What If Everything You Needed Was Within 15 Mins? by RMIT Architecture

Michael Cuccovia (Michael)

MINUTE CIT-IES

Nutsara Thaemmee (Nell)

Darren Soh Shi Yang (Darren)

Zihui Yu (Nancy)

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INDEX

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BACKGROUND & VECTORS OF CHANGE A series of points, diagrams, images or observations that explain the research arrived at this scenario. The vectors from present day that suggests this as a possible future.

URBAN MACHINE An abstract system that is built based on urban concept rules. Generative process which outcomes as diagrams to allow assessment the relative merits of outcomes.

EXPERIMENTS Volumetric experiment on urban forms that make use of datascapes generated by urban machine.

URBAN VISION Qualitative reflection on what and how the vision is produces. How it will look like? What are the ideological and frameworks that will support the system?

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â&#x20AC;&#x153;WHAT IF EVERYTHING YOU NEEDED WAS WITHIN 15 MINS?â&#x20AC;?

By 2050 essential services and amenities will be accessible within a 15 minute radius. We aim to achieve environmental sustainability through exclusive use of renewable energy sources, limiting pollution by reducing travel times and providing sufficient greenspace for all residents. This scenario will explore the effects through relationship between urban density, amenities and travel distances through ideas of sharing and exchange, to optimise the spatial organisation of the urban environment to accommodate the needs of the population in 2050.

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he site area is the Taihu region of China approximately 100km west of Shanghai. The site is approximately 100 square kilometres and is centred around Lake Taihu, some of the surrounding cities include Wuxi and Suzhou.

Site location in China

Weâ&#x20AC;&#x2122;re interested in the idea of providing equitable access to amenities and improved mobility to the future population of the Tahui region regardless of their location throughout the site. We began the research by first mapping and analysing the existing site area and noticed a disproportionate amount of amenities and access to public transport in the largest cities of Wuxi and Suzhou. We also noticed areas with higher population densities also lacked sufficient public open space. As the population of this region begins to expand and is expected to double by 2050, how can we support its growth while ensuring all residents have equitable access to amenities and public open space?

Cities around Taihu Region WUXI

We propose the idea of the 15-minute city, whereby anything you need is accessible within 15 minutes, this means immediate access within your local area but also including to surrounding cities through the implementation of a high-speed rail network.

SUZHOU

YIXING

WUJIANG CHANGXING

HUZHOU 6

NANXUN

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China is urbanising rapidly and the Taihu region is no exception and we expect the population in the region to double by 2050.

ES UT IN

How is this relevant?

IN U

TE S

The key focus of our proposal is to support the future growth of this region as one interconnected and overlapping city. Looking through a lens of increased connectivity and mobility with a potential upside of environmental sustainability and reduced carbon footprint of the regionâ&#x20AC;&#x2122;s residents by limiting travel times to amenities and other cities within the region.

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U IN

M 15 MINU T ES

Concept Diagram of One Interconnected Region

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WUXI

Initial Findings of Existing Conditions

YOUTUBE : GEORGE DING

Analysis of the existing region showed the population currently scattered throughout the Tahiu region, with a higher concentration of people in larger cities such as Suzhou and Wuxi. We noticed that these cities tend to have better access to amenities, transport networks and infrastructure compared with the smaller cities around the site.

SUZHOU YOUTUBE : SUDHEER K

This is what first initiated our thinking about equal distribution for all residents in the region, not just people living in major cities.

YIXING NEVILLE MARS 2019

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CIT-IES 15 MINUTE

Conventional 15 minute city

Good connectivity throughout the region

Poor connectivity to other areas

Redistribution of population

Redistribution of amenities

Considers amenity as an index for population distribution

Considers population as an index for amenity distribution

One interconnected and overlapping city

Multiple city clusters with boundaries

The alternative 15 minute city We were drawn to the idea of equitable access to amenities proposed by the traditional 15 minute concept but after feedback from our mid semester crit, which suggested our original concept might result in a number of cities that are homogeneous and that lack variety, we have decided to take an unconventional approach to the idea. The fundamental difference between the traditional 15 minute city and our idea is that we are focussing on a concept that involves re-distribution of population based on the number of existing amenities in an area, opposed to a traditional 15 minute city concept that would focus on distributing amenities based on the existing population. It is hoped that this method will generate a range of cities that are unique in their urban form but as a whole work together as one interconnected and overlapping city.

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hat are the vectors of change occurring in China that might aid in the success of this concept?

A higher concentration of people living in cities

The rapid urbanisation that is occurring in China will result in a much larger concentration of people living in cities, we expect the population in this area to double by 2050.

Improvements in transport technology

ES UT IN

As well as, Improvements in transport technology may lead to reduced dependence on the private motor vehicle and cheaper, more sustainable and readily available access to high-speed rail systems.

IN U

TE S

15 UT IN

M ES

15 MINU T

Rapid urbanisation in cities

Reduced dependence on the private motor vehicle

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CONCEPT RULES

RULES

URBAN MACHINE

OPERATIONS

DESIGN

ASSESS

DESIGN

ASSESS

OPTIMISE

3.Assess the access to amenity in surrounding areas.

4.Distribute the population according to the amenities available.

1.Break down the Taihu region into smaller areas.

2.Assess the level of amenity in each area.

5. Re-distribute density to make it more equitable.

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MACHINE RULES

MACHINE DIAGRAM

1. Break down the Taihu region into smaller areas. 2. Assess the level of amenity in each area.

Area splitting at 79km experiement

79km

Amenity index at 79km experiement

79km

Amenity index in 2020

The first step is splitting them into areas. The diagram generated here shows the initial amenities index of each area within themselves. The generated diagram is able to provide information of the difference in accessibility to amenities. We see a huge difference between Suzhou Wuxi area compared to the others.

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MACHINE RULES

MACHINE DIAGRAM

3. Assess the access to amenity in surrounding areas.

Relationships with immediate neighbour at 79km experiement

Re-calculated amenity index at 79km experiement

Amenity index when the travel radius is 79km

Those indexes then goes through a process of adding immediate neighbours. This is as a gesture of them being able to share amenities as the population in that area are able to reach them in 15 minutes. What we think is interesting as an experiment is that at furthest travel radius, it speculates to a future of reachability of the entire region as the amenities index are all having the same value. Hence, the diagram shows them at the same height. 28

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MACHINE RULES

MACHINE DIAGRAM

4. Distribute the population according to the amenities available.

Initial population of each area at 79km experiement

Redistributed population of each area at 79km experiement

Initial (Red) vs Redistributed (Green) population when travel radius is 79km

The machine then calculates the initial population of each area, doubling the total as a speculation that by 2050 the population would be doubled. The doubled population was then distributed based on the amenities index that had considered neighbouring relationships. The flat green diagram shows the population is distributed equally.

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MACHINE RULES

MACHINE DIAGRAM

5. Re-distribute density to make it more equitable.

Density of each area after population redistribution at 79km experiement

Pushed population density of each area at 79km experiement

Redistributed (Yellow) vs Pushed (Green) population density when travel radius is 79km

The result is that the density is relatively different as the availability of residential land use is different. What it shows in the yellow diagram is that, areas like Suzhou and Wuxi have a relatively low density as they were more residential compared to other areas.

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MACHINE RULES

MACHINE DIAGRAM

5. Re-distribute density to make it more equitable.

Land use change towards residential at 79km experiement

Land use change towards green at 79km experiement

Change towards Residential (Left) vs Green (Right) when travel radius is 79km

The machine finds the average density, and remapped the low density area by converting residential land use to either agriculture vertical farms or converting low rise residential into parklands. Due to that process, not only no land was converted to residential at all experiment, moreover the machine is able to give back to green. At the same time making sure residential land is used efficiently.

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EXPERIMENT STATS

EXPERIMENT FINDINGS

Initial (%) 79km

79km

39km

19km

9km

6km

19km 6km

Given to Green (km²)

Initial (%) Population

44%

26%

19%

11%

Given to Green (km²)

232.8

Increased Volume (%)

176%

95%

161%

11%

Initial (%) Population

Given to Green (km²)

50.5

42.7

4.2

10.2

11.3

Increased Volume (%)

380%

222%

-2%

946%

875%

Initial (%) Population

Given to Green (km²)

0.45

0.85

2.6

Increased Volume (%)

78%

49%

-56%

1073%

521%

We’ve picked the first, the third and last from the 5 sets of experiment statistics to visualise the volumetric side of them. And this is what each city might transform into.

This helps us to realise the bias of the machine that generates this inversely proportional relationship as the travel radius is varied. Because of that, we had decided to go with the middle experiment which actually generated more changes to the entire region. That is when the city is transformed based on a travelling radius of 19km in 15minutes. To visualise the chunk in more detail, we’ve picked Wuxi and Nanxun and tried to speculate on what it might look like simply because of the nature of the difference between a pretty dense and developed city to the other that has less population and density in 2020.

If we try to understand what the impacts of the cities relative to travel radius were, it is easier to compare the two extreme experiments. At the set up of cities at 79km, dense and developed cities like Wuxi and SuZhou give back to green the most, compared to relatively undeveloped cities like ChangXing. Interestingly this quantitative assessment of the relationship between the initial population and given to green is flipped. As the travel radius decreased to 6km. Now, Wuxi and SuZhou give back to green relatively less than undeveloped cities like ChangXing.

Subsequent pages are volumetric transformation comparison of each cities under the process of the machine.

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Experiment of cities in 2050 through Urban Machine Suzhou

Yixing

Nanxun

Changxing

Travel Radius: 6km

Travel Radius: 19km

Travel Radius: 79km

Wuxi

2020 Input State

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Experiment of cities in 2050 through Urban Machine Suzhou

Yixing

Nanxun

Changxing

Travel Radius: 6km

Travel Radius: 19km

Travel Radius: 79km

Wuxi

2050 Output State

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Wuxi

2020

2050 Travel Radius: 79km

Land use Commercial

Land use Industrial

Residential

Parkland

Agriculture

Commercial

Industrial

Residential

Parkland

Agriculture

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Suzhou

2020

2050 Travel Radius: 79km

Land use Commercial

Land use Industrial

Residential

Parkland

Agriculture

Commercial

Industrial

Residential

Parkland

Agriculture

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Yixing

2020

2050 Travel Radius: 79km

Land use Commercial

Land use Industrial

Residential

Parkland

Agriculture

Commercial

Industrial

Residential

Parkland

Agriculture

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Nanxun

2020

2050 Travel Radius: 79km

Land use Commercial

Land use Industrial

Residential

Parkland

Agriculture

Commercial

Industrial

Residential

Parkland

Agriculture

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Changxing

2020

2050 Travel Radius: 79km

Land use Commercial

Land use Industrial

Residential

Parkland

Agriculture

Commercial

Industrial

Residential

Parkland

Agriculture

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Wuxi

2020

2050 Travel Radius: 19km

Land use Commercial

Land use Industrial

Residential

Parkland

Agriculture

Commercial

Industrial

Residential

Parkland

Agriculture

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Suzhou

2020

2050 Travel Radius: 19km

Land use Commercial

Land use Industrial

Residential

Parkland

Agriculture

Commercial

Industrial

Residential

Parkland

Agriculture

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Yixing

2020

2050 Travel Radius: 19km

Land use Commercial

Land use Industrial

Residential

Parkland

Agriculture

Commercial

Industrial

Residential

Parkland

Agriculture

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Nanxun

2020

2050 Travel Radius: 19km

Land use Commercial

Land use Industrial

Residential

Parkland

Agriculture

Commercial

Industrial

Residential

Parkland

Agriculture

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Changxing

2020

2050 Travel Radius: 19km

Land use Commercial

Land use Industrial

Residential

Parkland

Agriculture

Commercial

Industrial

Residential

Parkland

Agriculture

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Wuxi

2020

2050 Travel Radius: 6km

Land use Commercial

Land use Industrial

Residential

Parkland

Agriculture

Commercial

Industrial

Residential

Parkland

Agriculture

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Suzhou

2020

2050 Travel Radius: 6km

Land use Commercial

Land use Industrial

Residential

Parkland

Agriculture

Commercial

Industrial

Residential

Parkland

Agriculture

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Yixing

2020

2050 Travel Radius: 6km

Land use Commercial

Land use Industrial

Residential

Parkland

Agriculture

Commercial

Industrial

Residential

Parkland

Agriculture

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Nanxun

2020

2050 Travel Radius: 6km

Land use Commercial

Land use Industrial

Residential

Parkland

Agriculture

Commercial

Industrial

Residential

Parkland

Agriculture

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Changxing

2020

2050 Travel Radius: 6km

Land use Commercial

Land use Industrial

Residential

Parkland

Agriculture

Commercial

Industrial

Residential

Parkland

Agriculture

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URBAN VISION

Wuxi is a high-density city with little green space and a large population of 3 million in 2020.

Nanxun is a countryside, with a relatively low population of half a million compared to 3 million from Wuxi. Nanxun now has a large area of greens. However, according to the urban machine, more population will be redistributed in 2050 to this area as the access to amenities and jobs from this area will be increased.

However, there will be a dramatic change in 2050 if the cities are planned out with our urban machine. 50.5kmÂ˛ of residential land use will be converted to green. With a portion of residential towers shifting to agriculture as vertical farms which can supply the food for the connected region, other remaining residential land use that should be converted to green becomes parkland that increases the urban livability of the existing dense city.

Similar to previous scenarios on Wuxi, residential land will be required to be used strategically as no new land will be provided by the machine for residential use. The green quality of this area will be able to be preserved even with the densification and population growth.

Due to the intense growth of population and conversion of residential land to green, the height and architecture of residential buildings will be required to maximise efficiency of residential land. In addition, the super overpass will replace the original ground transportation.

If the region is planned out in a way that a 19km radius will cover everything needed that would be able to be accessed in 15 minutes, the difference between a developed dense city and countryside that we see here in 2020 will be dramatically transformed. This high level of accessibility and transportation speed will make Wuxi to no longer be a city with extremely little green and parks, Nanxunâ&#x20AC;&#x2122;s flatness of inefficient use of land will be changed. Wuxi on the will have more parklands, as the result of population are dispersed to other areas of the region. Nanxun that used to be flat has greater efficiency in land use. This shows that the difference and gap between a 2020 city and countryside will be closed in the possible future.

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2020 URBAN STATE

2050 URBAN VISION

Wuxi

2020

2050 Travel Radius: 19km

Land use Commercial

Land use Industrial

Residential

Parkland

Agriculture

Commercial

Industrial

Residential

Parkland

Agriculture

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2020 URBAN STATE

2050 URBAN VISION

Nanxun

2020

2050 Travel Radius: 19km

Land use Commercial

Land use Industrial

Residential

Parkland

Agriculture

Commercial

Industrial

Residential

Parkland

Agriculture

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Nanxun Street View 2020

he speculated street in NanXun shows how the super overpass might work in the region in relation to residential, vertical farm and commercial, being connected into the transport system.

Nanxun Street View 2050

The sky bridge connects to other areas of the region for access to other amenities. The ground will be mainly for walking and cycling to create a safer environment for low speed movements.

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Wuxi Cityscape 2020

uxi will become greener and it also shows the speculated solution for the continuous growth of population without providing extra residential land.

Wuxi Cityscape 2050

With an overpass transport system that connects to the other areas of the region, it should meet all high speed transportation requirements. A sky road for autonomous vehicles on top and high speed rail on the other side of it.

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FINAL REVIEW

Neville: It’s a cool project. That’s for sure. I’m not convinced about the background with the visualizations. You guys push quite hard on this idea of urban engines. And,it’s in many ways quite convincing. I mean it raises the same questions as the previous presentation, right? The levers you are trying to pull. What is the reason to choose specific to those and only those levers in your case? I’m actually quite convinced of jobs and manatees. Access to jobs and amenities versus green which kind of generates a sort of density formulation. It is pretty convincing. I’m very, I’m in love with. I will go back to it. There’s one slide when you say experiment and you pick you show your model, where your model actually in a way delivers kind of levels itself out and therefore delivers nothing particularly interesting. And, you choose the middle ground, which is very surprising and I think it’s amazing. I think that’s exactly what planning needs right now. This sort of empirical approach. It sounds weird maybe but after that step. I would almost want to see what potential that can generate?

So, if you go to Wuxi for instance and you have an access point. A point of high accessibility, high amenities all concentrated all superimposed on top of each other. And you are able to generate so much green space. I’m wondering what are the other extreme architectural conditions? You need to introduce yourself to achieve that. Because at this scale, it looks amazing and very powerful indeed. But, I’m thinking, you know 300 meter tall towers etc. Also, here you see these layers and layers of infrastructure stacked on top of each other. It is also somewhat dystopian in a way. Anyway, that tension is fascinating. And, I wish you guys would have enough opportunity to even develop that final stage in more detail. John: Felix, do you want to take this or Ben?

Ben: I might quickly jump in before opening up to Felix. I think a lot of the issues that you’re talking about are super interesting. And it had a lot of commonality with the studio that Felix and I are running this semester. And,I’m sure this is true. You can make some comments similar to mine. I’m one of the issues that we’ve discussed. In the context of that video is the idea of the five minutes city or the 15 minutes city as a homogenizing or potentially a homogenizing, which you guys have kind of quite clearly articulated. It’s what you’ve responded to following the mid semester crit, which I think is really interesting. How you discussed the differentiation but the conventional approach in that you’ve said in this approach density is attracted to amenity rather than population. Can you describe what you mean by amenity? It’s a really important operative term in your proposal.

Ben: Okay, so it’s all of the nonresidential stuff. Michael:Correct Ben: And then so, your model is that new build volume is attracted to those elements. Is that correct? Darren: Yes, that’s right. (New response if we’re given the opportunity to re answer the question.)

The existing experiment we did was based on the relationship between population distribution and job opportunities. We here speculated that all amenities and land use types have a value on offering job opportunities. This is based on the reflection from given feedback on mid semester review that population moves based on job opportunities. That is the reason why we include everything other than residential as the attractors of the population. The attractor of the system can easily be replaced by any other specific building types or occupation that we would like to generate the outcome on. For an example we would like to see what the region would look like if the population is redistributed based on the accessibility of universities or commercial areas.

Michael: Yes, amenity is in pretty much anything, shopping centers, schools. Just Urban infrastructures actually.

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Ben: Okay, and you’ve also said that lack of population attracts new populations. So, the difference between Wuxi and Nanxun, which is currently a low population, has an increase in population in the future?

Darren: I think we are trying to keep the original or the existing state of specialty of this area. We think it will be able to do that because of the possible technology for transportation in the future. So, we speculate on how the cities or the rapid population will be redistributed based on the accessibility in that 15 minutes radius that we make those scenarios on.

Darren: Yes Ben: Okay, so I’m also equally interested in. So, I think where you’ve described the differentiation from a regular model around the super loop. You use the term that Felix and I use in our studio. I think that’s kind of an interesting idea because our students have chosen to do the opposite. They’ve tried to equalize the differences between different elements along the loop. And you’re saying that you using this is this particular structure to amplify the differences. Is that correct?

(New response if we’re given the opportunity to re answer the question.)

We think that it is important to keep the significant differences between the areas. These will give the population a reason to commute to other cities in the region. Not saying that they must travel across cities on their daily basis. We imagined this scenario at the most extreme condition that one is able to teleport to anywhere in no time, like split second. We think that no one would want to teleport to anywhere that looks nothing different to where they were. Similarly in our case, we think the same way.

Ben: I think it’s a really interesting proposition. Paul Minifie has talked about the work that he did a couple years ago. talked about how there’s different types of programs. What’s it’s a certain different type of amenities? So, amenities like being together. Like the example he gave is the motorcycle shops along Elizabeth street. So, it’s really really good for those motorcycle shops to be congregated together because you end up with a precinct. That’s kind of a defined motorcycle shop precinct. Where Seven-Elevens don’t like being together. So, they want to be spread out as much as possible. And, this is obviously talking about things that are very micro scale. But I think it’s still the analogy that works at the macro scale as well. So for example, you might not want a university and every one of the nodes around or every 15 minutes city, but you might want two or three universities in one. Because then being together is actually really beneficial. So, this’s one of the examples of that is Austin with MIT and Harvard being together is actually mutually beneficial for one another. And it’s not a problem if you have to go from one node to another node to go to university for example.

Where is in each of the nodes you would want a primary school, supermarket, all kinds of that or kind of incidental things. So, how do you start to distinguish between the really special things that are okay to be across between nodes and the things that you actually want to do within your current 15 minutes theme. This isn’t something that I think you need to answer now, but I think it starts to push forward some of the ideas that you’re talking about. With regard to the differentiation between your 15 minute city and the conventional 15 minute city. I do have one additional question. And maybe this question that you don’t need to answer immediately, but it’s a question around. Do you see this as a model for simulation or a policy model? So, the question is, how do you enact this? What policies would you need to put in place to make this type of 15 minutes city happen?

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Darren: I think the way we play this machine differently maybe from other groups. At first we try to play in a way that we can control the changes by every increment of five years . But then throughout the semester we eventually came up with this, which we speculate on the 2050. So, I would say this system is more like speculation on the end state. We try to speculate the end state and then we give each area a breakdown of what they need to achieve in 30 years from now. And then they can break down into that every five years. The area needs to maybe decrease the percentage of and this, changing the percentage of land use from low residential to others etc. So, rather than a stimulation program, it becomes a tool to speculate on the end state and then to allow it to play out by the breakdown stats.

Ben: I guess the question is more around what incentives people to move? So, the moment of resistance is like this is what will happen that there is not a lot of discussion. So it’s a I guess it’s really a question of economics or what the attractors? Why would people move from say Wuxi to one of the other nodes? And what’s the policies you put in place to encourage this example? And this may be an unfair question as it’s outside of questions to you, but I think it’s going to be an interesting question to think about. As to how do you get it to the state that you’re proposing? Perhaps John can pick it up. Darren: We sort of picked this out in one of the members earlier books that Neville did his research on. It was regarding how the government had this policy to try to keep people in villages. There is a certain credit system that would allow them to have benefits if they stay in the village. I think that is the kind of thinking we are discussing? Ben: Yes

Felix: Thank you guys. It’s an overwhelming presentation and overwhelming amount of work. It’s so exciting that I can just comment on something in detail. I think we need more time to reflect on so many graphs and so many findings that you showed. I think that the results are intriguing and the more I like. And I think also I agree with Neville is that when you find a certain policy that ugly? Is that the result of your research when it becomes interesting? So, I think you have to just continue on these testing like testing seats. Also, what kind of algorithms rules you can have and what resources you have. So, you have already done one test with five rules, but you could update the software and fine-tune it and change some things there and see the results again. I think this is the most exciting thing about this whole thing is that we don’t have all the answers beforehand, but it’s about trying to test what could work and what could result sometimes in surprises is that or paradox is how come certain kinds of development leads to more green or more concentration than other.

So, I think this is the main point. I think that again to just mention some references in the Netherlands. There is a model that is for planners and then they try to push forward for this model in this. In Holland, there was a discussion. If you should push towards cities like Amsterdam, Rotterdam. What should they become mega cities? Or should we instead have a kind of what they call deconcentration, which means that the biggest cities don’t grow so big but are not struggling making some clusters. So they did not scroll. So it’s trying to make a kind of model of a network City but is not just based on just once there is some quality of how organized this matter is. And this goes very much connected to your time connect policy of 15 minute cities. So the 15 minute cities for the community. It connected to amenities and to accessibility for everyone. So, it’s about fairness of how you can access all programs. And therefore it redirects or controls the certain kind of growth in this case, mostly focusing on giving all the amenities of schools and hospitals as close as possible to the public transport hubs.

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And saying that I miss that part I miss reading about the whole public transport system. I don’t see it in the presentation. And I don’t see how this has to be challenged or reform or intensified. And regarding the different transport systems that you have? Because we all know that not to do this system with cars most likely so we have to focus on mass transit systems. And so these may actually lead to certain typology for you about what kind of hubs you have where you have the biggest amount of amenities over there or not so essential amenities or almost no amenities. They have different types of hubs, different types of densities that could lead to some kind of development. But I think it’s quite impressive what you have done. I would just encourage you to continue on this format of research. And that is going to deliver incredible results as you go forward. So I’m looking forward to it if there is a final review.

John: Thanks Felix. some of these guys might end up in your studio some stage in the future as well. So hopefully it’s not the opportunity to sort of replace your reprise some of these conversations.

BLANK

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MID SEMESTER REVIEW

Ben: Thank you for the presentation. It was really clear. I think you did a good job of handing between the various presenters, which is great. The 15-minute city I think is an interesting proposition and it’s kind of discussed in the context of Victoria. There’s a planning policy around the 20-minute city, more or less the same thing. I’ve always been a little skeptical or concerned about the 20-minute city because if it’s a risk of homogenising the city and what I mean by that is ... and the proposition in Victoria is every part of the city that you need to be 20 minutes from everything you needed any time within the city. If that’s the case, why would you go anywhere? What’s the point of living in a big city? If you have everything within 20 minutes. Why don’t I live in a town somewhere. So how does this system counteract or not become a homogenizing influence on the city.

Darren: So we did think about this. We think that the way to move away from this issue is that even though each just looks similar right now, because of the existing infrastructure that is within each of the locations it might still have differences. Even though the population density is similar, the occupation of each cluster is different and that still makes people would have the need of going to the other clusters.

Ben: Yeah, I mean, I think that’s kind of an interesting response and it kind of leads into my next question. Which is how do you account for or leverage existing conditions in the city? So at the moment it’s a highly abstract system and I understand that’s part of the task, but then you are saying that the interaction of the abstract system and the existing infrastructure. For example, is the thing that leads to differentiation. How do you either leverage or demonstrate that in some way?

Darren: So we start by making use of data to show what the existing looks like or the location of each existing thing. At the moment we only picked some each of them to have an influence on the rules. So we think about moving forward. We will have more relationships or ratios between things.

I guess the question is what’s the next step which starts to take into account the existing urban infrastructure of the city in a systemic or how do you leverage it?

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Ben: I just have one comment or question really and I think when you presented what you described is vectors to change as I was quite interested, but one of the points that you made was that the transition to service-based work will lead to this decentralization. However, the transition to service-based work in developed economies, particularly in Australia, has led to extreme concentration within cities. Melbourne is a very good example of that. So one of the reasons why property prices are so much more expensive in the central city. Now is because of the transition to so the space work is extremely centralized. Why is the model that you’re proposing different to what we’ve experienced in developed cities over the last 20 years and you’re projecting this for the next 50 years, which is saying this is different?

Darren: In terms of the property prices, we think it is because of the contrast between what is seen as a city and what is as a rural area in terms of density. So what we try to do here is to have most of them have an equal population and because of that the density will become similar. Which we think will be able to control between the demand and the supply.

Ben: Actually, I would argue that difference in prices has to do with your work opportunities that exist in Central City. So I know there is quite a bit of data to support what’s driving property price in central Melbourne is the availability of high-income jobs and the proximity of high-income jobs. Which is just to say that I don’t think it’s necessarily density parts itself. So there’s a link or correlation between work, economics and your density, which I think is kind of interesting. This is an open question. I’m not actually expecting you to answer this yet.

John:

Maybe somebody else.

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Ian: Okay. Thanks for the presentation, great to see that the way you deal with really significant scale and also then jump in the scale by talking through layers of the project. Once that was studied off earlier than the second half of the semester. Just to pick up on what Ben was talking about the idea of assigning a number of whether it’s 15 or 20. I think it’s important to maybe use that as, maybe break down a bit further, when you start to detail a project. I’m trying to understand which bit might be realistic because very often that becomes … You can look at it from a number of ways. Is it a metric or measuring the quality of a city, is it just a diagram to help you sort of distribute activities and programs and or is it a criteria that gets built into what you start and measure. It might be a mix of those things. I think trying to understand that informs the process when he gets to designing. I guess the architecture or even the scale, the block and understanding what that means. It would be really good to know that it gives you a way of breaking down a very large city, also trying to figure out how it might allow different kinds of hierarchies within that system.

So if you use an example of Melbourne, it is sort of one of the ideas that’s been used in the last couple of years to think about how the city might develop is this sort of poly-centricity and and one of those things has been to also understand what kind of… Everyone of those models doesn’t necessarily try to replicate the Central City but it tries to take some of the load off the main centers. I think that might be a way in which you might be able to think about each one evolving over time, and maps into your diagram maybe speculation of population, maybe there’s also something coming in from the rules for setting. So think the other big would be those rules and to write I guess clear ways in which those rules manifest themselves as the final proposition. What does that change actually mean in terms of number, in terms of access to opportunity. For that matter like if x amount of people moving from one form of industry to the other. What does that actually mean? That might give you some criteria, to understand the difference between specific neighborhoods and precinct.

The other one is also to think about is there high speed rail that is involved in this situation? And think about what that actually means for this whole thing. I think you sort of talk about it in the start but then in the end it’s only about the cycle and walking, if I’m getting that correctly. So maybe there’s a way to think about that whether you’re measuring distance or measuring time and the two things become quite interrelated for relative in depending on how you start measuring it. I think there are a number of things for you to unpack. How the bigger agenda ties into a specific scale of the building would be really interesting. Do you mix relate to the floor plate while you look at things like a FAR and consider how it relates to pieces of infrastructure around it? Like are they all gonna be in nodal, are there other moments at which this differentiation and the form and think it’s something that comes up through the next couple of weeks.

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Neville: It’s a nice proposition, the idea of 50 minutes. I really enjoy that and my thoughts are very much along the lines of the previous two comments, but to be more specific, I think you really want to make a very distinct choice what your abstract system will do. Is it a tool of analysis for optimizing the existing city or assuming that there’s going to be so much new growth for the next 30 years that you can actually have enough meat to kind of reshape this entire region. Then it’s some sort of propositional tool which is in this case. I would say. More interesting. There was one point in the presentation where the grid seems to sort of perfectly click. It’s an orthogonal one. It’s really quite persuasive in the sense that to me then it seems like you’re trying to at least cover also all the people that are living in the countryside which is quite a sensible objective where you say, okay, I have this rather mixed spread of amenities that everybody has to be able to tap into.

According to this network, I can sort of invest in additional infrastructure and concentrate additional amenities exactly in those nodes where the people are within that little envelope can benefit and in that sense offer pretty much everything everywhere without kind of creating this spread. I think that will be the most sort of reasonable interpretation, much more kind of daring and maybe it’s utopian is that first slide you showed where there’s just this perfect grid of nodes. I think it’s even back one more. And you’re in that sense, you’re assuming I think it’s really quite insane and quite exciting and also very scary. You would somehow imagine that there is indeed a decentralized city, which I like because it’s a proposition that is already happening. We can assume there is a huge amount of decentralization occurring in the next 30 years as it has over the last 10 years 15 years in this region, and now with proposals such as townasation that’s Mackenzie term.

Where you would indeed invest in not even in the city’s third-tier cities, but actually in the smallest units in towns and create this kind of pattern and it would be if you have this analytical tool to be really interesting to know how much additional infrastructure would require our to let trips get really shorter. People are no longer required to move over long distances, which I strongly believe it’s not achievable. At the end of the day, you need to have some sort of hierarchy in amenities that are on for schools and universities. University can’t be in every one of these single little notes. So there is very some sort of hierarchy and how does the existing system then facilitate that people are able to move beyond that 15 minutes. That will be my next question that I find the last slide in that sense not so persuasive, the idea that there’s some sort of I think you call it multi neighbourhood core or something which would support extreme density. I think that’s not necessarily the solution that your analysis seems to drive at.

Micheal: Yeah, definitely and I think also just going back to that first slide. Where we were experimenting with all the nodes scattered out. That was the first test, the idea was to just put dots at equidistant from each other. The only thing we were considering was the lake and some topographical issues and at this point in time, that was our base and going further into the semester to add we want to add more variables to see how that kind of develops. So we’re playing with things like public open space, we are looking at doing a hierarchy of amenities to see which we consider most important things that we use daily, weekly, monthly and yearly. So as we go through the semester, we’re going to sort of play with those parameters and see what we think. I don’t know if we quite emphasized enough the high-speed rail element, but the core of our sort of design that develops is about connectivity more so than the decentralised city, although this first experiment kind of implies decentralization. I think we’re sort of headed towards more of a connected type design as we play with the parameters and different variables it gets more complex.

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Neville: Right, maybe you could just clarify, maybe you could use your tool to reintroduce sort of a clever hierarchy in the field of amenities that you’ve found to figure out where additional program would be needed to indeed support that kind of grid. Within 15 minutes you don’t need to offer that much, right? That’s kind of a daily trip, but maybe weekly is in one hour trip, maybe monthly is two hour etc. So maybe some sort of logic like that.

Bridget Yeah, I guess I’m a similar kind of response in terms of this idea of evenness and I guess I’m not sure if any of you had any time Melbourne before the semester started or in previous years, but we have a store called Bunnings Warehouse, which is a hardware store and you, honestly if you look at the distribution of that store around Melbourne it’s almost perfectly like your grid, 30km centres, because that’s kind of what they’re evaluating is the kind of correct or proper catchment zone of this store. I think that this kind of relationship where the node it is situated, so the red dot versus the boundary and potentially if you could think of it as a catchment, so what is being held within that boundary, you could potentially have a whole range of overlapping catchments. So I guess to follow on from Neville, there’s one thing that is travel time, that also, there’s kind of you need enough population to support a University, for example, there are different requirements for each of those that also have different extents and those extents might be kind of just formed by various other factors.

John: Okay, so we’ve got time for a couple more questions, Bridget did you want to make any comments or questions?

So how you can begin to think of the way that your parameters are qualified and by that, I mean when we think about a 15-minute city, for me that’s always been really funny as well because it’s like well because what is that for your grandmother with a zimmer frame, and what’s 15 minutes for someone with a pusher, and whats 15 minutes for someone who lives in an area with lots of hills. So how do these kinds of things... in a way you’ve already keyed them out, the topography and the water, how much they kind of stretch or allow you to have different ways of thinking about the boundary parameter.

John Thank you, all right, I love the Bunnings example like the bringing back to Bunnings I’m sure there’s an equivalent here that we’ve overlooked. But that’s a really good point because, I mean, we talked about mobile phone towers as a distribution system, I mean that’s kind of esoteric really, the mobile phone towers, when you, Bunnings is sort of one of those social infrastructures that are very close to the lived experience. Which is hopefully what we want.

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Reflection The result from these experiments conveys a concept that it is not that the growth of the city slows down for the countryside to catch up. Or a result of an intentional capping the growth of the city. However, we think it is the transportation technology, high level of accessibility, leads to a redistribution of population growth allows a city to step back and mimic the greenness quality of the countryside, and a countryside to learn and achieve the efficiency of land use from the city.

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