaScript and machine learning algorithms (i.e. Random Forest) to produce a time-series of Sentinel-2 images classified by land cover for a user-defined location and time-period, and compares them to determine threats and changes in land cover and use at and around a defined dataset of heritage sites. (Figure 1).

EAMENA_MLACD-Framework Figure 1. EAMENA MLACD Framework.

Figure 2 EAMENA_MLACD_UserInterface Figure 2. EAMENA MLACD User Interface.

About

The EAMENA machine learning automated change detection (EAMENA MLACD) is a tool developed by EAMENA researchers to rapidly monitor the changes at and around archaeological sites using satellite images.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published