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.

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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
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article

Characterizing manufactured home parks in North Carolina: A computer vision based approach

Nikhil Kaza, Miyuki Hino, Kshitiz Khanal, Antonia Sebastian
Environment and Planning B Urban Analytics and City Science
Impact of Light on Environment and Health
article

Characterizing manufactured home parks in North Carolina: A computer vision based approach

Nikhil Kaza, Miyuki Hino, Kshitiz Khanal, Antonia Sebastian
article en

Abstract

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.

Environment and Planning B Urban Analytics and City Science
University of North Carolina at Chapel Hill (US)
Openalex Percentile: Top 68%
Impact of Light on Environment and Health
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Characterizing manufactured home parks in North Carolina: A computer vision based approach — Nikhil Kaza, Miyuki Hino, et al. · Environment and Planning B Urban Analytics and City Science (2025) | TGRS Research Map | TGRS