City of Norfolk | Summer 2026
GIS, Automation, and Public Service in Action
I am Michael Okoroh, a Ph.D. student in Civil and Environmental Engineering at Old Dominion University. Through the Norfolk Emerging Leaders program, I served as an Executive Intern, Municipal Intern II with the City Planning GIS Team from May 18 to July 24, 2026.
Introduction and Career Focus
My academic work centers on water resources, hydraulic systems, and quantitative engineering analysis. Before this internship, I had limited practical GIS experience. Norfolk gave me a chance to add a geospatial layer to my engineering background while learning how mapped information supports planning, communication, and day-to-day municipal decisions.
My professional goal after graduation is to keep building at the intersection of civil and environmental engineering, GIS, Python automation, and data-driven decision support. I want to apply those tools to watershed and flood analysis, infrastructure planning, water-quality assessment, municipal asset management, and environmental decision-making.
Internship Description
The City Planning GIS Team uses spatial records to make planning work clearer, more traceable, and easier to communicate. My assignments started with production GIS work and grew into an automation project with real operational value.
I researched and digitized approved site plans, created polygons for approved site-plan areas, populated required attributes, and supported an online mapping layer. The work taught me that municipal records must be consistent because a small data error can ripple into searches, maps, and planning decisions.
Outcome: contributed multiple years of site-plan information to the growing Site Plan database.I noticed that preparing property-owner mailing lists required repeated manual selections, joins, relates, cleanup, and label formatting. I built a parameter-driven ArcPy workflow that turns request data into mailing-ready outputs.
Esri coursework strengthened the bridge between GIS production, spatial statistics, time-series analysis, imagery analysis, and communication.
Project Highlight
The automation accepts case IDs, GPINs, buffer distances, civic-league rules, and City ownership exemptions. ArcPy then performs source lookups, creates buffers, selects parcels, matches Proval ownership data, removes duplicates, and exports clean Excel records plus Avery 5160 PDF mailing labels.
Learning Objectives - CPT
The internship met my CPT objectives through work that had to be accurate, reproducible, and understandable to the staff who would use it.
Reflection
Early in the automation project, success meant getting the right answer once. As the work developed, I learned to ask harder questions: What happens when a case has multiple parcels? What if selections carry over? What if an owner appears twice, or a label overflows, or repeated database calls slow the process?
Those details changed the project from a script into an operational workflow. I left with stronger GIS skills, more confidence in ArcGIS Pro and ArcPy, and a clearer understanding of how technical work becomes useful when other people can check it, repeat it, and act on it.
Evidence and Training
Photos and Boat Cruise
The internship ended with a boat cruise, and many of the photos capture that closing chapter: a summer of city work seen against the water, alongside office moments, cohort memories, and small details from Norfolk.
The boat-cruise footage sits near the end of the page because it works like the closing scene: after weeks of maps, parcel data, automation, meetings, and learning, the experience ended with perspective.
