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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.

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AhmedMAMahmoud/EAMENA-MachineLearning-ACD

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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.

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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.

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