This cross-disciplinary project focused on investigating and visualizing the biodiversity of tree populations across five educational campuses: Patrician College of Arts and Science, St. Patrick's Anglo-Indian School, St. Patrick's ICSE School, St. Michael's School, and the Children's Block. Over the course of three months, we conducted detailed field surveys to record species types, tree counts, and spatial coordinates. By integrating Geographic Information Systems (GIS) with Python-based analysis, we transformed ecological field data into dynamic visual insights. The project aimed to support sustainability initiatives, guide green infrastructure planning, and promote biodiversity awareness through interactive mapping and data storytelling.
- Catalogue and classify tree species across multiple campuses
- Quantify and visualize species abundance and distribution
- Develop geospatial visualizations using interactive maps
- Implement an end-to-end analytical workflow using Python
- Deliver actionable ecological insights to stakeholders
A combination of data science libraries and GIS platforms was used to build an efficient and reproducible analysis pipeline:
- Field-based biodiversity surveying
- Data cleaning, integrity checks, and preprocessing
- Exploratory and statistical data analysis
- Interactive and visual storytelling with maps
- Environmental reporting and communication
📁 project-root/ ├── 📂 data/ │ └── trees_dataset.xlsx ├── 📂 notebooks/ │ └── tree_analysis.ipynb ├── 📂 images/ │ └── charts, dashboard └── 📄 README.md
A visual walkthrough of the analysis outputs — from interactive GIS maps and species distribution charts to biodiversity dashboards, tree count analysis, and campus comparison visualizations built in Python.
The survey recorded a total of 892 individual trees across 48 distinct species. Our analysis identified zones of high species concentration — biodiversity hotspots — as well as areas with limited variety, indicating opportunities for ecological enhancement. The interactive maps provide an intuitive way to explore spatial patterns in tree distribution and can assist campus planners and educators in making informed, sustainable decisions.
This project exemplifies how data science and GIS can be harnessed to support ecological resilience in urban environments. By bridging environmental research with computational tools, we created a comprehensive, interactive biodiversity profile of five campuses. The insights gained not only contribute to current sustainability efforts but also serve as a foundation for long-term biodiversity management. The initiative demonstrates the value of using technology to protect and enhance green spaces in educational institutions and beyond.