Building density and its implications to COVID-19 health risk management: An example from Yogyakarta, Indonesia

Abstract Transmission rates of COVID-19 have been associated with the density buildings where contact among individuals partially contributes to transmission. The research sought analyze spatial distribution building derived from satellite images and determine its implications health risk management using Yogyakarta surrounding districts as an example. Fine-scale obtained through remote sensing data transformation was analyzed GIS. NDBI applied Landsat 8 imagery; then, multiple linear regression analysis, it correlated density’s training samples generated high-resolution imagery. percent (PBD) combined publicly available records infection assess risk. This found that PBD could explain uneven diffusion at different stages development. Instead dividing regions into zones based on confirmed cases, government public officials should observe new cases in high-PBD districts; when are decreasing, their attention shift low-PBD districts. Remote allow for moderate-scale mapping integrating produces risks, determining target areas interventions allowing regionally tailored responses anticipate or prevent next wave infections.