Denver Reimagined: a 3D model of downtown — and the plan to bring it back.
Downtown Denver’s offices are about 39% empty— a record high in early 2026, roughly 12 million square feet dark. But the city isn’t standing still: it adopted the 2025 Downtown Area Plan and stood up the $570M Downtown Denver Development Authority to convert obsolete towers into housing. This is an interactive 3D model of the real downtown core and a year-by-year scenario of that plan playing out from 2026 to 2040.
It runs on real Denver open data (building footprints and heights), with a simulation layered on top. It is a scenario, not a forecast — it shows direction and sequencing, not a prediction.
How to read it
- Scrub the timeline (2026→2040) to watch empty towers convert to housing, crime density fall, and new transit links switch on.
- Tap any building for its real data and what the plan does to it.
- Toggle layers — vacant towers, crime density, new transit links, graffiti.
- Reimagine it — drop in your own ideas and share your version.
The plan, in four phases
Phase 1: Stabilize & Light 2026–2028
Safety, lighting, 24-48 hr graffiti abatement, secure and assess empty towers, and fix zoning so conversions are legal. Nothing else works until the core feels usable.
Phase 2: Convert 2029–2032
Adaptive reuse of obsolete offices into housing and mixed-use with DDDA gap financing. Ground-floor activation, residents arrive, vacancy falls.
Phase 3: Connect 2033–2036
Transit super-hub, protected bike + greenway network, and new Platte/Cherry Creek crossings knit the core to every neighbor.
Phase 4: Civic Heart 2037–2040
Consolidate the scattered center into one central common, cultural core, and transit plaza. Downtown finally has a middle.
Where it’s headed: 2026 → 2040 targets
- Office vacancy39% → 11% %
- Crime index100 → 55 2026=100
- Net new downtown homes0 → 7,500 homes
- Foot traffic90% → 122% % of 2019
Reimagine downtown
What if downtown Denver went bigger? Explore what these would look like — and what it’d take to build them:
Grounded in open data
Every layer ties to a named public dataset. Crime renders as aggregated density only, never addresses. Vacancy is a derived likelihood shown with its reasons, never asserted about a named building.