Welcome to my curated collection of Spatial Data Science Projects — a living repository where I combine geospatial analysis, data storytelling, and modern Python visualization tools to tackle real-world spatial problems.

This repo is part of my journey to transition into a professional role in Spatial Data Science, while applying my background in GIS, Remote Sensing, and Geospatial Data Integration & Automation.

Focus: Urban analytics, Environmental Monitoring, Accessibility Mapping, Land Use Change, Air Quality Visualization & more. Stack: Python · Streamlit · GeoPandas · Kepler.gl · GEE · Plotly · Leafmap · OSMnx and more.

More projects to follow soon — stay tuned!

• GeoPandas, Shapely, Fiona, rasterio
• Pyproj, Pandas, Numpy

• Plotly, Matplotlib, Seaborn
• Kepler.gl, Leafmap, Deck.gl, Folium
• OSMnx, NetworkX

• Google Earth Engine (GEE)
• EarthPy, SentinelHub, geemap, SAMGeo, Leafmap

• Streamlit, Panel, Dash, Voila for interactive web dashboards

This repository is ideal for:

• Spatial Data Scientists
• GIS Analysts and Researchers
• Data Science Enthusiasts exploring spatial datasets
• Recruiters looking for skilled geospatial professionals

I aim to demonstrate:

• End-to-end project design with reproducible code and insights
• Real-world spatial problem solving with open datasets
• Interactive dashboards for non-technical decision-makers
• Proficiency with Python, Earth Engine, Streamlit, and spatial data science libraries

I’ll be sharing project updates and behind-the-scenes details on LinkedIn & blog posts.
Follow along to see how spatial data can drive real impact!

Follow me on LinkedIn

This repository is licensed under the MIT License.
All datasets used are open-source and credited within each project.

Special thanks to the open-source GIS and remote sensing community for the tools, tutorials, and inspiration that make these projects possible.