Planning Municipality Growth Using AI can save 1 year in planning processes

For the Bergen region to grow sustainably, it needs to upgrade the railroad connecting Bergen and Voss. Voss has been estimated to grow by as much as 300% over the next 20 years; meaning that the upgrade would reduce the current 1h 20m commute in half, making it possible to live in Voss while working in the more metropolitan region of Bergen. These changes inspired my Master in Architecture thesis:
Investigating how and where Voss could be densified in order to make room for the expected population growth.
Red areas show existing development and circles illustrate the potential growth for each town along the suggested railway.

One challenge posed by densification is that Voss is surrounded by mountains, limiting the space for residential development. Also, residents need to live close to the train station to take advantage of the abbreviated commute to Bergen offered by the fast train. Together, these conditions meant that the historic city centre had the most potential for densification. Shown below, three areas, in particular, stood out.

Then, the question becomes how to best densify without compromising the character of the town or the living qualities of existing residents?

I decided to focus on three comprehensive design goals: (1) preserve the view of the surrounding neighbours, (2) create as many apartments as possible with a lake view and (3) design outdoor areas that would be attractive to residents and visitors alike. I developed three site concepts catering to all of these demands and, in this post, I will describe how using Spacemaker’s software would have improved my decision-making in terms of concept development and time management.

The concept for Site A

The concept for Site B

The concept for Site C

In the summer of 2019, I started working for Spacemaker and found myself with a powerful platform at hand that allowed me to test my assumptions in a data-driven manner — in a fraction of the time, with more accuracy and comprehensiveness than I could have achieved using just my architectural instinct and education.

The insights I received from Spacemaker are threefold: (1) The view analysis proved that the new buildings would not block the view of the neighbours as much as I thought they would (2) but it also revealed that a smaller number of apartments would have a lake view. Also, the noise and wind analysis showed (3) that the outdoor areas would not meet the level of comfort that I expected.

The View to Area Analysis established that fewer apartments than expected would have a lake view.

The Wind Analysis shows that large areas (in purple) are at risk of heavy wind and wind corridors which renders them uncomfortable to be or stay in.

The construction sector is the least digitized industry in the world. Many workflows and ways of working have not changed for decades, including the way I worked: drawing on tracing paper and basing the concepts on estimates of how the wind, sun, views, and noise would affect the buildings.

The Noise Analysis proved that the noise levels coming from the road adjacent to the residential complex were too high for several apartments, making it hard to comply with regulations.

Spacemaker gave me a tool that supercharged my intuition with data and smart analytics — dissolving time-consuming, manual steps into short simulations within the platform.

For example, it took me a lot of time to analyze the density and heights of each of the proposals, time that would have been better spent creating more proposals that would bring me closer to optimal solutions.

The Geometry Analysis gives a live update on areas and statistics divided into the various functions.

With Spacemaker, the real estate industry will be able to deliver the first two design phases — the concept and feasibility phase, as well as the design and planning phase — completely digitally. Spacemaker is a platform that gathers all relevant information early on and gives access to all stakeholders in the planning process to collaborate, which results in a significant improvement in the quality and speed of the planning process.

My architectural education and intuition equipped me with a thorough understanding of what a “good” living environment means on a local level, how different stakeholders use spaces, and what the needs could be for each. But adding quantifiable truths to my analysis, rather than “guesstimates”, would have allowed me to:

  1. Create, explore, and test significantly more site proposals for the Voss city centre, all within hours rather than weeks
  2. Obtain more detailed and accurate analyses on view, noise, and wind qualities instantly
  3. Identify real challenges in my proposals and solve them right away
  4. Improve the living qualities while maximizing the sellable area

The Sun Analysis confirms well to very good sun conditions in this site proposal.

The Daylight Analysis ensures that the proposal meets the daylight requirement set by the municipality.

The Outdoor Area Analysis proves that the proposal is well within what is required. The analysis is a complex calculation to meet regulatory requirements, taking into account the distance between opposing facades, amount of sunlit hours and noise requirements on ground level within a specific time during any given day.

Spacemaker powerfully fuses architectural intuition with artificial intelligence. Introducing Spacemaker in the very early stages of the urban development process would have resulted in densification that is more tailored to the needs of the city and its inhabitants.

Arne Magnus is an Architect and urban planner with experience from strategic planning on large scale projects and masterplans. Arne works as an Architect and as a Customer Success Manager at Spacemaker to help the software and users unite and grow. Arne holds an M.Arch in Architecture and Urban Planning from Aarhus School of Architecture.

Source: https://blog.spacemaker.ai/how-i-put-my-assumptions-for-an-urban-concept-to-test-with-spacemakers-ai-platform-b97aa7493e0c

Solution: spacemaker.ai

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