The repository serves as a portfolio for geospatial analysis with Python. Python code presented in the repository is completed as part of academic work and reflects the usage of near real-time data (Jan - May 2023). I took Geog 573 during Spring 2023, and the course was taught by Professor Song Gao, a renowned professor in the geospatial data science domain and director of GeoDS Lab in the department of Geography, University of Wisconsin - Madison. The repository is made public for geospatial enthusiasts and students seeking knowledge in the intersectoral domain of Geography + Computer Science.
- Observations from application of Moran's I, Geographic Weighted Regression (GWR) using PySAL geospatial analysis library. The below image shows the distribution of wasted votes [1] for Democrats during the presidential election 2020 in Madison, WI. Where a hotspot showcases strong spatial autcorrelation of wasted votes and coldspot showcases a weak spatial correlation of wasted votes.
- Snapshot of Airbnb median price variation based on mean bedrooms and review score values in Austin, Texas using GWR
- Google Earth Engine (GEE) map is a powerful geospatial analysis tool that uses power of Google data to create distinct and large-scale map products developed by Professor Quisheng Wu from University of Tennessee, Knoxville. [2] As part of analysis, I was able to create a timelapse of Las Vegas, Nevada that depicts urban growth and how urban analysis is important.
