Harmonizing Tourism and Nature Protection in the Bavarian Forest National Park 💡

This project was a part of Data Science for Social Good (DSSGxMunich) 2024. The goal of this project was to harmonize tourism and nature protection in the Bavarian Forest National Park. We aimed to develop a data-driven approach to monitor traffic, using sensor and survey data, to understand the impact of tourism on the park’s ecosystem. The project involved data collection, analysis, predictive modeling, and visualization to provide insights for park management and policy-making.

We worked with an interdisciplinarz group of economists, social scientists and computer scientists to contribute to the project in the following ways:

• Develop a data pipeline to harmonize the data collected from the all the different sensors and external sources.
• Implement a predictive model to forecast the visitor traffic in the park for the coming week.
• Develop a dashboard to visualize the data and insights for the park management, along with visualizing the forecasted visitor traffic from the predictive model.
• Create technical documentation to provide insights on the data pipeline, predictive model and suggestions for future improvements in the project.

Currently, the project is in the process of being deployed and will be available for public use soon. We are also working on a manuscript to document our findings and methodologies in detail.