Urban Planning & Smart Cities

City Development

Validate city development scenarios, land use configurations, and infrastructure demands — enabling data-driven decisions before planning and capital are committed.

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Also in Urban Planning & Smart Cities Smart Cities Compact City 15-Minute City Masterplanning Land Use Prediction Amenity Planning
Aerial view of a city development zone with land use planning overlays and infrastructure data
Trusted by
TAKENAKA Jacobs EMAAR McKinsey Dubai Municipality egis
The Problem

Fragmented city development planning creates late-stage surprises

City development projects span multiple land parcels, stakeholders, and planning systems. Fragmented feasibility workflows — where land use, infrastructure, and sustainability are assessed separately — create late-stage surprises that delay delivery, increase cost, and erode the confidence of planning authorities and investors.

Without DBF With DBF
Land use configurations and density scenarios validated separately
AI generates and scores 50+ city development scenarios against planning and investment KPIs
Infrastructure capacity checked late in planning
Infrastructure demands modelled from development scenarios before planning is submitted
Sustainability targets addressed after spatial planning
Sustainability and liveability KPIs integrated from the first scenario
Stakeholder alignment built on limited scenario evidence
Comparable scenario outputs ready for authority and investor reporting from day one
Process

How It Works

01
Data Ingestion

Upload site boundaries, GIS data, demographic datasets, and planning policy constraints. DBF integrates multi-source data into a single spatial model.

02
Scenario Generation

AI generates 50+ development scenarios — each scored against planning, liveability, sustainability, and infrastructure KPIs simultaneously.

03
Spatial Analysis

Every land use configuration, density gradient, and infrastructure relationship is evaluated. Conflicts and opportunities surface with spatial evidence.

04
KPI Scoring

Scenarios are automatically scored against liveability, sustainability, infrastructure capacity, and planning policy compliance.

05
Stakeholder Comparison

Comparable scenario outputs ready for planning authority, investor, and community stakeholder review from day one — not after weeks of consultant work.

06
Authority Reporting

Planning-authority-ready evidence outputs and spatial data exports delivered from the feasibility stage — not the planning application stage.

Platform

Built for city-scale development planning

Every DBF capability is designed for the specific demands of city development — where land use, density, infrastructure, and sustainability interact across multi-parcel, multi-stakeholder planning processes.

  • AI city development scenario generation
  • Land use and density configuration analysis
  • Infrastructure demand modelling
  • Sustainability and liveability KPI integration
  • Multi-stakeholder scenario reporting
  • Planning-authority-ready outputs
Who Uses DBF

Use Cases

City development planning team reviewing land use scenarios and infrastructure capacity analysis
01
Municipal Government
Planning Director

Validate city development scenarios against planning policy, infrastructure capacity, and sustainability targets — building the evidence base for faster planning decisions.

02
Property Developers
Development Director

Test city-scale development configurations against infrastructure investment, planning constraints, and investor return targets before committing to planning applications.

03
Government Agencies
Infrastructure Head

Assess city development scenarios against infrastructure capacity, economic development targets, and demographic demand forecasts simultaneously.

04
AEC Consultancy
Project Director

Deliver faster, more evidence-based city development feasibility with validated spatial scenarios, KPI scoring, and planning-authority-ready outputs.

50+
Scenarios Validated
Per planning cycle
Multi-source
Data Integration
GIS, infrastructure, economic
Pre-design
Full Pipeline
Evidence before planning
Future Vision

Planning cities that compete for investment and deliver for people

As cities compete for investment and face growing housing and infrastructure pressures, city development planning must become faster and more data-driven. The evidence base for planning decisions will need to be stronger, the scenarios more comprehensive, and the reporting more comparable. DBF enables teams to validate development scenarios earlier — delivering the spatial evidence that helps planning authorities make faster decisions and investors commit with greater confidence.

Future vision of evidence-based city development with sustainable, liveable mixed-use districts
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