Roots of Resilience: Leveraging GIS and Python to Map Campus Biodiversity Hotspots

Project Overview

This interdisciplinary project aimed to analyze and visualize the biodiversity of tree populations across five educational institutions: 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 a span of three months, we conducted a comprehensive ecological survey and created an interactive geospatial representation of the tree distribution using Python and GIS tools. The initiative focused on collecting detailed data on tree species, geographic coordinates, and population counts to gain insights into spatial patterns, species richness, and ecological health. Through a data-driven methodology, the project offered actionable knowledge for biodiversity conservation and environmentally sustainable campus development.

Objectives

This project aimed to analyze biodiversity across five campuses by leveraging spatial data and Python-based tools. The goal was to provide insights into tree distribution, species richness, and ecological balance to support sustainability efforts.

• To systematically document and classify tree species across the campus zones.
• Analyze distribution by type, name, and quantity
• Generate professional visualizations
• Map tree locations interactively
• Build a complete analysis pipeline

Technologies Used

A range of data analysis and visualization technologies were used to streamline workflows, handle large datasets, and build interactive spatial maps. The integration of these tools enabled the transformation of raw ecological data into actionable insights.

• Python (Jupyter Notebook)
• Pandas, NumPy
• Matplotlib, Seaborn
• Folium (for mapping)
• Microsoft Excel (data entry and cleaning)

Skills

This project reflects a multidisciplinary skill set in environmental research, data science, and geospatial technology. From manual field surveys to creating professional, interactive maps, each stage highlighted the practical application of technical and analytical skills.

• Manual field data collection
• Data cleaning and validation
• Exploratory Data Analysis (EDA)
• Professional data visualizations
• Geospatial mapping
• Insightful project reporting

Structure

📦 project-root/
├── 📂 data/
│   └── trees_dataset.xlsx
├── 📂 notebooks/
│   └── tree_analysis.ipynb
├── 📂 images/
│   └── charts, dashboard screenshots
└── 📄 README.md
    

Conclusion

This project highlighted the significance of integrating computer science and environmental science to promote ecological sustainability. Through the documentation and analysis of 892 trees across 48 different species, we identified key biodiversity hotspots and areas needing ecological attention. The interactive maps and statistical findings generated during the study offer practical applications for campus management, educational engagement, and future environmental planning. The successful execution of this project stands as a testament to the power of data analytics in ecological conservation and underscores the importance of using technology to build resilient, sustainable urban ecosystems.