Using Existing Conditions in ArcGIS Urban

Urban planners are facing a common challenge: supporting growth without further driving urban sprawl. Infill development or densification—adding density within existing urban areas—has therefore become a key strategy to make better use of existing infrastructure and improve housing availability. To successfully pursue this approach, it is essential to analyze and understand existing conditions, as they form the foundation for a realistic and effective densification workflow.

In this blog post, you’ll learn how to model existing conditions in ArcGIS Urban by working with existing building spaces and parcel parameters. You’ll see how these approaches help establish a reliable baseline for densification workflows and support informed decision‑making when exploring future development scenarios directly in Urban.

Existing building spaces 

As an urban planner, you might be tasked with transforming an urban area. Before you can start exploring different strategies, you need to know what’s already there, both visually and quantitatively. Working with existing spaces in Urban allows you to get an overview of the current urban fabric to base your development on.  

As an example, we focus on MFO-West in Zürich, Switzerland, a former industrial site transitioning into a mixed‑use urban quarter. In the following paragraphs you learn how to create and edit existing spaces as well as how to use them for different densification strategies in Urban based on this example project. 

Represent existing buildings as spaces 

Let’s start by creating building spaces based on existing buildings. Currently, this is done by manually tracing the schematic buildings from the basemap of your Urban model in the existing scenario—a workflow that will become more automated in a future release. As soon as you’ve recreated the ground floor, simply choose the space-use type of the building, duplicate the floors to model the building’s upper-levels, and adjust floor geometries where needed.  

The spaces have the development status “Unchanged” assigned, meaning these spaces are existing spaces. The development status will become important when exploring different densification strategies later. Continue creating existing spaces for all the buildings you want to include in your existing conditions. 

Copy building spaces to design scenarios

When you’re finished with tracing the buildings in the existing scenario, you can copy the parcels into a design scenario to start transforming the area. Alternatively, you can also create a new scenario based on the existing scenario. With the existing spaces copied into the design scenario, we can now start to explore different densification strategies.

Strategy 1: Repurpose building spaces

A common example for repurposing existing spaces is an office space that is no longer required due to evolving work‑from‑home policies. To reactivate these valuable spaces, we can repurpose them to apartments.

In our MFO-West example, we reuse the upper floors of an existing industrial hall as cultural space, hosting art galleries, youth programs, and other social projects. In ArcGIS Urban, repurposing a space is done in a design scenario by changing its space‑use type. The development status automatically updates to “Repurposed”, indicating that the space already exists but is assigned a new use.

Strategy 2: Extend and retrofit existing buildings

Another approach is to add new floors on top of existing structures. In our example, we build up the existing industrial hall, used for exhibitions, with office and residential space. This strategy increases usable floor area without expanding the building footprint, allowing you to densify the site while preserving the existing structure.

This strategy can also be used to evaluate the impact of retrofitting. Older buildings can be extended with new materials or additional structures to make them more energy efficient or improve their climate resilience.

Use the dashboard to see the impact

Switch to the dashboard to make the impact of densification visible and measurable as existing spaces and future changes coexist within a scenario. We can compare existing conditions with transformation scenarios side by side and track changes such as floor area, housing units, or space‑use distribution.

This helps us communicate results transparently and build a shared understanding of how repurposing and building up affect the neighborhood.

Parcel parameters

In addition to existing building spaces, parcel parameters provide another way to represent existing conditions in Urban. When added to the existing scenario, they allow you to capture parcel‑level characteristics that help complete the picture of the current condition. We can use parcel parameters to store parcel‑specific values such as tax rate, land value, or other relevant attributes.

Add parcel parameters to your plan

We want to know the current land value of each parcel in our transformation area. Let’s add a parcel parameter metric to our metrics graph in the configuration of our plan and call it “Land Value”. In the next step, we can import the data from a feature layer. Our parcel parameter is now ready to be used in further metrics calculations.

Use parcel parameters in metric calculations

Using the land value and combining it with the building value and tax rate, we can calculate the tax revenue per parcel. This makes it possible to translate existing parcel‑level conditions into measurable indicators and compare how different densification scenarios affect fiscal outcomes across the study area.

Key take aways

Modeling existing conditions is a critical first step for successful densification workflows. By working with existing building spaces, you can capture what is already built and explore strategies such as repurposing or building up within a realistic context.

Parcel parameters complement this approach by representing existing conditions at the parcel level, allowing you to incorporate parcel‑specific constraints and values directly into your analysis. Together, these tools help establish a reliable baseline, support transparent impact evaluation, and enable informed decision‑making when exploring infill and densification scenarios in ArcGIS Urban.