Every semester, her 120 students would create beautiful, complex GIS projects—analyzing flood zones, mapping food deserts, tracking wildfire spread. But when a student accidentally saved over a shapefile, or when a group of four tried to collaborate on a single ArcGIS Pro project, chaos ensued. Emails with attachments named final_map_v3_REAL_FINAL.aprx flooded her inbox.
But the students in Geography 76 were learning a new kind of geography: . They wrote Python scripts using geopandas , rasterio , and folium . They built interactive maps with leaflet.js . Their projects weren’t just maps—they were reproducible geospatial analyses . geography 76 github
The problem was .
Then she discovered that , the world’s largest repository of code, had quietly become a powerful tool for geographers. The Problem with Traditional GIS Workflows Traditional GIS work—whether in ArcGIS, QGIS, or GRASS—relies on binary files ( .shp , .gdb , .geotiff ) that don’t play nicely with standard version control. You can’t “diff” two shapefiles the way you can with Python or R scripts. A single corrupted polygon could destroy weeks of work. Every semester, her 120 students would create beautiful,