Tracking Water Hyacinth Movement at Hartbeespoort Dam

This project predicts and controls water hyacinth at Hartbeespoort Dam.

This project uses predictive modeling to track and control the spread of invasive water hyacinth at Hartbeespoort Dam. By analyzing weather data and satellite imagery, the system provides real-time updates, an interactive map, and predictive insights for stakeholders like environmental agencies and researchers.

Built with Django and Python, the web-based platform integrates a machine learning model that forecasts hyacinth growth up to seven days in advance. This enables proactive ecological management strategies to mitigate the impact of the invasive species.

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