Independent Reproduction of the Lab Urban Environmental Justice of Green Space Access in Chicago

For my final project in the course Open GIScience, I reproduced the lab Urban Environmental Justice of Green Space Access in Chicago within a Python environment using the geopandas geoprocessing package. The project succeeded in reproducing the original QGIS calculated results with geopandas in Python. The analytical aspects of the reproduction process were framed within discourses about reproducibility and replicability within GIS as a discipline or GIScience and urban green space access studies.

I learned two primary lessons during this project: how to better work in geopandas and Python and the labor intensive nature of reproducing even a well documented study. Before the project, I had only edited existing Python scripts that utilized geopandas. The project forced me to dive deep into geopandas documentation and online discussion forums to learn how to work with geopandas. My ability and confidence working with geopandas grew dramatically during the project. The challenges of reproducing existing studies is commonly accepted across scientific disciplines. One challenge is the work required to make a study reproducible. Reproducing the existing lab and documenting the reproduction was time intensive. I did not solely figure out how to reproduce the study. I documented the reproduction in a clear and detailed manner so that another person could understand my process and reproduce my reproduction.

Please follow this link to the entire reproduction study.

Please follow this link to the reproduction study’s Github repository.