Multi-Criteria GIS Prioritization of Urban Housing Renovation: A Case Study of Astana, Kazakhstan

Housing-renovation programs in post-Soviet cities typically rely on a single wear-percentage threshold to decide which buildings are demolished, disregarding the building age relative to normative service life, population density, and construction logistics. This study develops a reproducible multi-criteria GIS framework applied to the 174 buildings in Astana’s officially approved 2026–2030 renovation program. Each building was assigned a normative service life, flagged as “Condemned” (wear ≥ 61%) and/or “Dilapidated” (age ≥ normative Lifespan), scored with a composite four-variable Priority index, assigned geographic coordinates through manual online-map search, and linked to an Ordinary Kriging-interpolated population-density surface (heatmap) across all six of the city’s administrative districts. Each building was then assigned one of six differentiated renovation decisions (demolish–expand, demolish–rebuild, demolish–reduce, reconstruct–expand, capital repair, or exclude) based on its condition flags and local density class, and rescheduled across 2026–2030 to equalize the annual floor-area workload. Statistical analysis revealed a significant negative correlation between building age and wear (ρ = −0.157, p = 0.038), no significant effect of wall material on wear once construction types are consolidated into comparable categories (Kruskal–Wallis H = 5.62, p = 0.230), and highly uneven spatial concentration of Condemned buildings across the districts (χ2 = 28.48, p < 0.0001). The rescheduled program reduces year-to-year floor-area imbalance from a coefficient of variation of 41.8% to 4.8%, and four buildings meeting neither condition criterion were identified as candidates for removal from the program. Limitations concerning density resolution, geocoding precision, and criterion weighting are discussed alongside a concrete agenda for spatial clustering of construction logistics, investment-sensitive decisions, and city master-plan integration.