Abstract machines urbanism book

Praxis: Emergent Urbanism Abstract Machines Leeds Metropolitan University February/May 2014

1 Emergence[y] urban rules for post traumatic urban landscapes

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Contents

Emergence[y] Rules for Post Traumatic Urban Landscapes

Paul Bedson Nick Hart-Woods

Emergent Urbanism River Valley Settlements

Chris Foster

Ben Lillywhite

Emergent Urbanism Hills Dominic Kennedy

Hillside Urban Landscapes Richard A F Arthur

Oasis Theory and Research

Sam Hayes

Jan Harmens

4 Emergence[y] urban rules for post traumatic urban landscapes

Emergence[y] Rules for Post Traumatic Urban Landscapes Nick Hart-Woods Paul Bedson

Contents Part 01 Introduction Part 02 Case Study Part 03 Approach Part 04 Relational Simulation Part 05 Quantitative Mapping Part 06 Connecting Part 07 Nodal Clustering Part 08 Praxis Part 09 Bibliography

Foreword

The following research is aimed at investigating the phenomena of architectural morphogenesis in small-scale urban developments situated in extreme environments.

The extreme environment of study for this project is slum settlements, and it will aim to abstract out principles, rules and parameters as a series of metric, interlinked relationships operable on and guiding manifestation of form.

This defined ‘performative model’ will be created as a digital simulation from which it will be possible to demonstrate various instances of digital morphogenesis subject to varying preference of defined parameters.

“When the avant-garde group Archigram introduced the term ‘instant city’ into architectural discourse nearly a half-century ago, they were inspired by the mobility of contemporary society and its dependence on high technology to enable urban migration and make it creative and exciting—a dynamic, uniquely contemporary way of living. Their model was the circus, which they admired for its élan as much as the excitement of its continuous performances. In their drawings and models they were projecting a future of adventurous hedonism, a liberation of the sort projected by Constant, though emphasizing human creativity less than leisurely consumption. Their visions fulfilled the idea that the city was not to be a monumental artefact of civilization, but a tumultuous, ever-changing process. “Each generation must build its own city,” Antonio Sant’Elia had proclaimed, and Archigram and Constant, in their own very different ways, fulfilled his demand at the same that they speeded-up the process. They never realized— or acknowledged—that the modern age could create utterly different kinds of ‘instant cities,’ the hastily constructed communities of urban dwellers displaced by catastrophes of both human and natural origin— war, economic disaster, hurricane, earthquake. After all, where was the role for architects in them? What could architects do to turn these instant cities into affirmations of the human spirit? Architecture is about planning. How can architects plan for the unplanned, for the unpredictable? Exactly….”

Lebius Woods

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Introduction

01 01

Slums

Historically the term ‘Slum’ was used to describe housing areas that were once desirable, but which deteriorated as the original occupants moved on to new and better parts of the city. The condition of these properties declined as they were progressively subdivided and occupied by lower income citizens.

Slums develop and are perpetuated by a number of different forces.

Among the main causes cited for slum settlements are rapid ruralto-urban migration, increasing urban poverty and inequality, insecure tenure and natural disasters.

0-10% 10-20% 20-30% 30-40% 40-50% 50-60% 60-70% 70-80% 80-90% 90-100% No data available

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Overcrowding

Poor access to infrastructure

Poor access to clean water

Insecure tenure

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Lack of durable, permanent housing

Slum settlements

Today, ‘Slum’ has come to include a large variety of informal settlements, and as such a UN expert group recommended that policy makers consider a more “operational definition” of a slum. According to these experts, a slum is an area that combines, to various extents, the following characteristics:

• • • • •

Inadequate access to safe water Inadequate access to sanitation and other infrastructure Poor structural quality of housing Overcrowding Insecure residential status

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Development Models

Globally the biggest cause of exacerbated slum conditions is not increasing rural-to-urban migration, not people squatting on disused land, not even poverty itself. The biggest factor is incorrect policy responses and ill informed- out dated administration all underpinned by a hostile and aggressive attitude to the urban and urbanizing poorer demographic.

Most urban growth takes place in existing cities, not new ones, this means that planning responses to slums must take into account existing infrastructure. The current methodologies for planning these cities is based on colour coded zones on a master-plan, a top down approach. This approach is problematic because most city growth (especially in relation to slum settlements) is informal.

By forcing development in these areas it is necessary to evict the existing population, demolish and rebuild. This fails to address the problem and simply moves it.

Alternatively, a bottom up approach allows the development to occur incrementally and naturally as people improve their living conditions over time, as and when they can afford. The downside being there is no overriding control over the system and undesirable conditions can arise.

To overcome this, the aim of this study is to begin to understand and simulate the complex relationships that govern slum development.

By simulating the rules that govern slum dynamics, the designer can manipulate the outcomes for the benefit and improvement of the area.

Slums will disappear not through demolition, but by transformation.

Over time the shack becomes a house, the slum becomes a suburb.

This is how citizenship and cities are built.

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Bottom up vs Top down

Statistics

Demolition

The study of informal settlement processes, with their direct generation based on locality, network relationships and open ended growth, appears to be promising terrain for exploration with computational tools. The development of bottom-up algorithms generating emergent behaviours from local interactions has the possibility to allow planners and architects to understand, foresee and drive urban growth.

In this study computational tools will be employed as relational tools, attempting to move away from a paradigm of pure shape generation and embrace the complexity of network relationships and social structures.

Planner

Masterplan

Planning Rules

Imposed Order

Available Land

No infrastructure

The hopeful outcome of the study will be to illustrate some possible strategies of intervention in informal settlements, emphasising the need of avoiding large scale evictions and demolitions and instead trying to interact with the existing network processes to implement nodal changes that can influence the entire urban network.

Top down planning

Citizens

Self Build

The computational tools play a significant role as simulation and modelling tools, allowing the exploration of the complex interaction between social, economical and environmental parameters and to test and predict possible outcomes before implementation.

The final outcome, far from having resolved the complex and often contradictory dynamics in informal settlements, will nevertheless try to propose a study and intervention method, and outline possible lines for further exploration into the topic.

Rescources

Undesired attributes

Bottom up planning

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Case study

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Case study: Petionville golf course, Haiti

Carribean

Petionville

Haiti

Port-au-Prince

Golf course

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Development

t=0 The 2010 Haiti earthquake was a catastrophic magnitude 7.0Mw earthquake, with an epicentre just west of the capital Port-au-Prince.

The earthquake occurred on January 12th 2010.

The earthquake caused major damage in port-au-prince, Jacmel and other settlements in the region. Many notable landmark buildings were significantly damaged or destroyed.

t=1

t=2

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Figure ground analysis

26.08.2009

18.08.2010

13.01.2010

16.09.2012

15.01.2010

13.01.2013

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Approach

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03

Urban Strategies

Fundamentally, the city exists as a network of systems. In the past, this perception of the city was not useful when attempting to create an urban intervention due to the extreme complexity, offers designers the potential to tap into these systems and to alter them. â€œâ€ŚIt is not individualistic but relational; instead of treating them as independent, a network approach recognises that people and places influence one another through their relationships.â€?

Reductionism Reductionism Historically the approach to urban design employed reductionist methodologies. This is exemplified by the modernist movement, and ultimately failed due to the assumption that the designers will could override the underlying forces at play.

Complexity The complexity approach attempts to apply complex systems science to urban design problems such as chaos theory. While this has potential, it required vast computing power and an extremely accurate and detailed model of existing conditions that are often infeasible to obtain.

Relational Complexity

The relational approach aims to analyse the relationships between the various elements at play. By setting design objectives the results of various relational elements can be tested against desired outcomes and the system can be altered accordingly.

The complex element of this method can be dealt with using computation while the objectives are set by the designer. This study will aim to explore the relational qualities of slum settlements.

Relational

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Urban Growth Simulation

In order to simulate testing and evaluating these theories we implemented a simulation following Michael Batty’s formula for urban growth :

Pi(t) = f{εi(t) ,hi(t) ,ci(t), ai(t), νi(t)}

P- population l- location t- time

εi(t)-Randomness The variable used to blur explicit decision, the consideration of human decision making, this the case of this simulation, the random variable by which each dwelling is orientated on the plot.

hi(t) - Historical Accident The way in which mechanisms of change are enabled, be it the choice of a business or settlement based on human factors such as family, or in this case the position of the main track through the golf course determined by the previous usage.

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ci(t) - Physical Determinism Geometric or geographic containers that affect an area or development, can have a varied impact on the development dependent on the level of the technology available. In this simulation the geometric container in action is existing site boundary of the golf course.

ai(t) - Natural Advantage Access and proximity to resources, growth will vary dependant on the economic and environmental gain of accessibility to a variety of resources. In simulation 1 the resource considered is the position of the main water point on the site.

νi(t) - Comparative Advantage Weighted measures and decisions based on benefit potential and distance, considering both benefit to cost ratio and non spatial impacts such as social and economic weighting. In this simulation this element is represented by the computational test of proximity to resources, the water point, or infrastructure. Allowing for settlement position to achieve the minimal distance to one of these factors.

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Sphere Project minimum standards for emergency settlements

Public Active recreation creates spatial voids with well maintained boundaries.

Maximise existing environment Shelter solutions should be planned to retain existing trees and other vegetation to maintain the soil stabilisation such growth provides and to maximise the opportunities for shade and protection from climate.

Roads, pathways and drainage networks should be planned to make use of natural contours in order to minimise erosion and flooding.

Amenities Where possible, households can access land, markets or services for the continuation of development of livelihood support activities.

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Personal Privacy The plot layout in temporary planned camps should maintain the privacy and dignity of separate households by offsetting door openings and ensuring that each household shelter opens onto common space.

Family Privacy In mass shelters, the grouping of related families, well-planned access routes through the building or structure, and materials to screen personal and house-hold space can aid the provision of adequate personal privacy and safety.

vav Where possible, [...] routes should avoid creating isolated or screened areas that could pose a threat to the personal safety of users.

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Relational Simulation

04

Urban Network

In order to begin to attempt to simulate the complex relationship of forces at play it was necessary to attempt to recognise and establish patterns of how the settlement developed.

In the days after the earthquake people began to congregate on the golf course from the surrounding city to escape falling debris caused by after shocks.

At this early stage many people had lost all belongings so their primary concerns were based on basic survival needs. The needs we derived based on the Sphere Project minimal standards are as food, water and shelter.

The road is a settlement attractor due to the potential access to surviving infrastructure, the ability for the population to move across the site and the access to aid supplies.

Water sources on the site are an obvious attractor as people would attempt to set up dwellings as close to water sources.

The limited supplies available would encourage people to make use of the existing environment for shelter as much as possible. As such existing trees on the site act as attractors.

Obviously all of these initial nodal connections do not act independently and it is the interplay between them, as well as the weighting in terms of importance that effect the overall field of development.

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Proximity Simulations

Closest position to line

Once threshold reached develop around water source

Once threshold reached choose position closest to either attractor

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3D visual of attractor rules

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Quantitative Mapping

Terrain

Resources

Tree cover

Water

Distance to centres

Distance to centres

Choose closest

Choose closest

Topography

Road

Contours

Subdivide

Minimum exposure

Region

05

Region

Maximum slope

Region

Value map

+

-

Community Centres

28 Emergence[y] urban rules for post traumatic urban landscapes Add Dwellings

Potential sites

Region

Access to city

Land Value Generator

Road

Height To begin to simulate the urban growth of the Petionville tent city five rules, defined from the starting conditions of the site were established.

The main driving factors for settlement of the golf course are established by the relationship between terrain elements.

This created diagrams of the most valuable land in relation to the attractor nodes.

Water sources

Tree cover

Terrain

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+ 30 Emergence[y] urban rules for post traumatic urban landscapes

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Development over time

Reality

Simulation

t=1

t=1

t=2

t=2

t=3

t=3

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+ 32 Emergence[y] urban rules for post traumatic urban landscapes

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Value Weighting

The simulation of the urban growth on the site is driven by a land value map. This map takes into account a number of set attractors across the site . Each of these attractor nodes is given a weighting based on their importance.

Road

The resulting value map is then generated based on the result of the average of these weightings. It is assumed that the most valuable land will be occupied first.# As this land increases in density its value will fall making other areas across the site more desirable.

Water Sources

The diagrams below show how the shifting value of the weightings over time alter the value of the available land and thus dictate the probable locations for the growth of the slum.

Trees

City connection

Contours

Heights

Weighting variations

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Road

Water Sources

Trees

City Connection

Contours

+ Heights

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Analysis

Road

Water sources

Road weighting decreases over time based on the initial need for a connection for resources and food aid. As the population grows the density of the land around the road increases. Shops and markets are also established which removes the importance of aid and the overall need for a road connection. As the population increases the settlement is unable to sustain itself with the shops and so aid is once again required.

Water is given high importance as the slum is established for obvious survival reasons. As density increases this land becomes less desirable

Trees across the site are valuable for the cover they offer, reducing the amount of building materials necessary to be salvaged for house construction. Given that there are a limited number of trees across the site the value of these increase exponentially.

Trees

The connection point represents the access to the site from the destroyed city. The value for this is given exponential importance as this is where building materials can be salvaged. Given the weight and size of these materials the less distance these have to be carried the better, meaning clustering occurs around this area.

Value is given to the site contours to represent the comparative ease of traversing along a hillside as opposed to climbing across it.

City connection

The height values across the site are calculated based on the need to avoid the weather exposed hill crest and instead favour the sheltered hillside.

Contours

Heights

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Connecting

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Frei Otto

Frei Otto proposed that settlements are a series of interconnected networks. These networks exist on multiple scales, from territory path networks (the connections between settlements), to settlement path networks (the connections within villages, towns and cities).

These networks can be of the following types with many variations: The direct path system Masses and energies are transported in this system without making detours. In its ideal form, it only contains straight paths and path crossings. Path forks and concentrations do not occur. The direct path network is very simple to construct, as a plan on paper and also in any terrain that can easily be surveyed using simple plotting instruments, such as the Egyptians and Romans used.

The minimal path system In a direct path system, every point is connected with every other point by the shortest route. This still applies if impassable obstacles deform some individual stretches.

A minimal path system constructed between the same points has a significantly shorter total length. Minimal paths are created when paths have a low level of use and/or too expensive to construct, for example when three sites are situated in impassible terrain.

The generative path system In many cases the occupation of a surface takes place sequentially.

In addition to this, it is often random. Generative systems ‘search out’ the next nearest useful connection point. In generative path systems, users, when close to paths connecting at a right angle of the second generation usually take a short cut as soon as possible.

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Emergent Circulation Routes

Once these rules were established we were able to visualise the force relationship between the attractor nodes within the settlement and their effect on potential population movements.

These diagrams proved to be especially useful at displaying ‘conflicted’ zones where the distance between one node and the next is equidistant.

Essentially these diagrams are showing the shortest paths between the average of the nodes, marking the path of least resistance through the settlement as it is assumed that housing density would be less in these areas as people attempt to gather around useful resources.

These paths of least resistance would become new pathways and road networks allowing people to move around the camp. In turn these pathways would become attractors in themselves.

Water

This emergent system is displayed in the formation of rivers and streams, where water flowing under a force (gravity) attempts to find the path of least resistance downhill.

Road

Trees

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Fractal pattern created by water

Distance to centres

Topography

Distance to centres Distance to centres Choose closest Choose closest

Choose closest

Region

Choose closest Minimum exposure

Region Region

Road Access to city Subdivide

Subdivide Contours

Contours Distance to centres

Maximum slope Minimum exposure

Path Network Maximum slope

Region Region Region Region Region Another method of generating circulation routes is to create a definition that begins from a predetermined start point (in this case the road) Valueand mapsearches for valuable features (water sources.)

Value map The next step for development in this simulation is to combine it with an optimisation routine such as the one simulated below. Finally it would be desirable to have the circulation ‘growth’ self reference the development of housing and other environmental factors.

Community Centres Community Centres

Potential sites

Add Dwellings

Potential sites

Add Dwellings

t=0

Access to rescources

> Critical < Threshold Critical Threshold Join Node New Node Add Dwellings Add Dwellings

< Critical Threshold New Node Add Dwellings

> Critical Threshold

Need for community Access to rescources

Attracting force

Join Node Add Dwellings

Need for privacy Need for community Power Law

Ne

Distancing force Attracting force Resultant density

Di

Orientatio Resultant density

t=1

Attractor node

Start node Attractor node

Start n

Distance to next node Distance to next node If ≈ Find nest nearest

Random possible paths

If > or < If ≈

If > or <

Unsuitable Find nest nearest

Unsuitable

Make connection

Target node Random possible paths

Test for nearest point Test for nearest point Average direction of attractor Average direction of attractor Make connection

Make connection

Make connection

t=2

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Nodal Clustering

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Social Dynamic

t=1

Centralized

Decentralised

Distributed

t=2

Following on from the circulation route investigations, we began to investigate how the various nodes across the site could be clustered into neighbourhoods.

By studying the relationship of the connection to the nodes we are effectively establishing neighbourhood relationships.

This will aid in the investigation of maximum densities that can be achieved.

It is also hoped that this information it is hoped that social/cultural aspects of the slum can be added to the simulation.

t=3

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42 Emergence[y] urban rules for post traumatic urban landscapes

Neighbourhood grouping

In this simulation we attempted to simulate on a basic level the social groups that would form throughout the slum.

The initial starting nodes are set to represent water points (i.e. community centres where people from nearby houses would meet.)

From here we added further dwellings to these groups based on their proximity to neighbours. It is assumed that people living in close proximity would have regular contact as well as people who use the same water source.

t=1

At a certain point in the growth of a neighbourhood, the distance of the outlying houses reaches a critical distance from the central node (and contact with the central occupants) Where the outer region is isolated to the point where it becomes a sub neighbourhood.

t=2

t=3

Community centres with neighbourhoods

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44 Emergence[y] urban rules for post traumatic urban landscapes

Neighbourhood Growth

t=1

t=4

t=2

t=5

Small (Stable)

Large (Ready to divide)

t=3

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K-Means Clustering

Resources

t=1

Tree cover

Water

Distance to centres

Distance to centres

Choose closest

Choose closest

Topograp

Contou

Minimum exposure

Region

Region

Region

Value map t=2

Neighbourhood simulation plotted over entire site

Community Centres

Potential site

Add Dwellings

t=3

< Critical Threshold

> Critical Threshold

New Node

Join Node

Add Dwellings

Add Dwellings

Access to rescources

Attracting for

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Potential sites

Access to rescources

Need for community

Need for privacy Power Law

Attracting force

Distancing force

Resultant density

Orientation

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Occupation With Distancing And Attracting Forces

Frei Otto distancing occupation

Distancing occupation Node

Frei Otto undertook a number of studies to simulate the occupying and distancing forces at play in urban environments. We undertook a computational simulation to recreate this experiment and to simulate how the slum dwellings would group at a neighbourhood level.

To this we introduced forced separators such as roads and then applied an algorithmic solver to calculate the orientation of the buildings based on the requirement for privacy.

Attracting occupation Node

Algorithmic orientation

Frei Otto attracting occupation

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Praxis

08 Terrain

Resources

Urban conditions Existing density Tree cover

Water

Distance to centres

Distance to centres

Choose closest

Choose closest

Topography

Road

Contours

Subdivide

Minimum exposure

Region

Region

Access to city

Maximum slope

Region

Region

Value map Community Centres

Start node

Add Dwellings

Distance to next node

< Critical Threshold

> Critical Threshold

New Node

Join Node

Add Dwellings

Add Dwellings

If â&#x2030;&#x2C6; Find nest nearest Random possible paths Test for nearest point

Potential sites

Access to rescources

Average direction of attractor

Need for community

Make connection

Need for privacy Power Law

Attracting force

Distancing force

Resultant density Depletion

Orientation

Density levels

Existing Proposed

50 Emergence[y] urban rules for post traumatic urban landscapes

If > or < Unsuitable

Combined Simulation

t=1

t=2

t=3

t=4

Initial experiments attempting to integrate feedback between levels of simulation for example as above showing relationship between neighbourhood clustering and road development The logic diagram on the left shows a model for future development of the simulation. By adding iterative feedback the various forces at play across the urban network would be able to self reference and produce a more accurate recreation of the true settlement conditions.

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Conclusions

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Simulation Conclusion

01

01. The simulation seems to accurately predict in terms of land value the way that the settlement will develop in terms of responding to the site conditions 02. Land value anomaly; the area of high value land shown here remains unoccupied. There are a number of possible explanations for this, firstly the trees that are given an attractive value are plotted from a plan view. This makes it impossible to establish their height, and so areas of low bushes are plotted as tall trees.

Obviously these would be difficult to build around due to their density and lack of strength. Similarly the area could have unfavourable ground conditions, to solve these issues a more detailed site survey would need to be undertaken.

02 03

04

03. Here it is possible to notice a direct correlation between the offshoot of the settlement and the land value map. From the satellite images it was possible to derive that these areas built up once the most valuable land was occupied. Given that they occur on medium value land this is an encouraging result, however the simulation does not currently have an iterative factor, and is unable to set limits on density for self referenced growth.

04.Land Value anomaly; this area shows that it is of low value which is significant due to the proximity of the road (an attractor) and the fact that people are settling in this area in the satellite images of the site. Upon further scrutiny it was discovered that the US military established this area in order to supply aid to the settlement. The camp is situated on the highest point on the site, away from water sources and tree cover. This is significant, as it highlights that the military area is governed by different settlement rules. In turn it is likely that this would become an attractor in and of itself, so this area will require further analysis.

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Conclusions

The phrase ‘city planning’ conjures images of quite traditional architectural working methods. Things like sketch perspectives and charts and graphs about how we use urban space.

The problem with this way of working, is that as soon as you print out one of these graphs, sketch or photograph a feature of this city you’ve captured a snapshot of a dynamic system.

The built form of a city is perceived as a result of its history, a snapshot of the human activity it represents and facilitates.

The built environment is also only the tip of the iceberg in terms of what defines and drives a city’s development. Fundamentally then, the city exists as a network of systems as argued by Zachary Neal in ‘the connected city: how networks are shaping the modern metropolises when he says: It is not individualistic but relational; instead of treating them as independent, a network approach recognises that people and places influence one another through their relationships.”

In the past this way of looking at the city was not useful in the design process because of the extremely complex relationship of the forces at play.

Parametric tools, and the computers innate ability to handle complexity, are offering designers the potential to tap into these systems and to manipulate them. Currently the main problem with this approach is that architects and planners are still approaching the use of these tools with methodology that pre-dates them. This is echoed by Dr Micheal McAdams in a paper called ‘Complexity theory and urban planning.’

“Within the last few decades, urban planners, urban geographers and others have noted the inadequacy of using existing scientific methods and organizational structures based on concepts tied to logical-positivism such as rationalism, reductionism and comprehensive long-range planning to address the problems and challenges of the urban environment.”

The way that modernist schemes approach the problem is to handle complexity with reductionism. For example in Le Corbusier’s radiant city plan; the city is treated as a machine with the function of addressing four identified problems: inhabitation, work, recreation and circulation.

The problem here is that while it might sound valid on a theoretical level it is completely inadequate in practice. The assumption that the will of the designer can override the extensive underlying forces at play in the city is clearly a flawed methodology.

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So how else can we approach the problem? One approach it to utilise complex-systems science, things like complexity theory and chaos theory. There are problems with this method as well though, because besides the difficulty in formally modelling complexity if you take the simplest urban relationship, in isolation it can be easy to predict its outcomes. Add it back into the urban network and it becomes extremely complex through its interactions. As more and more of these relationships are combined they become intertwined like tangled string, as we found with the simulation as the scale was reduced.

While you can analyse the relationship between these strings as either tangled or untangled it is extremely difficult to predict the effects of pulling one end of the string on the system as a whole.

Once these systems are intertwined to the extent of a modern city they can only be addressed with chaotic system theories. At which point it could be argued that planning becomes infeasible and the system should just be allowed to develop naturally.

This approach though, can lead to undesirable manifestations of the settlement, whether this be in a physical sense (the form) or on a social, economic or environmental level. So if reductionism is too simple, and complexity is beyond our ability to comprehend, how can we address the problems of designing in an urban context effectively?

The way to manage the outcome of this method is to design the desirable city. We can set objectives to achieve with our designs.

Objectives come from the desire to realise our imaginations.

Imagination has the power to conceive a city not yet in existence, before all simulations and computer programs. It is a feat best performed by the human brain, not by computers. Parametric tools seek to augment our ability to simulate complex urban relationships, human creativity and the designer’s intuition create the goals of this process. While this sounds obvious, the way the majority of architects are practicing is not endeavouring to achieve this. It is essential that favourable social conditions are a primary objective and not the hopeful outcome of a deeply related set of purely geometric principles. By taking advantage of parametric tools architects can integrate digital computation with analytical design processes at a much more fundamental level than has previously been possible to achieve. What are objectives?

Objectives are basically rules and rules are what makes computers work. So, it seems obvious that digital techniques could be useful in designing our cities.

Conclusions

The study aimed to simulate the way that emergent slum settlements grow and develop. At every step it was necessary to interrogate, in detail how we were achieving these outcomes.

Primarily this was due to the fact that there are countless ways to generate the perceived patterns. It was however, vital to attempt to simulate the relationships that existed on the site, not merely recreate patterns that are visible from aerial views. Primarily, this was because it would have created incorrect results which would have compounded their inaccuracies through interactions with other aspects of the system.

For future study it would therefore, be vital to test the simulation on other slum settlements, and observe whether the results are accurate. Similarly, when using this kind of methodology in practice it would be important to include an anomaly checking framework.

Within our simulation there are areas that do not behave as predicted, it is necessary that these areas are scrutinised in order to either address inaccuracies in the simulation, or to extract the rules behind these anomalies for feedback into the system.

Unfortunately, the simulation is limited by its inability to feedback between scales. Primarily this was due to the difficulty in achieving this computationally. There is also extensive research necessary to address and comprehend how these different scales interact.

In summary, the simulation provides a good foundation for the simulation and study of slum settlements. It is by no means a comprehensive, entirely accurate model, it is a tool for facilitating a more in depth study of the complicated set of networked relationships that drive a settlement. While there are levels of complexity to this simulation, there are also gross simplifications that have had to be made in order to reduce processing time. Given more computational power, it would be possible to increase the level of complexity and create a more organic, real time simulation of growth. The authors strongly believe, that approaching urban design with this methodology, is drastically more comprehensive than the current approach. Primarily, because it allows the computer to handle the multiple relational aspect, and does not rely on the designer to remember, or to calculate the effect of one chance on the entire system. Which would take a huge amount of time, and is therefore, largely overlooked in current practice.

Using these tools it also facilitates the designer to simulate interventions and asses them against the desired objective. In the past the â&#x20AC;&#x2DC;simulationâ&#x20AC;&#x2122; occurred in the physical world, the intervention would be built and if it failed it had real world consequences. By rigorously testing such schemes computationally, more effective, site specific and sustainable solutions can be achieved.

It seems logical that, given settlements are essentially driven by human movement which is proven by observing the similarities between the patterns of individuals coming together to form groups and those of settlements. That there is an interaction between scales, i.e. the individual citizen has an effect on the system as a whole.

For example if you place a large group of people in a landscape and left them there, with no way of constructing buildings, it is likely that the places they occupied and the pathways they used would be remarkably similar to the locations of the various buildings they would construct.

Similarly, the simulation does not currently self-reference its own growth, In reality, as areas became overcrowded, or new amenities were added to the site this would alter the value map. Adding in this iterative self referencing, as opposed to a predefined change over time, would be necessary if the study was taken further.

The next point of interest for further study would be to apply this simulation as a tool for design. By adding in additional services and nodes to settlement, it would be possible to predict areas where they would be most effective. It would also be possible to observe the possible detrimental effects these services could have.

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ban landscapes

Bibliography

Frei Otto, Occupying and Connecting: Thoughts on Territories and Spheres of Influence with Particular Reference to Human Settlement. Edition Axel Menges (1 Oct 2008) ISBN 978-­3-­932565-­11-­3 Edna Shaur ‘Non-­planned Settlements; Characteristic features, Path system, Surface subdivision IL39 (1991) Michael Weinstock, The Architecture of Emergence: The Evolution of Form in Nature and Civilisation, John Wiley & Sons 2010, IBSN 978-­0470066331 Michael Batty, Cities & Complexity: Understanding Cities with Cellular Automata, Agent Based Models and Fractals The MIT Press (August 24, 2007) Daniel Shiftman,The Nature of Code: Simulating Natural Systems with Processing (http:// natureofcode.com) Alex Lehnerer, Grand Urban Rules, nai101 (Sept 2009) ISBN 978-90-6450-666-6 Jak Drinnan. (2012). Urban growth networks. Available: http://www.jd-d.co.uk/2012/06/urban-growth-networks.html. Last accessed 17th April 2014.

Davis, Mike, ’Planet of Slums’ London ; New York : Verso, 2006. 01/01/2006 eTorrens, Paul M.; Kevrekidis, Ioannis; Ghanem, Roger; Yu Zou. Entropy. Jul20123, Vol. 15 Issue 7, p2606-2634. 29p. 2 Color Photographs, 4 Diagrams, 3 Graphs. DOI: 10.3390/ e15072606 Zachary P. Neal, the connected city: how networks are shaping the modern metropolis McAdams, Dr M. A, 2008. Complexity Theory and Urban Planning. PHD. Istanbul, Turkey: Fatih University Urbanism for Expanding Cities: Designing the Conjugal Interface of Contrasting Systems”, with Jason King, in Landscape Architecture (China), Issue #2, pp.62-66.

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Emergent Urbanism River Valley Settlements Chris Foster Ben Lillywhite

Contents 1. Defining Settlements Researching the basic understanding of what a settler and settlement are, without being defined by itâ&#x20AC;&#x2122;s context, to develop a knowledge of the key principles to define a settlement 2. Rivers Refining our research to its context and learning about the key features and factors of a river valley 3. Settlement Expansion Using our knowledge learnt so far to look at how the early settlements would have arrived at a river valley and then how the settlement would have expanded 4. Case Studies Using real life examples, we aim to test our theories to see if they run true and analyse the case studies for further rules and parameters 5. Digital Simulation Testing the rules we have found in a digitally created environment attempting to predict the initial starting point of a settlement within a river valley and analysing how they would expand 6. Conclusion Evaluating our work and script

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Defining Settlements

01

To help us gain a greater understanding of how to fulfil the brief, we have gone back to the routes and learnt the basics of settlers and settlements

A settler is defined as:

â&#x20AC;&#x2DC;A person who permenantly resides in one locationâ&#x20AC;&#x2122;

Humans settle in various locations, looking for areas which offer qualities that support the growth of a community and can assist in survival

Settlements expand to accomodate increasing populations due to developing their knowledge, but the emerging urbanism is affected by its environment.

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Settlement Criteria When deciding upon a location in which to settle, a set of criteria are established.

The primary criteria for locating a settlement are related to its proximity to valuable resources such as:

“Where can we grow crops?”

“Does the topography of the land ensure safety?”

“Are materials for building nearby?”

“Are there methods of easy travel?”

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Benefits of Settling in the River Valley As every human needs water to survive the majority of settlements are close to a source of fresh water.

Rivers are the most common source of fresh water, and their valleys often meet all the criteria for settlement location.

Fertile land for crop cultivation

Higher ground is safer for building

Forests offer timber for shelter construction

The river itself is used for travel

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Rivers

River Features The locations of certain river features can be approximated based on the topography of any landscape. Rivers are often broken into three different courses; Upper, Middle and Lower.

Source - Upper Course

Meanders - Middle Course

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The source of a river originates from areas of higher ground, where groundwater emerges from the substrate and flows downhill. The valley is usually v-shaped here and waterfalls and gorges are often found close to the source of a river.

Meanders are found in the middle course of a river where the surrounding land is open and gentley sloping. Faster flowing water erodes the the outside of a river bend whilst sediment is deposited on the inside, forming curved meanders.

River Features It is possible to approximate hypothetical locations of certain river features, as the locations of features below and subsequent pages are defined by the shape, gradient and geological make-up of the valley itself.

Confluence - Middle Course

Delta - Lower Course

Also known as a conflux, a confluence is where two or more bodies of water meet. Rivers meet in areas where two valleys run downhill and open out in the same location, these areas often flood creating vast expanses of fertile land.

A delta is formed where a river valley opens out to meet the sea, or other large body of water such as a lake. The river deposits its sediment where the gradient of the surrounding land becomes almost flat and the river loses its momentum.

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Features of the River valley that effect settlement emergence It is important to identify key features found in river valleys, as humans will look for these when deciding on a location to settle. We believe these will be the initial major factors.

Shallow points

River meander

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Often found in the upper course of a river, where the surrounding land is steeper and the water moves slower. Shallow, and or narrows points of a river are often sought out by nearby settlers as this makes crossing by foot easier; Thus allowing the possibilty of exploring the other side of the river valley and its inherint amenities.

Meanders primarily occur in the middle course of a river, where the surrounding landscape is less steep. Settlers will travel to the outside of a river meander to find the deeper, faster flowing water. Fish swimming in the river are pushed, by the current, to the outside of meander bends making them easier to catch.

Features of the River valley that effect settlement emergence The relationships and distances between these key features will affect the ways in which settlements emerge to accomodate a growing population.

Regularly flooded areas

Shallower gradients

Flood plains are usually found in the lower-lying middle course of rivers.

River can burst their banks following heavy rainfalls, spilling the water into the surrouding landscape. The flatter the land to either side of the river, the further the water will spill and larger the floodplain will be. Humans often utilise the flat land that floods regularly to cultivate crops as this land is made much more fertile by flood waters. Ancient calendars were often defined by this regular flooding season and the subsequent harvests.

Areas of land with shallow gradients are sought by settlers to erect their shelters. It requires significantly less energy to form settlements on flat land, areas that are elevated above the flood level and have shallow gradients are often the most suitable locations to initiate settlements.

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Settlement expansion

Settlement Expansion Investigating the effects of an expanding settlement as resources and knowledge increase to fulfil its potential

Settlements are initiated at locations that meet the criteria.

Settlements expand to cater for growing communities, this increase in population is supported by the rivers eco-system and available resources

Communities continue to expand, in one location, until the resources in the immediate area are depleted and/or the land becomes too difficult to build upon.

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Settlement Path Emergence By learning how a settlement will look to expand when it reaches its maximum potential, we can then start to apply this in our digital simulation

When the growth of a settlement exceeds that of the available resources, a new location for settling is sought.

Paths develop linking communities from the existing site with those in new orv nearby settlements.

A network of paths linking settlements along the river is formed, allowing continued growth without depleting local resources.

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Urban Emergence How will the urban arrangement develop as the town increases in both size and population

From the initial settlement, the primary direction of urban emergence runs parallel to the river, in order to maintain each inhabitants proximty to the fresh water source.

It is possible that a settlement may expand and grow away from the river, this only occurs when the surrounding environment dictates it is better to do so.

Eventually the settlement will reach the boundaries constraining its growth, it is at this point that urbanism begins to emerge down pathways leading to nearby settlements.

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Urban Path Emergence By learning how a settlement will look to expand when it reaches its maximum potential, we can then start to apply this in our digital simulation

Building density increases alongside the growing population. Secondary path networks are formed connecting new inhabitants with others in the settlement.

Path networks evolve over time within the emerging settlement allowing easier access to amenities, whilst determing the locations of future properties.

Public buildings are often situated at the heart of existing settlements, as path networks linking settlers are already in place.

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Case Studies

Case Study: Sheffield, UK Don Valley

River Length - 110 km

Multi Scale Analysis of Sheffield

40km

• • • •

8km

Sheffield

Rivers / Tributary

Surrounding Cities

Soft Substrate - Fertile Land

Road Networks

Hard Substrate - Higher / Steep Land

Sheffield resides in the centre of multiple major towns such as Leeds, Manchester and Doncaster.

Located within valleys to all sides, Sheffield sits within the confluence of 5 rivers: Don, Sheaf, Rivelin, Loxley and Porter.

Path networks have developed as these cities grew defining the routes in which the settlements would evolve Using the local minerals and resources found within the ground, Sheffield quickly expanded it’s industrial prowess thanks to accessible transport links from the river. As well as using the river as a source of power

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• • • •

Sheffield has developed alongside the River Don and has been inhabited for around 12,800 years Surrounded by hilltops, Sheffield is protected from the south westerly prevailing wind The fertile land drawn above represents the flood plain of the river.

Sheffield has developed to lie just outside of this region, whilst close enough to take advantage of the opportunity to grow crops Whilst this fertile land helped the early settlements, Sheffield truely expanded during the industrial age, when the city took advantage of lieing on the fasterflowing outside of a meander, and using the river to power turbines

Multi Scale Analysis of Sheffield

2km

1km

Pre 1830’s Settlement

River Don

1830 - 1900

Initial Settlement

1900 - 1940

Urban Emergence

Post 1940’ss

• • •

The city quickly developed and expanded during the 1800’s as the industrial age took hold within Britain Developing along the path networks to Manchester, Leeds and the other major towns, people sought to come to the area due to the large number of opportunities and jobs Over the past 100 years, expansion has slowed, with ronovation being seen as key to the region

• •

To utilise the space as best as possible, properties were developed to sit back to back to allow for an increase in population Open space within the city centre was seen as room to expand for the early governments

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Abstracting Rules of Emergence

Primary settlement in relation to nearby settlements

1km

River Don Initial Settlement Urban Emergence

• • •

Transport to nearby towns was key in Sheffield evolving as the products manufactured within the city could be easily taken to other area; either by the river, or more commonly, road.

These early path networks helped to define the areas upon which buildings could be constructed and helped to shape the city plan The images to the right help to explain the way the city expanded defined by the path networks, whilst the image on the opposite page shows the paths on a larger scale

Road / path networks link settlements

Urbanism emerges along the road / path networks

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Diagramming Rules of Emergence

Elevated Land

Fertile Land

Crossing Points

Fast Flowing Water

Based on the river features we identified in the previous chapter, we wanted to test these theories against Sheffields development. The city expanded primarily due to the fast flowing water on the outside of the meander used to power machinery. There was also a significant use of fertile land in the early history of the area to provide resources, whilst the development was little based on crossing points and elevated land. The urban development appeared to be defined by the road network and there were clear signs that the city grew along these paths, as we had previously predicted, a result we can take forward into our own digital simulation.

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Case Study: Owensboro, USA Owensboro, USA Ohio River

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Multi Scale Analysis of Owensboro

40km

•

• • •

8km

Owensborough

Rivers / Tributary

Surrounding Cities

Soft Substrate - Fertile Land

Road Networks

Hard Substrate - Higher / Steep Land

Owensboro is the 4th largest otwn by population in the Kentucky state, with neighboring nearby towns being Louisville, Evansville and Princeton, as well as being within 200 miles of Cininnati and Indianapolis Lies on a meander of the Ohio River The first European people settled here because their boats were puished to the shore due to the strong current. With evidence suggesting that the first settlers in the area occured 12,000 years ago.

The city is famous for producing whiskey, as well as the Owensboro Wagon Company, utilising the central location and path network

• •

•

Owensboro developed on the outside of a meander of the Ohio River and lies on the opposite side of the fertile land.

Despite the fact that Owensboro grew on the south side of the river, away from the fertile land, this has its advantages in the fact that the area is less likely to flood, and so the city could grow a lot closer to the river and utilise the power of the current a lot more efficiently Due to its location, the climate is hot and humid, whilst moderately cold in winter. Therefore, as well as being on the opposite side of the river to the fertile land, the area may not have grown many crops due to the environment.

Multi Scale Analysis of Owensboro

1km

2km

Initial Settlement

River Ohio

Initial Expansion 1797

Initial Settlement

Secondary Expansion 1900’s

Urban Emergence

Post 1940’s Developments

• • •

From the initial settlelemt, Owensboro has increased in stages in a radial fashion, with the first expansion primarily towards Evansville A secondary expansion occured early in the 20th century, again in a radial motion. During this period, a ring road was established signifying the extents of the city After the Second World War, the city again expanded, however this expansion occured along the road network, adhering to our previous hypothesis

• •

With limited extrnal parameters, and in a similar fashion to other American towns, Owensboro city centre has developed on a grid system Whilst the city centre does not comply with our previous thoughts regarding settlement expansion along path networks, the development in the 1940’s, outside of the city ring road, does mirror our initial thoughts

Abstracting Rules of Emergence

Primary settlement and transport link

1km

Ohio River Initial Settlement Urban Emergence

• • • •

All roads within the city centre run along a North/ South, East/ West axis, with clearly defined areas of the city The images opposite help to diagram the grid expansion Any future expansion is already clearly defined on where it is likely to take place, with any future buildings being restricted by the road networks The residents in Owensboro could build as close to the Ohio River as possible due to the fact they did not lie within the flood plain

Roads are the only growth constraint

Urbanism emerges in grid form, bounded by roads

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Diagramming Rules of Emergence

Elevated Land

Fertile Land

Crossing Points

Fast Flowing Water

Similar to Sheffield, elevated and fertile land carry little significance in the evolution of Owensboro. A key factor was the faster flowing water, allowing industry to thrive and use the river as a power source. The quicker current also brings with it an influx in fish, an alternative food source to the naturally grown crops. These crops could have been grown on the opposite side of the river, therefore crossing points also played a large part.

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Rules for emergence

Rules - Shallow Gradients

Safe to build

Safe to build

Safe to build

It is an inherent building rule, that the flatter the land, the easier it is to construct. Within a river valley, these areas are highly sought after due to the nature in which a valley is produced. In the case studies we have researched, the area has developed thanks to a shallow gradient and we believe this will be one of the key factors in our simulations and any future predictions.

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Emerging Urbanism of River Valleys

Topographical analysis of gradient

Z Axis Angle from verticle

To analyse the gradient in our digital simulations, we will analyse the surface normal, against the Z-Axis. The surface normal is the perpendicular angle created from the face of the surface. The lower that this angle is when compared to the Z-Axis, then the lower the gradient and the higher chance that settlements will begin to develop there. The larger the angle, then the steeper the gradient is and the ability to construct increases significantly.

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Rules - Fertile Land Proximity to river crossing points

Having the ability to find a food source is a neccesity to any settlement. In areas that flooded, when the flooded river drained away, it left behind highly fertile land which was then utilised by settlements to produce crops. These floods often became seasonal, allowing the settlements to predict when they would occur and so could harvest in time. As time went on, settlements began to realise the level to which the river would flood. Armed with this information, the settlement then new the lower boundary that they could build to, to avoid being flooded.

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Emerging Urbanism of River Valleys

Topographical analysis of fertile land

Flooded Water Level

Normal Water Level

In our digital simulation, we are going to set two river levels, a normal and flooded. Doing this will allow us to create a region of fertile points and find a desirable location for the settlelments. Depending on the surface that is created, it will be possible to see where the gradient is flatter, which will allow the river to flow over more land and create a larger fertile land region, as is depicted in the diagram above, to the left of the river. In this larger fertile land region, it will then be possible to cultivate and grow crops. Where the river bank is steeper, a smaller fertile land region will be created, meaning that it will be harder to grow.

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Rules - River Crossing Points Proximity to river crossing points

Often found near the source, in the upper course of the river, are shallow, narrow crossing points. Looking for these narrow points further down the river is another key finding of our research. These narrow points meant that less time and resources were needed to produce a bridge type construction, therefore less energy wasted. The crossing points also allowed towns such as Owensboro and Budapest, to develop or use the land on the opposite side of the river.

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Emerging Urbanism of River Valleys

Topographical analysis of potential crossing points

Depth

Width

Determining the shallow and narrow points of our digital simulation will allow us to find the natural crossing points. We plan to analyse the width of the rivers created and use this in the urban emergence. By finding the crossing points, it will enable us to attempt to find possible paths that would be taken, to allow further settlements to develop along the river.

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Rules - Fishing Locations Proximity to river crossing points

Crops is not the only food source that a river can provide, with fishing being another key consideration. Where little fertile land is available, fishing becomes the main food supply and is highly sought after, especially in the higher mountainous regions where the land is steeper and the temperature colder, meaning cultivation is extremely difficult.

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Emerging Urbanism of River Valleys

Topographical analysis of potential crossing points

Shallow / slow current

Deep / fast current

As the river meanders, the current flows faster around the outside, cutting and eroding a larger proportion of the river bed, compared to the slower moving inside bend. With this faster current around the outside, comes an increased population of fish as they are pushed around, meaning a greater chance of catching food. In our digitial simulation, we will analyse the curvature of the curve, in an attempt to predict the best fishing places.

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Initial river valley simulation

Elevation Analysis Visualisation

Gradient Analysis Visualisation

Areas Satisfying Parameters

Digital Simulations

Three-dimensional topography formation Describing the process of how we have created a flexible surface, in order to allow us to predict the Urban Emergence final arrangement in the future, based on numerous iterations of weighted rules

To give ourselves greater flexibility, we created ourselves a NURBS surface.

We were then able to manipulate it in the Z-Axis to create a surface

With this surface, we can then analyse the effects of one river source

Or multiple river sources and witness the results

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Plotting rivers on three-dimensional topography

From the single river source, we can see the path that the river will take.

Increasing the river level due to heavy rains we can find the flood plain

We are also able to see the results of adding a second river

And again the results of the flooded rivers

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Digital Simulation - Creating the Valley Creating the river valley that we will use to test our rules and devise a conclusion

Creating a random surface from which we can examine the results of our theories

The river valley was defined by the path of the river

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Digital Simulation - Creating the Valley

The river flows down the valley from pre-determined sources

Overlaying a grid of points, enables analysis of the surface at any given point to ascertian areas the best comply with our rules

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Digital Simulation - Our Rules By using the surface we have created, we are able to examine the various points that meet the needs of the individual rules

Finding flatter land upon which to build made it easier for settlers.

Based on our inital points, the points highlighted offer initial settlement points based ona gradeint of below 10 degrees

Settlers often looked for fertile land from which they could grow crops.

The points shown lie within the flooding region, meaning they will be most fertile through the growing season

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Digital Simulation - Our Rules

Crossing points allowed settlements to grow and so settlers often looked for the narrowest part of the river when determining their initial location.

Highlighted are the best crossing points

On the outside of a meander the river flows slower and so fish can be more readily caught. Shown on this diagram are areas on which the river will be flowing at its slowest

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Digital Simulation - Testing Our Rules Testing the surface against a number of rules with differing weights to examine the final outcome

To test our theories, we decided to weight our rules and try and predict where the initial starting point would be.

Starting from our initial points, we then deleted points that we found were on too steep a gradient.

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Digital Simulation - Testing Our Rules

From these points, we then found the closest points to the fertile land, whilst not lying within the flood plain

Finally, we found the areas that could be expanded easily.

Therefore, we narrowed down our inital points to the ones closest to the crossing points

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Digital Simulation - Finding the Initial Settlement Narrowingdown the inital settlement to one location

We managed to narrow down our starting points to several initial locations. We are now going to attempt to narrow this down even further. We start by finding how many points are within the immediate vicinity.

To find the closest points, we drew circles around all of our points. We then grouped these circles together, in order to find the ones with the largest area. This means that the region has the best chance in which to expand.

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Digital Simulation - Finding the Initial Settlement

After analysing the areas, we then cull the regions which we believe to be too small

Finally, we again search for the region which are closest to the fertile land and the crossing points, and are left with the one intial settlement.

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Digital Simulation - Urban Emergence Focusing in on our surface, we can begin to analyse how the city would begin to develop based on our rules

From an initital starting point, the village will begin to expand, looking for its closest neighbour point

In the early stages, the settlement grows in a linear fashion

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Digital Simulation - Urban Emergence

Based on the points we found the settlement begins to grow along these points, having to curve around with the gradient, before diverting back towards fertile land.

Eventual settlement layout, based on pre-determined parameters

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Digital Simulation - Urban Emergence Using the knowledge we learnt by analysing path networks, we can begin to predict how the settlement will look to expand outside of its territory

As the settlement expands, eventually it will reach maximum capacity. The settlers will then look to find a new territory. Based on our theories, we have found these new location points.

Analysing the direct paths, the settlers will have had to have crossed extreme terrain in this scenario. The river was often used for transport, allowing settlements to develop along the river banks

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Digital Simulation - Urban Emergence

Highlighted are the previously culled initial settlement regions, which were culled due to being too small. These areas could eventually develop being passing points to the larger settlements

Shown in green are the predicted smaller settlements that would develop as the 4 larger settlements grow

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Digital Simulation - Path Outcomes On a smaller scale, investigating the effect the path networks will have on the smaller, satellite villages

As the settlements begin to expand and searching for new areas, small satellite villages will start to develop, as discussed on the previous page

Looking on a smaller scale, these satellite villages will begin to expand in the directions of the larger towns

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Digital Simulation - Path Outcomes

The larger towns will develop and expand towards the satellite villages and the other larger towns. These settlements will then start to trade between themselves

Final iteration including the smaller towns of how we believe the region would develop based on our rules

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Digital Simulation - Various Iterations Testing the surface based on a variety of iterations to deem wether the script has been succesful and allowed us to predict a final scenario

This final iteration is based on the gradient being weighted heaviest, before fertile land.

In this iteration, the most important parameter was the fishing points, before culling the too steep gradient points

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Digital Simulation - Various Iterations

Here we have examined what would happen if the crossing points were weighted the heaviest, before culling the fertile points

Finally, we looked into the fertile land points, and fishing points

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â&#x20AC;&#x153;We have always believed that River valleys offer the best option available for a settlement to emerge and allow urban growth. Through our initial research, we found the key criteria required when searching for an initial starting point based on any environment, then focused this criteria to river valley specific parameters. We were able to analyse path networks, how they formed the basis of new settlements and informed the evolutionary direction of the given settlements.

Through our case studies, we were able to see that settlements did not need to fulfil all of the criteria, meeting just a few was enough to allow major urban development. Weighting the criteriaâ&#x20AC;&#x2122;s a food source, be that crops or fish, was a necessity; alongside the flatter gradients to allow easier construction given the limited construction techniques.

After thorough research we were able to devise 4 key criteria needed to enable urban growth. These being: shallow gradient to allow construction, fertile land to allow the cultivation of crops, narrow/ shallow points permitting easier crossing and further exploration and fast flowing meanders meaning a greater source of fish.â&#x20AC;?

â&#x20AC;&#x153;Using this knowledge, we could digitally create a surface and test our hypotheses, varying the weightings of the parameters in a similar fashion to the case studies, in order to predict the initial starting point, the expansion routes and the final outcome of our modelled terrain. We believe that the results found are in the areas that we would have imagined settlements to develop given the environment and that the urban evolvement to the nearby settlements would have been true. However, we based our initial starting settlement based on area and the potential to increase the settlement size. This may not have necessarily being true, with a settlement emerging at the earliest opportunity available given the direction that the travellers came from. Therefore, this may have meant that different satellite villages would have developed and the final scenario would have been different. Furthermore, every travelling community may have weighted their needs differently to the ones we have predicted, had a variety of construction methods, required another key principle such as elevated land for security, consequently another final outcome would have emerged.

We believe that given the information and the surface topography, using our script we would be able to find an initial starting point and the final outcome of a scenario, based on a given set of rules. There are options to incorporate a variety of parameters within our script, where additional data can be collated such as; Wind velocity, Material / Energy use per person, Geological surveys, or Tidal influences.â&#x20AC;?

Conclusion

EMERGENT URBANISM HILLS

By Dominic Kennedy

123 EMERGENT URBANISM_HILLS 123

TYPES OF HILL AND WAYS TO INHABIT

MOUNTAIN Formed by tectonic forces and volcanism Generally uninhabitable Highest points viewed as a connection to the Gods

HILL Formed by erosion and weathering Strategic devices for fortification, authority, storage of resources Inhabitable and suitable for agriculture

CLIFF FACE Formed by erosion and weathering Inhabitable spaces to protect civilisations from the harsh elements or climates across the world

124 EMERGENT URBANISM_HILLS 124

HILLS AND HIERARCHIES IN URBAN ARRANGEMENTS

LOCATION FOR MONARCHY / DYNASTIC INFLUENCE

RELIGIOUS PRESENCE ANCIENT ROME, CHRIST THE REDEEMER, TIBETAN MONASTERIES

FORTIFICATION - SITES FOR GOOD VANTAGE POINTS AND ATTACK ADVANTAGES

LOCATION FOR HOUSING HIGH VALUE / IMPORTANCE RESOURCES TO DISTRIBUTE TO OTHER SETTLEMENTS

HILL TOP / SUMMIT

AUTHORITY

HILL BASE / VALLEY

PROVIDERS

HIERARCHIES Hills have traditionally been used for hierarchical delegation of authority or importance of amenity.

The higher regions of hills are where the decision making, high value persons/goods would be located making it a key node to inhabit or take over.

The ‘providers’ to the ‘authority’ settlements would be located in the lower altitudes. They would be subservient to the king or dynastic region and provide resources. Both parties however would have a strong mutual reliance upon each other. For example, a high defensive settlement would sacrifice amenities such as arable land, water sources lower down and the providers would require protection of resources, families, etc from rival tribes.

MUTUAL RELIANCE

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FLOOD AVERSION

SEASONAL FLOODING DETERRED ENEMY ATTACKS

HIGH ALTITUDE LOCATIONS AVOID OR CURB FLOOD RISKS IN RAINY SEASONS

Uses today Today, hills are also used for sustainable measures. Higher terrains can be utilised for the wind energy generated by wind turbines.

Recent climate change has resulted in increased rates of flooding around the world. Measures have been taken therefore to utilise sustainable urban drainage (SUDS) to reduce these catastrophic effects in valley regions.

Tourism is a large industry today and hilly topographies have taken advantage of this.

Chamonix resort on Mont Blanc, for example held the first Winter Olympics in 1924 and has attracted extreme sports enthusiasts and winter holiday makers ever since.

126 EMERGENT URBANISM_HILLS 126

SUSTAINABLE ENERGY WIND FARMS

SUSTAINABLE URBAN DRAINAGE (SUDS) FOR EXAMPLE TREE PLANTATIONS TO REDUCE FLOOD RISK IN VALLEYS

LEISURE / TOURISM INDUSTRIES

TACTICAL ADVANTAGES OF HILL TOPOGRAPHY

ANTICIPATED FLOOD ZONES, TYPICALLY IN VALLEYS OR THE BASE OF STEEP TOPOGRAPHY

DEFENSIBLE AREAS ADVANTAGEOUS TO ENEMY ATTACKS

HIGHER ALTITUDES PROVIDE BETTER VANTAGE POINTS

FLOODING

CLIFFS

VANTAGE POINTS AND VISIBILITY

The potential risk areas have been mapped here to demonstrate where flood zones occur at high point in the rainy season.

Whilst the steeper gradients of cliffs show where cultivation, construction and access to and from the summit are more difficult to achieve, they are tactically essential for defense.

High points have been traditionally used on topographies around the world for awareness of contextual surroundings. Being higher than everyone else would provide a tactical advantage when spotting enemy troops from a distance.

Hills can be used tactically to avoid areas which are susceptible to flooding, but also locating near to water traditionally enabled a defensive barrier between rival tribes making it more difficult to penetrate a settlement.

Ascending up the areas highlighted below would significantly deplete energy resources over flatter terrain. Therefore, traditionally the more successful hill settlements embraced these conditions to make it more difficult to find and also attack.

Locating settlements or icons equally means that these locations can be seen more visibly by settlements lower down. Landmarks or beacons would be situated here to signal a high importance monument or party.

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AIMS AND OBJECTIVES

+ DEFINE TOPOGRAPHY

DEFINE THE RULES

EVALUATE STRENGTHS / WEAKNESSES

AIMS AND OBJECTIVES The aim of this exercise will be to discover the rules that different topographies employ, when inhabiting a hilly or steep terrain.

Some examples may employ a set of rules to address an intended purpose.

This may include factors such as tactical attack and defense, climate considerations or simply finding the most suitable location to house the most amenities to prosper for the long term.

These notions will then be cross examined to ascertain where these rules may be strong or weak in a different extreme environment.

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CROSS EXAMINE RULES WITH OTHER TOPOGRAPHIES

ANCIENT PERGAMON URBAN RULES

MORE FUNCTIONS INCORPORATED Desirable site incorporates more uses. Key uses clearly ordered into differentiated districts - for example the barracks, palaces, cultural quarter, shops.

LANDMARKS AND ICONS Key diplomatic, religious and societal monuments were designed to be presented in the most desirable wy possible from the lower regions of the city.

ANCIENT PERGAMON Pergamum was an ancient Greek city in Aeolis, on the north side of the river Caicus (modern-day Bak覺r癟ay). The ancient city housed its cultural and religious landmarks at the highest, flattest peak of the city. It used its altitude to exhibit its exquisite monuments to bee seen from afar and justify its title as a cultural hub in Ancient Greece.

129 EMERGENT URBANISM_HILLS 129

PERGAMON - SCRIPTING THE FLATNESS RULE

METHODOLOGY

X Y Z CREATE TOPOGRAPHY

DIVIDE SURFACE TO ACCURATELY EVALUATE ALL REGIONS

DECOMPOSE DATA TO EVALUATE FLATNESS

DEFINE DESIRED FLATNESS

DISTINGUISH FLAT ZONES

DEFINE SUITABLE HABITABLE REGIONS

PROCESS

DEFINED SURFACE Defined geometry mapped for specific topographical location.

DIVISION OF SURFACE Division of topographical surface to more accurately evaluate parameters

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MAP TO SURFACE Find closest point on surface to evaluate

DECOMPOSE DATA Decomposing the surface into 3 dimensions enables critical evaluation of the Z-axis.

DEFINING FLATNESS Parametric controls enable a degree of flatness to be defined on the terrain.

CULL By cross-referencing the points higher than an inferred height with the total points gives the results at the higher altitudes.

PERGAMON - SCRIPTING THE FLATNESS RULE

1] TOPOGRAPHY DEFINED

2] ALL FLAT AREAS MAPPED

4] DESIRABLE SETTLEMENT AREAS MAPPED

DETERMINING AREAS

DEFINING FLATTEST TOPOGRAPHY FOR SETTLEMENT

FLAT AREAS DISTINGUISHED

FLATTEST

TOPOGRAPHICAL

The flattest topographical areas have been mapped here to determine suitable areas for overall vantage points, crop growth and village clustering. The blue demarcated zone shows potential flood risk parameters which, whilst this area may be flat, may be less desirable than locations in higher altitudes.

The water zone (blue) was advantageous to the settlement of Pergamon due to its defensive strengths.

This would have acted as a barrier to the site from rival tribes. The resource would have provided sustainable resources to make this settlement prosper for the long term.

3] FLAT AREAS DIFFERENTIATED

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ANCIENT PERGAMON URBAN RULES

METHODOLOGY

X Y Z DECOMPOSE DATA TO EVALUATE STEEPNESS

DEFINE DESIRED FLATNESS

CULL INVALID REGIONS

PROCESS

Referencing FLATNESS rule Referencing the flatness rule shown previously enables more in depth analysis of habitable regions to determine more suitable flatter high points.

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HEIGHT PARAMETER Parametrically decipher the correct location using the referenced data.

Sort data into ascending order Sorting the data found in the Z-axis allows for ease of selecting correct points. Used this as reference to define flatness.

DEFINE SUITABLE HABITABLE REGIONS

PERGAMON - DETERMINING HIGHEST AREA RULE

SUITABLE HIGH POINTS FOR LANDMARKS AND ICONS

PERGAMON LANDMARKS AND ICONS

OPTIMAL LOCATION FOR FLATTEST, SAFEST LOCATION FOR MULTIPLE USES

HIGHEST POINTS

MOST DESIRED HIGHEST POINTS

The highest points of the topographical surface have been mapped to show where the most effective vantage points and most noticeable points may be located when considering the contextual surroundings.

The flattest, highest points remain, making this area the most desired topographical area for settlement.

FLATTEST, HIGHEST, SAFEST LOCATION

133 EMERGENT URBANISM_HILLS 133

PETRA FIGURE GROUND PLAN

PETRA Petra is a unique city, carved into the arid, rocky mountainous region of Maâ&#x20AC;&#x2122;an in Jordan.

Unlike the Norman settlers who exposed themselves to the hot elements just 170km away in Kerak, the settlers took the climate into close consideration. The trade routes were channeled by the steep cliffs that formed this dramatic topography. The settlers used the cliffs for inhabiting and for amenities such as the treasury.

134 EMERGENT URBANISM_HILLS 134

Cliff inhabitation

Protection from climate

SETTLEMENTS FORMED ALONG Channeled trade routes

Religious usage

PETRA - SCRIPTING THE STEEPNESS RULE

METHODOLOGY

X Y Z CREATE TOPOGRAPHY

DIVIDE SURFACE TO ACCURATELY EVALUATE ALL REGIONS

DECOMPOSE DATA TO EVALUATE STEEPNESS

DEFINE DESIRED STEEPNESS

CULL INVALID REGIONS

DEFINE SUITABLE HABITABLE REGIONS

PROCESS

DEFINED SURFACE Defined geometry mapped for specific topographical location.

DIVISION OF SURFACE Division of topographical surface to more accurately evaluate parameters

DECOMPOSE SURFACE Decomposing the surface into 3 dimensions enables critical evaluation of the Z-axis.

EXAMINE DATA Check data points to establish points needed to cull / maintain. Used this as reference to define steepness.

CULL By cross-referencing the points higher than an inferred height with the total points gives the results at the higher altitudes.

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PETRA CLIFF RULE

PETRAâ&#x20AC;&#x2122;S TACTICAL CLIFF INHABITATION The mapped nodes depict cliff inhabitation forming. There are multiple reasons for utilising this type of topography that is often avoided. Firstly, the hot and dry climate would have made inhabiting open high areas difficult to live sustainably in this desert region of Jordan. Inhabiting the shaded cliffs would have therefore curbed this difficult condition.

Tactically, this rock cut, man made route through such a steep vast terrain made it necessary for traders, invaders and religious parties to make use of. The route carved through the basin has inevitably been inhabited along it, to either attract sales for trade, maximize religious gathering numbers and provide key vantage and defensive points for attacking unwanted guests.

136 EMERGENT URBANISM_HILLS 136

DEFENSIVE STRATEGY Carved route channeled unwanted parties into areas where they would be easy to ambush

VANTAGE POINTS High cliff regions enabled ease of attack below. Easy to predict opponents movements

ROUTE FORMED IN BASIN SETTLEMENTS FORMED ALONG PATH for commerce, religion and tactical reasons

KERAK CASTLE

VANTAGE POINTS Open location allows for maximized sight lines from all directions

URBAN ENVELOPE Settlement enclosed in perimeter wall to maximize security and defense from outside world.

CLIMATE ISSUES The hot climate was not as well considered as the defensive strategies

KERAK CASTLE Kerak Castle is a large crusader spur castle located in Kerak in Jordan. A spur castle is a type of medieval fortification that uses its location as a defensive feature. The crusaders who inhabited the castle of Kerak were motivated by the preservation of their influence and defense against rival parties; the high vantage points and urban envelope addressed these aims and intentions quite successfully. However, Jordan maintained a hot climate which would have made long term inhabitation for the Normans difficult.

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KERAK CASTLE - SCRIPTING HIGH POINT RULE

HIGH POINT AND STEEPNESS RULE

METHODOLOGY

The intention here was to map the highest points to depict the most strategical advantageous vantage point in the settlement; in this case the rule was the ‘highest point’. The cluster in the first image below shows the highest points set by a small threshold domain. This is indeed the location of the Kerak Castle container settlement. This location would provide panoramic vistas from the most directions making the settlement secure, tactically.

The steepness rule is then applied in conjunction to depict the topography which would be deemed difficult to climb. Set by a gradient parameter, the areas highlighted in green show steep banking features locally. This factor would exert more energy for the intruder as opposed to inhabiting the flatter ridge lines higher above. These would have been avoided by the enemy due to being quickly spotted from the castle. Defensively, the inclines surrounding Kerak Castle provide excellent defensive attributes for the inhabitants as a result.

DEFINE HIGH FLAT REGION

EVALUATE AND DEFINE STEEP ZONES

PROCESS

RULES DEFINED Height and steepness rules defined and culled

HIGHEST POINTS RULE

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STEEP TOPOGRAPHY REGIONS ENABLES MORE PROTECTION FOR CONTAINER SETTLEMENT

KERAK - MAPPING ACCURATE CO ORDINATES FOR DATA METHODOLOGY

N째E째 GATHER OS COORDINATES

OS CORDINATES Data collected from OS coordinates

TREE DATA Data collected from OS coordinates extracted into different path networks

MAP CO ORDINATES

TOPOGRAPHY OS Data and VRML space data gathered to accurately plot world location

EXTRACT DATA TREES INTO ROAD TYPES

TOPOGRAPHY MESH Surface created using accurate OS and topographical satellite coordinates

MAP TO TOPOGRAPHY

ROUTES MAPPED Direct path networks mapped to topography to create accurate analysis of hill settlement

139 EMERGENT URBANISM_HILLS 139

KERAK PATH NETWORKS

TOPOGRAPHY

WATER AMENITIES NEARBY

MAIN PATH NETWORKS FORMED FROM CASTLE / HIERARCHY

TERRITORY PATH NETWORKS FORMED FROM CASTLE EPICENTRE

PATH NETWORKS The diagram depicts how the primary and secondary path networks are notionally formed from the hierarchical epicentre of Kerak Castle. Here, generative path networks have spanned across the flat ridge line topographies to create the most direct path systems to other settlements.

This method of generating path networks would conserve energy otherwise exerted from ascending steep topography, which has largely been categorically avoided.

Tactically, inhabiting the high open roads would preserve vantage points from the castle from all directions and at an increased distance.

The steeper topographies are largely uninhabited by settlements. Whilst the hot climate is a factor which can make inhabiting Jordan in the higher exposed altitudes difficult, the flatter terrain evidently becomes a more favourable attribute as opposed to building into hilly terrain. It has been utilised positively here to create a network which is closely arranged and conserves minimal energy.

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KERAK CASTLE AT THE CENTRE OF ROUTES TO ALL DIRECTIONS

FLAT TERRAIN RULE FOR INHABITATION

SWAPPING THE RULES

EXTREME CLIMATE Exposure

INCREASED / DIFFICULT ROUTES

VANTAGE POINTS KERAK ‘HIGH FLAT POINTS’ RULE MAPPED TO PETRA

SWAPPING THE RULES AND TOPOGRAPHIES - ‘HIGH FLAT POINTS’ AND ‘LANDMARKS AND ICONS’ RULE IN PETRA As discussed earlier, the hilly settlements which adopt the rules have been chosen with a focused intention. Whether this is to be the highest settlement for defensive reasons, the flattest location to accompany most districts or functions in the most dense area or to adapt to an extreme climate by sheltering, all the case studies have shown effective use of the notional hill.

However, the results become even more interesting when these acutely defined principles unique to a site are swapped with a contrasting topography. In the first instance, Petra has been mapped with the ‘highest points’ rule seen in Kerak and Pergamon. As seen before, the rule becomes successful on first glance at locating the potential threats from below.

On the other hand, being located at the highest points is perhaps not as successful as the native origins of this rule.

Firstly, Petra is a steeper, vertical gradient than Pergamon and Kerak. This could work for or against the settlement, depending on the intent. If the intent is to be spotted, such as in the case for the cultural buildings in Pergamon, the rule would not be as successful due to the extreme variation in height over area.

If the intent were to be of a defensive nature such as the case would be in Kerak, adopting the highest point in Petra would have been advantageous to spotting the channeled tribes below or spotting the threat on the adjacent higher altitudes. This luxury would come at a cost however, due to increased energy consumed from ascending or descending the high altitudes, although this again would be a strength defensively.

141 EMERGENT URBANISM_HILLS 141

SWAPPING THE RULES

Diversification of districts

Vulnerable from all directions TO ENEMY ATTACK

?

PERGAMON FLAT POINTS RULE MAPPED TO PETRA

SWAPPING THE RULES AND TOPOGRAPHIES - ‘LOW FLAT POINTS’ RULE IN PETRA The ‘defined low flat points’ rule is then applied to Petra, a notion taken from Pergamon which considers maximum cumulative flat area to accommodate multiple districts. The results show inhabitation of the carved route as before, suggesting successful inhabitation of the route to channel trade, religion and enemy attack from one concentrated direction.

However, the open meander previously left vastly open by previous descendants of Petra would be perhaps an unsuccessful location defensively. This is because the direction of enemy attack now becomes more unclear, where before the cliff inhabitation of the man made rock-cut route clearly channeled enemy combatants in a linear notion.

Being located lower down at a crossroads would also leave the inhabitants incredibly vulnerable, with the advantage of being located at a higher altitude than their adversaries is gone. This would be due to the vantage points lost.

Neither scenarios discussed here successfully consider the hot climatic implications in Jordan. The original steepness rule applied to Petra is the most triumphant at addressing this factor which was implementable to the development of this urban area long term. Therefore, this rule which was otherwise successful elsewhere would fail the civilisation would undertake these principles in this urban extreme environment.

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DIFFICULT TO TRACK ENEMY MOVEMENTS

SUMMARY

SUMMARY From the case studies discussed, the motives behind all these settlements that inhabit the topographies have clearly defined rules to address a requirement to ultimately survive or sustain a long term establishment in an area.

The ‘high point’ and ‘landmarks and icons’ rules for Pergamon showed successful results contextually.

Utilising these notions at the high altitudes would enable the acropolis to exhibit its cultural status through portrayal of its landmarks. This would have been difficult to achieve if these beacons were less visible in a lower down region.

Some settlements studied are more rounded than others.

In Kerak for example the settlement is incredibly secure from enemy attack due to its raised elevation, steep topography surrounding it and contained fortification.

However, Kerak is a hot climate which would have been difficult for the Norman settlers there who would have not been indigenous to this location. Left isolated, this hill fort settlement would have struggled to sustain itself long term without the path networks which subsequently formed to provide for this centre of hierarchy and decision making.

Steep cliff topography is usually a solely defensive aspect instrumental to topographies. Hill settlements usually favour inhabitation of flat high points. However, Petra has exercised the steepness rule to meet hot climatic drawbacks in the desert region of Jordan. By carving out the rock to create linear route, the settlements forming along this would have benefited in terms of trade, religion and defensively to create a robust cliff settlement that could establish itself long term.

When swapping these rules shown to be successful with each other, the results have shown to be quite drastic and surprisingly unsuccessful in places. The results demonstrate that the rules applied have been more carefully considered than by simple randomness or trial and error. The native regions of the rules have been applied to make the best use of an extreme aspect of a topography and these rules cannot be necessarily universally applied to another topography to achieve a similarly successful urban arrangement.

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Hillside Urban Landscapes Richard A F Arthur

Contents Introduction - Hillside, Urban Landscape Hillside Attractors

Traditional Hillside Attractors

Evolutionary Hillside Attractors Case Studies

Lincoln, Lincolnshire, England

Longsheng, Guangxi, China

Derinkuyu, Cappadocia, Turkey

Paro Taktsang, Paro District, Bhutan Hillside Urbanisation Rules Traversing the Landscape

To Move Across the Landscape

15o Path Gradient

30o Path Gradient Bibliography List of Illustrations

Introduction

Definition of ‘Hillside’ - The sloping side of a hill.

Further to this definition Hillside Urbanism encompasses Hills, Mountains and Cliffs. A Hill is a naturally raised area of land, not as high or craggy as a mountain.

Mountains are large natural elevations of the earth’s surface rising abruptly from the surrounding level. Cliff, steep rock face, especially at the edge of the sea or on mountain sides.

This chapter will describe how it is possible for these regions of the earth’s landscape are able to urbanise. All urban growth has reasons to why the location was suitable, these reasons generally are in the form of a primary attractor and these can either be traditional or more recently evolutionary. Once an attractor has laid the foundations for growth to start clear rules and understanding mould the way each urban landscape will form.

Through the use of case studies taken from different regions in the world each with different attractors, the rules and understanding can be extracted. These rules can then be further studied to aid new growth. Rules can be implemented through the entire lifespan of an urban landscape from the very beginning with the first structures emerging to the continuing growth, or eventual infilling and transformations of landscapes for other purposes. The end of this chapter begins to use some of these rules in a simulation for terrain traversing which is a fundamental aspect of a Hillside Urban Landscape.

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Traditional Hillside Attractors

Monarchy Monarchs and people of importance tended to favour hill tops for residences. Primary reasons for this were, Defence and an Influence over the surroundings. With a structure of this importance came eventual and gradual urbanisation. left: Edinburgh Castle

Religion Historically it was believed that the higher you stood in a landscape the closer you were to heaven. For this reason hill tops were seen as the perfect locations for religious houses. In these cases the wealthier tended to settle around the point of interest and class spread out from this point. left: Lincoln Cathedral

Fortress In a hostile environment it was fundamental to have a raised position to be able to effectively see the surroundings and repel any potential attacks. Urban growth would be found near to such fortresses so that citizens my take shelter in times of need. left: Krak des Chevaliers

148 Hillside, Urban Landscapes

Evolutionary Hillside Attractors

Produce As populations continue to increase the need for produce (food / materials) also increases. This need generates a requirement for more cultivated land. With the creation of new produce landscapes there becomes a need for urban interventions.

Right: Longsheng Rice Terraces

Energy With the growing energy requirement especially in the renewables sector a new attractor has be produced. These large installations are generally found on hillsides. The installation process requires heavy machinery and therefore there is a requirement for new infrastructure in an area that has been previously untouched allowing a new urban landscape to develop.

Right: Scottish onshore wind farm

Leisure The leisure industry has played a large part in the development of newly emerging landscape. This development can primarily be seen within the ski industry where people require an unban landscape to survive while using the hillsides. Development can be found on the upper and lower slopes.

Right: Ski Run in France

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150

LINCOLN, Lincolnshire, England Lincoln is a Cathedral City and County Town of Lincolnshire, England. Lincoln developed from the Roman town of Lindum Colonia, which developed from an Iron Age settlement. Lincolnâ&#x20AC;&#x2122;s major attractors are Lincoln Cathedral and Lincoln Castle. The city is also has modern attractors in the form of the University of Lincoln and Bishop Grosseteste University.

Attractors on the topography

Path angle & width

Urban development

Growth from attractor

Avoiding topography

Growth along pathway

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152

LONGSHENG, Guangxi, China The Longsheng Terraced Rice Fields are built along the Longsheng slopes from the riverside up to the mountain top, between 600m to 800m. The terraces divide the mountain into layers of water in spring, layers of green rice shoots in summer, layers of rice in fall, and layers of frost in winter. The terraced fields were mostly built about 650 years ago.

Attractors on the topography

Slope transformation

Urban development

Growth along pathway

Path of least resistance

Lines of sight

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154

DERINKUYU, Cappadocia, Turkey Derinkuyu is notable for its large multi-level underground city (Derinkuyu Underground City), which is a major tourist attraction. The historical region of Cappadocia, where Derinkuyu is situated, contains several historical underground cities, carved out of a unique geological formations. The underground cities are not generally occupied but there has been urban development due to this attractor.

Attractors on the topography

Using natural landforms

Urban development

Growth from attractor

Growth along pathway

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156

PARO TAKTSANG, Paro District, Bhutan Paro Taktsang Monastery is a prominent Himalayan Buddhist sacred site and temple complex, located in the cliff-side of the upper Paro valley, in Bhutan. The access to this site is by a winding mountain path which is slowly developing as the popularity of the temple grows as a tourist destination.

Attractors on the topography

Path of least resistance

Urban development

Growth along pathway

Using natural landforms

Path angle & width

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Hillside Urbanisation Rules

Growth from Attractor As described earlier in this chapter there are different forms of attractor. These urban attractors generally become the epicentre of urban growth.

Growth Along Pathway Before or after an attractor has formed in an area a communication route will lead to and from the attraction. This route may begin as a pilgrims pathway which becomes a cart track for supplies or trade. Once the route is established it may progress to become a road so that a larger volume of traffic may flow along it. As a route becomes more of a resource it too becomes an attractor and reason for urban increase.

158 Hillside, Urban Landscapes

Using Natural Landforms In multiple regions of the world existing landforms are used as urbanisers. Through either natural means or human intervention a landscape can provide a suitable base for constructing.

As described above the region of Cappadocia is famous for structures of this form, soft rock erodes and the hard volcanic rock remains. The settlers of the region used these formations as starting points for their urbanisation, which then spread deep underground.

These settlements became attractors for future growth once the underground cities were no longer required.

Path of Least Resistance The shortest and most direct path route may not always be the most economical or viable in terms of cost, energy, time and intended use. Routes for different uses will have an optimal path.

Linked to Path Angle and Width.

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Path Angle & Width There is a direct correlation between the gradient of a path or route and its width. A pathway intended for pedestrian use can be wide enough for a single user and the gradient can be greater due to the size of the user, this pathway can be cheaper to construct / maintain and requires a low energy output.

A route intended for large vehicles (horse & cart to cars & lorries) will require a route adapted to their needs. Width will be wider and the gradient angle will be less. This route way will have high construction / maintenance costs and a large energy requirement.

Avoiding Topography In most cases of hillside urbanisation there will be gradients that are not built on. The predominant reason for the is the excessive gradient of the slope. These areas if built on will usually be the last area of urban growth with the landscape requiring amendments to be made to create a suitable site for building on. One amendment would be slope transformation in the form of terracing.

160 Hillside, Urban Landscapes

Slope Transformation There are many ways of urbanising a slope and transforming a slope can allow greater diversity. This transformation could be used for both construction and industry.

The most common form of slope transformation is Terracing. This transformation creates flat areas of land but retains the slope outline. Terracing is widely used for agriculture especially used in rice and grape growing. The flat steps also provide suitable building landscape without the need for expensive columns and deep foundations. Terracing a landscape helps to slow natural processes like erosion.

Lines of Sight Building on a hillside will generally come with a view. When constructing this view from a single location is not the only view point that needs to be taken in to consideration as others will have a similar view which should not be obstructed.

This is where slope transformation can be implemented along with growth along pathways and avoiding topography.

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Traversing the Landscape

To Move Across the Landscape From A to B

Start Location Point A Look ahead for shallowest path

Viewing Distance

Shallowest point becomes Point C

Chosen Multiplication

Look at Point C

Define Path Gradient

Define Move Distance

Movement boundary

Move to Point D

Positive points on boundary

Is Point D Point B?

Find closest point to C

Yes

Closest point becomes Point D

Move to Point B

No

Destination Point B

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15o Path Gradient

164 Hillside, Urban Landscapes

30o Path Gradient

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Conclusion

Chapter Conclusion This chapter has looked at primary reasoning as to why a â&#x20AC;&#x2DC;Hillsideâ&#x20AC;&#x2122; can urbanise. From these primary reasons and through the use of case studies I have been able to extract some rules which are implemented and many are unique of a hillside environment. These rule can be simulated in any hillside environment to be able to produce the best urban development possible.

Personal Conclusion I have enjoyed undertaking this project. Through reading and studying I feel that I have furthered my understanding of urban development and processes. I have been able to formulate some urban rules and understand these rules in a logical fashion.

The progression I was looking to take has been hindered by my personal understanding of computer programs to effectively simulate the extracted rules. If I was to undertake this project again I would do so once I had built a higher program knowledge to develop the rules and simulations.

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168 Oasis Theory and Research

Oasis Theory and Research Sam Hayes Jan Harmens

Contents Analysis of Case studies - Dunhuang Oasis Location Context History - Huacachina Oasis Location Context History - Kabr Aun Oasis Location Context History - Bahariya Oasis Location Context History Dynamic Flow Exploration Application Analysis Conclusion Cellular Automata Exploration Application Analysis Conclusion Application to Huacachina Oasis Theory Development in Co-ordination with Case Studies Conclusion to Oasis Research with Calculated Spacial and Carrying Capacity Formulas Appendix

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What Is An Oasis?

‘A fertile spot in a desert, where water is found’ - Oxford Dictioinary An Oasis is an island of life in an ocean of temperature extremes.

170 Oasis Theory and Research

The Difference Between An Oasis And A Lake

An oasis typically has a small water source, fed from underground and rain but never from streams, tributaries or rivers. It can also ‘go dry’. Oasis areas are typically NOT man made.

Most lakes remain filled with water, except after/during a drought. Depending on environmental conditions, lakes can “go dry”. Lakes can be fed from underground or from streams, tributaries, and rivers. Some lakes came into being as a result of human planning.

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World Deserts Sahara Peruvian

Turkestan

Atacama Gobi

Australia Great Indian

Great Basin Patagonian

Arabian Kalahari & Namib

172 Oasis Theory and Research

Most World Renowned Oases Oasis of Maranhao (Brazil) Crescent Oasis (ะกhina) Oasis Herรฐubreiรฐarlindir (Iceland) Ubari Oasis (Libya) Oasis Gaberoun (Libya)

Oasis Turpan (China) Oasis Timi, Sahara Desert (Niger)

Oasis Huacachina (Peru)

Oasis Chebika (Tunisia)

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Global Landmass Overview

Oases are usually found in areas such as Deserts

2/3 of the earths surface is covered by water.

Of the remaing 1/3, 1/3 of this is covered by Desert.

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What Is A Desert ?

< 250mm

A desert is defined as an area of less than 250mm of annual precipitation.

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How A Natural Oasis Forms ?

Aquifers supply most oases. These are created by water getting trapped above the bedrock and so being unable to drain away.

In some cases, a natural spring brings the underground water to the surface.

The water rises until just below the surface before evaporating in the extremely hot desert conditions.

Strong winds / sand storms shift sand across the desert revealing these bodies of trapped water.

176 Oasis Theory and Research

Birds drink from these pools and excrete around the edge creating fertile ground full of undigested seeds.

The seeds grow creating vegetated space within the barren desert

The space becomes an epicentre of life with desert

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Oasis Civilisation Evolution If the area is big enough an oasis can support human life. This may begin as a marker or rest point on a trade route and gradually evolves into an inhabited area of human life.

Travellers Routes Though The Desert

Camel Herders

Trade routes open up and the flow of travellers increases 178 Oasis Theory and Research

Travellers begin to setup camps along routes

The Camps become more permanent settlements

The settlements develop into villages and later grow into towns Oasis Theory and Research

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180 Oasis Theory and Research

Dunhuang Case Study Location Maps

Dunhuang

China

Dunhuang district Dunhuang

Dunhuang

Dunhuang Dunhuang Oasis

Dunhuang Oasis

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Dunhuang Context

The Oasis has an area of approximately 0.0066 sq km and the surrounding inhabited area covers approximately 0.0677 sq km.

Early Buddhist monks arrived at Dunhuang via the ancient Northern Silk Road. A small population of monks still populate the space. However it is now a tourist destination for 1000â&#x20AC;&#x2122;s of sightseers a year.

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Fortification And Trade Of Dunhuang

Dunhuang became one of the Four Frontier garrison towns established by the Emperor Wu. Dunhuang played an important part in the Silk Road trade route.

Silk, lacquer-ware and porcelain were abundant in the east and much valued by the West.

In turn, the Mongols and Chinese received large amounts of luxury goods from Europe.

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The Great Wall Of China Extended To Dunhuang

Dunhuang

China

The Great Wall Of China Line of fortified beacon towers stretched westwards into the desert

By the second century AD Dunhuang had a population of more than 76,000 and was a key supply base for caravans that passed through the city: those setting out for the arduous trek across the desert loaded up with water and food supplies, and others arriving from the west gratefully looked upon the mirage-like sight of Dunhuangâ&#x20AC;&#x2122;s walls, which signified safety and comfort.

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Silk Road Trade Route Dunhuang Changâ&#x20AC;&#x2122;an

Russia Europe

China

Kashgar

The Great Wall Of China

Pamirs Merv Damascus

Roman Empire 13th Century, trading along the Silk Road peaked in the Mongol Empire allowing trade in the region to flourish.

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Water Depths 1960’s

Maximum 7.5 m

Average 4-5 m

1990’s

Maximum 1.3 m Average 0.9 m

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2006

The local government intervened and began artificially filling the oasis to support the surrounding environment.

Fixed 1.5 m

Alternative 2015

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188 Oasis Theory and Research

Huacachina case study Location Maps

South America Peru Peru

Ica

Ica

Huacachina Oasis

Huacachina

Huacachina Oasis

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Huacachina Context

The Oasis has an area of approximately 0.025 sq km and the surrounding inhabited area covers approximately 0.125 sq km.

The area has a permanent population of approximately 95 people.

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The Oasis became famous during the 1920-50â&#x20AC;&#x2122;s. Wealthy people from all over Peru came to soak in the waters of the oasis, which were considered to have medicinal properties.

200,000 tourists per year come to see the sights, soak in the oasis, sandboard, drive dune buggys and visit the wineries.

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Water Depth 1940’s-50’s

Maximum 11 m

Average 7-8 m

1990’s

Maximum 2.5 m Average 1.7 m

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2008

The local government intervened and began artificially filling the oasis to support the surrounding environment.

Fixed 2 m

Alternative 2015

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194 Oasis Theory and Research

Kabr Aun Oasis Case Study Location Maps

Libya

Awarbi Africa

Libya

Kabr Aun Settlement Kabr Aun Awarbi Awarbi Region

Kabr Aun Oasis

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Kabr Aun Oasis Context

The Oasis has an area of approximately 0.90 sq km and the surrounding inhabited area covers approximately 0.09 sq km.

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The area had a permanent population of approximately 6000 people.

The Bedouin people lived off the land and the oasis for hundreds of years.

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They were moved in the 1980s to a settlement of concrete apartments outside the sand dunes in the Wadi Bashir. This was a government intervention to protect the oasis from the increasing Bedouin population.

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Land Use And Water Depth

Prior to resettlement the land surrounding the oasis had been used for agriculture to support the Bedouin population

Average 2.5 m

The average depth of the Kabr Aun Oasis has remained relatively constant

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200 Oasis Theory and Research

Bahariya Case Study Location Maps

The Nile Egypt Bawiti

Africa Egypt

Bawiti City

Bahariya

Bahariya Oasis Bawiti

Bahariya Oasis

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Bahariya Context

The Oasis has an area of approximately 65.0 sq km and the surrounding inhabited area covers approximately 2.40 sq km.

The area had a permanent population of approximately 27000 people.

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A Greco-Roman necropolis known as the â&#x20AC;&#x2DC;Valley of the Golden Mummiesâ&#x20AC;&#x2122; was discovered in 1995

In the last 100 years Carcharodontosaurus and Bahariasaurus dinosaurs have been found in Bahariya, which date to about 95 million years ago.

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Bahariya has always been predominantly an agricultural area however during its history the surrounding area was found to be rich in iron ore which has attracted many new settlers. The area is now know for its agriculture but also as a tourist destination due to the discovery of tombs and dinosaurs remains.

In the early 70â&#x20AC;&#x2122;s the asphalt road connecting Bahariya to Cairo was finished. With the new road came phone lines, electricity, cars, and a more accessible route to Cairo which has resulted in an increase in trade.

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Water Depth

Average 5 m

Average 11.5 m Average 22.5 m

The average depth of the Bahariya Oasis has remained relativly constant within its three troughs

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Civilisation Theories

That Apply to oasis civilizations

Oasis Theory Raphael Pumpelly

Proposed in 1908. Due to drought, both humans and animals converged close to oases. It was there that animals were first domesticated and seeds were planted.

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Demographic Theory

Carl Sauer

Proposed between 1889-1975. The increase in human population is hampered by the carrying capacity of the natural environment in supplying food.

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The immediate obvious starting place when trying to decipher spatial and carrying capacity rules was the water any specific oasis held. Priorities included the ability to break down and analysis hydrological cycles within extreme desert terrains. We investigated how limited amounts of water could be more effectively utilised and how pressure, water flow and underground strata affected the locations of oases.

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Fluid Dynamics Fluid flow Initial precipitation source

Initial precipitation source

Resultant flow 210 Oasis Theory and Research

Initial precipitation source(s)

Resultant flow

Fluid Dynamics Fluid vector analysis

Zero precipitation source

Few precipitation source(s)

Several precipitation source(s)

Many precipitation source(s)

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Fluid Dynamics Terrain and Strata

Lofted terrain generation

Multiple layered strata

Setting levels of opacity to the strata layers

2 finished layers creating a unconformity within the terrain

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Fluid Dynamics Impermeable surfaces and hydrolgolical pressure

Identify surface for flow to originate

Produce a series of source points for flow to begin

Each line plots a water course based on terrain and pressure

When enough water is collected it forces its way upwards and when it reaches the desert surfaces forms a oasis

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Fluid Dynamics Oasis generation

Flow begins from source points with lowest pressure

The flow begins to react to the terrain

The flow had completely changed direction

The flow has saturated the space between layers

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The collection of water is forced upwards

The source has finally stopped and the oasis has begun to form

The water is continued to be forced upwards towards the desert surface

The flow has generated an Oasis

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Fluid Dynamics Oasis force analysis

Identification of contours

Generation of reactive surface based on the contours

Random generation of source points each with an up thrust vector based on hydrological pressure

The water is forced to change course to eventually reach the surface

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The water is forced to a confluence point underground

The flow meets at a confluence where the pressure is at it highest

The water is continued to be forced upwards towards the desert surface

The flow has generated an Oasis

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Fluid Dynamics Dunhuang case study Flow analysis

218 Oasis Theory and Research

Identification of contours

Generation of reactive surface based on the contours

Generation of interactive surface for flow dynamic study

The flow reacts to the terrain to highlight pressure areas and ultimately shows where the Oasis is formed

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Fluid Dynamics Huacachina case study Flow analysis

220 Oasis Theory and Research

Identification of contours

Generation of reactive surface based on the contours

Generation of interactive surface for flow dynamic study

The flow reacts to the terrain to highlight pressure areas and ultimately shows where the Oasis is formed

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Fluid Dynamics Kabr Aun Oasis case study Flow analysis

222 Oasis Theory and Research

Identification of contours

Generation of reactive surface based on the contours

Generation of interactive surface for flow dynamic study

The flow reacts to the terrain to highlight pressure areas and ultimately shows where the Oasis is formed

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Fluid Dynamics Bahariya case study Flow analysis

224 Oasis Theory and Research

Identification of contours

Generation of reactive surface based on the contours

Generation of interactive surface for flow dynamic study

The flow reacts to the terrain to highlight pressure areas and ultimately shows where the Oasis is formed

These case studies prove that the computational study we have performed correctly approximates the location and scale of any given Oasis.

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After defining relationships between energy cycles and oasis formations. The micro-ecosystem that develops became the next investigated strategy. We developed and applied a cellular based digital system that approximates a biological agent to obtain behaviour, growth and development characteristics. This enabled us to progress onto the final strategy after resources and time. Space. We plotted and identified trends to generate a digital tool to produce a more efficiently and holistically sustainable Oasis environment.

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Cellular Automata Cellular based system

Stage 1 Object: To progress from A to B

Stage 2 the automata has influenced each neighbours cell.

Stage 3 the cellular pattern progresses one step closer to B

Stage 4 the cellular pattern has reached B in 4 stages. It has effected 24 cells.

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Inactive cell

Dead cell

Alive cell

Active cell

Cellular Automata Agent based system

Stage 1 Object: To progress from A to B

Stage 2 the agent based system can react to any cell and calculates a minimum pathway

Stage 3 the agent based system progresses towards B with the option to influence any cell, not just its neighbouring cells

Stage 4 the agent based system has reached B in 4 stages.

It has only effected 4 cells

Inactive cell

Dead cell

Alive cell

Active cell

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Cellular Automata Grid definition

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Square grid (1 node has 4 neighbours)

Triangular grid (1 node has 3 neighbours)

Rectilinear grid (1 node has 4 neighbours)

Hexagonal grid (1 node has 6 neighbours)

Cellular Automata Neighbour interaction

Square grid (1 node has 4 neighbours)

Triangular grid (1 node has 3 neighbours)

Rectilinear grid (1 node has 4 neighbours)

Hexagonal grid (1 node has 6 neighbours)

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Cellular Automata Iterative patterns

Square grid (Completed coloured iterative pattern)

Triangular grid (Completed coloured iterative pattern)

Rectilinear grid (Completed coloured iterative pattern)

Hexagonal grid (Completed coloured iterative pattern)

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Cellular Automata Random true/false sampling

Hexagonal grid (10% true ratio for random seed 1)

Hexagonal grid (10% true ratio for random seed 2)

Hexagonal grid (10% true ratio for random seed 3)

Hexagonal grid (10% true ratio for random seed 4)

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Cellular Automata Generation rules Generation rule 1 - 8

Resultant generation patterns

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Cellular Automata Live/Die rules and generation patterns

Version 1 (Born if false, Die if true)

Version 3 (Born if false, Die if you have more than 1 neighbour)

Version 2 (Never born, Die if you do not have a neighbour)

Version 4 (Born if you have neighbours, Die if you have 2 neighbours)

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Cellular Automata Generative predefined patterns

Orange pattern (Serpinskies triangles)

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Grey pattern (Accumulative pattern)

Cellular Automata Infinite oscillating patterns

Square pattern (Infinite block)

Triangular pattern (Infinite flower)

Rectilinear pattern (Stretched infinite block)

Hexagonal pattern (Infinite beehive)

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Cellular Automata Multiple rules combinations

Vegetation (Born if you have neighbours Cannot die)

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Generic insect experiment (Born if you have 0, equal or more oasis neighbours than competition. neighbours must die in you have neighbours)

Combined experiment (Both values of vegetation and insects are given a value of 2 if both true. If only one is true they receive a value of 1. If none are true the value is 0)

Cellular Automata Function vs analysis

Pattern 1 Multiple random source points.

Purely additive process

Pattern 2 Similar to pattern 1 just with an added death mechanic

Pattern 3 Deliberately positioned source points based around a resource. Has both life and death mechanics

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Cellular Automata Huacachina case study analysis

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T1 shows a series of sporadic source points

T2 shows some growth completely encompassing the perimeter of the Oasis Oasis Theory and Research

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Cellular Automata Huarcachina case study analysis

T3 shows a large body of cells active clustered around the source

T4 shows how a large percentage of the cells active from the previous stage have since died. The input equation applies the effect to assimilate competition between biological agents 242 Oasis Theory and Research

T5 shows a large number of newly living cells due to the significant cull that occurred during the previous timeframe.

T6 shows a large â&#x20AC;&#x2DC;swarmâ&#x20AC;&#x2122; like body of active cells. They show distinct approximation to the water source and are influenced by maximum number (carrying capacity), competition (quantity of neighbours), terrain (distance to the water source) and age (chance of survival) Oasis Theory and Research

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Cellular Automata Limiting factors within the computational process of the Cellular Automata

1

3

2

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5 4

Irrespective External factors 1. Once the input parameters have been computationally derived and the Cellular process has begun. No external factors can react to active or inactive cells and impact the resultant cellular definition.

Like like cell definitions 2. Each inactive cell that has yet not been reached but could be activated may have external influences from external source that are treated as irrelevant. These as the cellular geometry progresses could and should influence the pattern but don’t.

Predefining boundaries 3. Before the computational process is allowed to begin there are forced limits on the maximum gird size and the maximum boundary. These eventually provide/manipulate the eventual outcome as they limit its tendency to spread ‘organically’.

Variable inputs 4. Once the computational process has begun, the input resource factors cannot be changed without completed restarting/ altering the cellular outcome. For example. An Oasis in summer will have a lower volume due to increased evaporation rates. The cellular automata works by defining a relationship over time, and yet the inputs cannot change across the span.

Grid attenuation 5. Regardless of the shape or size of the input resource, the grid that provides the framework for the ‘organic’ growth is limited to orthogonal grids patterns. This leads to a Significant inaccuracy based on the orthogonal attenuation for space when meeting a curve. The inaccuracy is further extrapolated by using multiple scales.

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Why The Collected Data Can Be Compared

Desert is a title for the environmental conditions of an area thus stating that the environmental conditions these oases exist in are all similar.

41 oC

< 250 mm -18 oC Extreme temperature changes

Precipitation is Less Than Evaporation

Less Than 250 mm Precipitation per annum

The Researched case studies all exist within deserts.

This allows us to cross reference the data and form an average of life supported per body of water.

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Basin Area Of The Oases

= 77 000 m2

Bahariya Oasis

Kabr Aun Oasis

Huacachina Oasis

Dunhuang Oasis

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Use Of Space

2 400 000 m2 4%

Bahariya Oasis

28 000 000 m2 43 %

Population of 27000 people 2 800 000 m2 4% Kabr Aun Oasis

88 000 m2 10 %

425 000 m2 47 %

34 000 m2 4% 248 Oasis Theory and Research

Population of 6000 people

17 500 m2 16 %

Huacachina Oasis

36 000 m2 32 % 41 000 m2 37 % Population of 95 people 6100 m2 8% Dunhuang Oasis

8900 m2 12 %

2800 m2 4%

Population of 10 monks

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Life Supported By 1m3 Of Water Per Case Study

0.003 People

2.7 m2 of Vegetation

0.080 People

5.8 m2 of Vegetation

0.008 People

1.6 m2 of Vegetation

0.030 People

2.9 m2 of Vegetation

1 m3

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Average Oasis Life Supported By 1 m3 Of Water Huacachina and Duhuang Oases information has been removed from further calculations due to anthropogenic tourism factors

0.042 People

4.25 m2 of Vegetation

This formula can be applied to any body of water in a desert environment to estimate the quantity of life that it can support (in terms of vegetation and people). The aim of this is to assess its carrying capacity allowing for oases to be used more efficiently and so reduce the effect of the demographic theory.

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Life supported by finite quantities of water

Area x Depth / 3 = Volume of water

/2

Water = Population + Population in terms of Vegetation

From our research we have deduced an equation that with an input of ‘w’ volume of water (the volume of water in an oasis) an oasis can support ‘p’ number of people which need ‘b’ amount of area to live and ‘v’ amount of vegetation to live off.

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Generic Oasis A case study

165m2

Plan

123.75m2 Total water volume = 240m3 Average water depth = 2m Area = 160m2

165m2 123.75m2

Isometric

Total water volume = 240m3 Average water depth = 2m Area = 160m2 Built Up Area Vegetation Area Water Area Oasis Theory and Research

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Appendix

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Urbanism Conclusion

Sam Hayes and Jan Harmens

We thoroughly enjoyed the Urbanism project. It challenged us to look at a site in a very informative way. The brief was to analysis and evaluate a micro ecosystems for human requirements without a human perspective. Gathering initial information and following a logical process to determine an in-depth logistical and characteristic build up of site specific constraints.

The micro ecosystem we were given was Oasis. We previously knew very little about these climates but were extremely keen to delve into their location generation, lifespan, uses and extremely niche site specific situations.

We split the workload up and created a plan to analysis the research. There was a steep learning curve as we each presented and taught each other the relevant information we had learnt on a weekly basis. This was an extremely productive method as it allowed us to digest small sections of information with ease. This process passively questioned the progression of information. This investigation into the thought process that led from stage to stage allowed us to cover a huge range of information with relative ease.

This process to segment the work allowed for those not covering that specific topic to critique each other without bias. This self editing system worked well and created a sophisticated and more holistic piece of group work that we had equally contributed too.

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Each individual withdrew a set of rules from the initial research then investigated a computational process to impliment and define these rules in a urban strategy that could be analysed. In order to consolidate the accuracy of the systems we had developed we chose a series of case studies. We then referenced the systems against the real case studies to determine the validity. Pros and cons of systems could be easily determined and as we had used parametric software that could easily redefine the rules. These rules underwent a series if developments which allowed for a more accurate urban strategy to be formed.

The result of our research concluding in a mathematical formula that can help analyse and more sustainably use a finite amount of resources. Although it provides some level of accuracy there are inevitable inaccuracies within the informational process itself.

Sam’s Reflection

Jan’s Reflection

The project was split into several small group, pairs, which I feel worked really well. The smaller the group the easier it was to distribute workloads and create comprehensive pieces of concise well informed work. Each smaller group was then asked to contribute thier work to an overall book and there was a significant number of problems ranging from; conversion of works from multiple operating systems, multiple layouts, file compatibility hardware issues with different versions of similar software. There was a plan to collectively create a base format but as such a diverse range of formats where generated a final issue was never produced. This resulted in multiple groups reformatting and or adapting work. If this process was to be repeated I would like to see enforced deadlines with repercussions at interim stages to regiment the completed output.

Following on from Sam’s I agree with his points though feel that the quantity and quality of work should have been better regulated as the number of pages each group submitted differed significantly initially.

Compatibility issues affected all groups. For example; different versions of InDesign changed text and also working between Mac and PC contributed further complications when compiling different groups chapters.

Decisions upon the final output I believe should have been more demographic and once one part was decided upon should have been fixed.

Considering these issues I am still very pleased with the final output and believe the output, book, successfully represents our portfolio for this project.

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