Objective: The goal of this project was to conduct spatial analysis and create static and interactive maps using only Python programming. The analysis identifies high-risk areas in Hillsborough County, Florida, where industrial facilities that manage hazardous materials are in or close to high-risk flood zones and socially vulnerable communities. Flooding events make it more likely for certain industrial facilities to be damaged, leading to a release of toxic materials into the surrounding environment. Socially vulnerable communities face the greatest risks associated with such releases. The static maps display various layers of industrial facilities, flood zones, social vulnerability, and census demographic variables. The interactive map aims to put these layers together and rank the facilities by the level of threat that they pose.

Methodology: I collected information about industrial facilities that manage hazardous materials in Hillsborough County from 3 datasets. These datasets include wastewater facilities, oil tankers, and manufacturing plants. I then created a batch address geocoder to pinpoint the location of these facilities. Next, I brought in social vulnerability and flood zone datasets to identify high-risk areas using various geoprocessing tools in the command line. Lastly, I created static and interactive maps using different Python packages such as Folium and Contextily. The maps, as well as a more detailed description of the data and methodologies used to create the project is hosted on a github page.

Created for: Command line GIS course final project

Software and tools used: Data cleaning, GIS analysis, geoprocessing, and cartographic design done in Python using various geopandas and GIS packages on google colab. Project hosted on github and formatted using markdown language.