BACKGROUND: Aerial images are being used more often to map residential structures on the ground in a study area (the sample frame). However, non-coverage bias associated with overhead imagery has not been fully explored. Non-coverage occurs when residential structures are not included in a particular sampling frame. Our study aimed to evaluate non-coverage bias and sensitivity of an aerial photograph methodology in Nueva Santa Rosa, Guatemala, which was used to generate the sampling frame for a larger cross-sectional survey of sanitation, disease, and water quality.
METHODS: High-resolution aerial photographs of Nueva Santa Rosa were overlaid with a grid, and roof images were geo-located within randomly sampled cells, dichotomized by population as very high-density (VHD) or non-VHD. Roofs found on-site were compared to roofs found in photographs to evaluate the numbers and sizes of residences excluded from the sampling frame. Non-coverage proportions were estimated, and sensitivity and specificity were assessed.
RESULTS: There was no statistically significant difference (1.2%; 95% confidence interval, CI= -12.1-14.6) in non-coverage proportion between VHD segments (39.6%) and non-VHD cells (38.4%). Roof-size range sensitivity and specificity were 66.4% (95% CI=57.6–74.2) and 69.4% (95% CI=54.4–81.3).
CONCLUSIONS: Approximately one-third of residential roofs were missed, perhaps due to outdated photographs. No substantial bias concerning population density appeared to influence our sampling frame. Further assessment of non-coverage bias, possibly expanding the roof size range to modify sensitivity and specificity, should be performed to generate geographically based best practices for overhead-image use.
