Characterizing manufactured home parks in North Carolina: A computer vision based approach
This study uses a computer vision-based approach to identify manufactured home parks (MHP) across North Carolina, addressing the critical lack of comprehensive public records for these vulnerable housing communities. Using high-resolution aerial imagery, a custom-trained YOLOv8 object detection model, building footprints, and parcel records, we identified 8460 MHP—more than three times the size of the largest current public dataset. The precision and recall of our model are over 93%, in detecting individual manufactured housing units. Results reveal that while large and medium-sized MHP are predominantly an urban phenomenon, small MHP (fewer than 50 units) constitute 95% of all identified parks, with over 67% of these small parks located in rural areas, and are concentrated in southeastern, central, and southwestern counties. This approach enabled comprehensive identification of MHP, supporting better-informed planning for these often overlooked but critical affordable housing options.
Authors
- Nikhil Kaza (ORCID: https://orcid.org/0000-0002-9536-7643)
- Miyuki Hino (ORCID: https://orcid.org/0000-0001-9369-5769)
- Kshitiz Khanal (ORCID: https://orcid.org/0000-0002-4765-4832)
- Antonia Sebastian (ORCID: https://orcid.org/0000-0002-4309-2561)
Institutions
- University of North Carolina at Chapel Hill (US)
Publication Details
- Journal
- Environment and Planning B Urban Analytics and City Science
- Published
- 2025-11-14
- DOI
- https://doi.org/10.1177/23998083251395471
- Primary Topic
- Impact of Light on Environment and Health
- Type
- article
- Field-Weighted Citation Impact
- 0.00