The Forest City {
} How can we transform the current anthropomimetic into a biomimetic city?
Faculty of Technology, Design and Environment
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Name of student: Rada Daleva Student number: 18041665 Module number: ARCH6008 Module name: Dissertation Module leader: Philip Baker Title of work: The Forest City: a step towards transforming the anthropomimetic into a biomimetic city Date of submission: 25.01.2021
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Contents
{ Preface
p.6
;
}
{ Definitions
p.7
;
}
{ Abstract
p.8
; }
{ Methodology
p.9
; }
{ Introduction
p.10-11
; }
{ Cahpter
1
p.12-13
; }
{ Cahpter
2
p.14-15
; }
{ Cahpter
3
p.16-19
; }
{ Cahpter
4
p.20-21
; }
{ Cahpter
5
p.22-25
; }
{ Cahpter
6
p.26-35
; }
{ Conclusion
p.36-37
; }
{ Bibliography
p.38-43
; }
{ Appendix
p.44-47
; }
The Anthropomimetic city model
Towards a Biomimetic city model
A Forest City
The place of the human in a Biomimetic city
The place of technology in a Biomimetic city
Forest City algorithm
5
Preface We, humans, are the spectators of and participants in the current environmental, health, economic and political crises that are shaking the world we live in. Architects, however, hold the key to preventing those disruptions overtake the development of our civilization. They have all the means and tools necessary to lay the foundations of a sustainable future and adaptable cities, however, what I argue, is that they lack a development plan and buildings lack communication. This dissertation advocates for taking a step forward towards a systematic action that will change the fundamental model upon which cities currently operate.
6
{
Biomimicry
“Drawing upon decades of research into biological design approaches, principles and relationships between organisms within ecosystems, biomimicry aims to identify and abstract design approaches that have developed within ecosystems over 3.8 billion years of evolution“ (Pawlyn, 2016)
} {
Biomimetics
(including ‘biomimetic design’) describes the “interdisciplinary cooperation of biology and technology or other fields of innovation with the goal of solving practical problems through the function analysis of biological systems, their abstraction into models, and the transfer into and application of these models to the solution” (Hayes, Desha and Baumeister, 2020)
} {
Anthropomimetic city
One based on the model of the human. Philosophers such as Plato and Rousseau and architects such as Leon Battista, Vitruvius and Le Corbusier based the city on the human model and developed all the socio-political systems according to the metabolic processes of the human body (Dicks, 2018)
} {
Biomimetic city
One based on the model of nature. Applying the models abstracted from biological systems to urban design (Dicks, 2018)
} 7
Abstract {
“Imagine a building like a tree, a city like a forest” (Braungart and McDonough, 2002). ;
{
Cerda (1867) and Weinstock (2010) suggest that cities are equivalent to living organisms, systems that consume vast quantities of resources such as energy and materials and expel their by-products thus generating waste and pollution, leading to the notion that urban tissues behave with a high degree of metabolic properties which makes cities consumers just like humans. Given the size of cities and their impact on the planet as the biggest consumers, it is not hard to see why the United Nations (2019) have reported that cities are responsible for 70 percent of global energy-related greenhouse gas emissions that trap heat and in turn cause global warming. However if we manage to change the model on which cities are based, the solution to climate change will reside there too (United Nations, 2019). ;
{
Forest ecosystems could help us rethink the fundamental structure of our cities (Dicks, 2018). I envision cities based on the model of a natural ecosystem, generating their own energies and materials and recycling their wastes through processes analogous to natural nutrient cycling. The rapidly changing environmental, climatic and demographic global conditions and the current health crisis due to the pandemic of COVID-19 are creating a turbulent environment that will inevitably cause a great morphological change in the urban tissue of our cities. If we accept that cities are living organisms, then Gould’s ‘punctuated equilibrium’ theory which states that forms tend to persist unchanged for great lengths of time, and undergo brief but rapid change to produce new species in response to severe changes in their environment, can act as a proof for the urgent need of providing a new model that will help design better performing cities and environments (Gould, 1986). In line with these thoughts, the European Union has taken a crucial and fundamental step forward towards tackling the current environmental challenges with the European Green Deal (European Commission,2019). By advocating a coherent collective transformation of our cities, economy and society to a more sustainable circular system, the European Union aims to target all levels of social, economic and cultural strata. As buildings are recognized to account for 40 percent of energy consumed, the EU and Member States are urged to respond to the sustainable metamorphosis by engaging in a “renovation wave” of both public and private buildings (European Commission,2019). In order to pursue this energy efficient ambition, a holistic approach is adopted and some guidelines are set. ;
{
} 8
However, I believe that the creation and implementation of a clear and coherent strategy for renovation is crucial in order to not only address the Sustainable Development Goals set by the United Nations, but achieve and even exceed the energy efficient targets (United Nations, 2015). This is an opportunity for architects to change the anthropomimetic model on which our cities are based into a biomimetic one. The following dissertation will discuss why this metamorphosis is so crucial for us as human beings and for the planet on which we reside. It will further propose a direction for the creation of such a fundamental model for future responsive and adaptive urban environments which can help us overcome the environmental crisis that we are headed to. ;
Methodology {
The methodology to be adopted for this research follows the Evolutionary Process Model for software development. ;
{
It is an approach to designing algorithms that divides the development cycle into several stages, where the outcomes of each stage serve as the foundation for the conceptual framework of the next stage(GeeksforGeeks, 2019). It is therefore allowing a more interactive approach to design which takes into consideration the user’s feedback at the end of each development cycle in order to improve and optimize its performance (GeeksforGeeks, 2019). Dividing the model into smaller parts, gives access to the user in the end of each cycle thus allowing for the better understanding of the process and the easier targeting of flaws, leading to a sustainable evolution over time. Due to the innovative nature of the system that will seek to be developed, a method which offers opportunity for constant evaluation of the stages of development has been embraced. ;
{
In order to turn the initial concept of designing a new model, which will help transform cities into biomimetic, into a coherent and comprehensive system, the evaluation criteria, proffered in this paper, is formed by the value of this algorithm to society. The outcomes from the evaluation process will form the underlying principle of the algorithm. ;
{
The evaluation is developed by a comprehensive analysis of Heidegger’s chronological understanding of the clearing. The evolution of his thoughts combined with the philosophical understanding of nature as physis, determines the proposal of a potential new method for coding the spatial distribution of trees. This new method is then employed to the development of an algorithm in C#. The outcomes of the algorithm are then applied to the territory of Sofia, Bulgaria to visually represent the underlying concept. ;
} {
The following research is the first evaluated iteration of the intended system. Therefore, flaws will be encountered along the way. However, the fundamental aim of the dissertation is to reveal the potential of those new ideas and advocate for the expansion of the scope of current research which is linking the fields of biomimicry, technology, architecture, urbanisation and human philosophy. ;
}
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Introduction Preface. Algorithm concept The dissertation begins by outlining the main concept behind the research. It reveals the twofold intentions which work in symbiosis to advocate for further investigation in the proposed direction
Software concept
Chapter 1. Anthromimetic city
Problem
This chaper will identify a fundamental, global problem which our society is facing and the solution to it is the key which will allow us to endure on our planet longer (UN News, 2019). It is argued that the issue is the inappropriate model according to which our cities were designed to operate. The development of this model is examined by performing a chronological analysis of the philosophical theories, discussing the relationship between the human and the State. The investigated texts share one main characteristic which is the identification of the human being as the perfect form for both the philosophical and physical organization of the city which leads to proving that our cities are based on an anthropomimetic model (Dicks, 2018).
Identifying a problem
Chapter 2. Towards a Biomimetic city
Solution
This chapter will propose the core of the new model which is to be developed. It advocates the use of biomimicry as an approach to discovering the mechanisms orchestrating natural processes and defines this discourse with the principles set by its founder - Jeanine Benyus. It further highlights the distinction between the current anthropomimetic model and the proposed biomimetic by emphasizing the new functionalist approach to design. It continues by stressing the important distinction between using an organism and an ecosystem as a model and it advocates the use of the latter.
Initial Proposition of System Core
10
Chapter 3. A Forest City The intricate systems that have emerged and developed in the forests over the course of billions of years will be investigated and explained in this chapter. Through a set of illustrations, a visual representation of the mycorrhizal networks that are responsible for the communication between trees, will be made.The visual argument will be followed by a theoretical concept of the application to these networks in the design of our cities.
Propose Initial Version
Chapter 4. The place of the human in the Forest City
Chapter 6. Forest City algorithm This chapter will provide the reader with a synthesized overview of the main methods for characterising and simulating the spatial patterns of trees used in Forestry. Having considered the limitations of the currently used methods, the goal of the following chapter will be to propose the core concept behind a potential new method that could lay the foundations of a new direction for further research and development of much bigger scope. The chapter is endeavoring to achieve this aim by proposing the consideration of the principle of autopoiesis as the base for the development of a new coding method. The programing language C# will be used to code an algorithm working on this principle.
Dicks (2018) raises the question of the place accorded to humans in a new biomimetic city. He proposes an answer using a speculative philosophical anthropological theory which merges Heidegger’s ontological view of the “clearing” and various anthropological evolutionary theories. The objective of this chapter is to demonstrate that Dicks’ view might be biased and limited due to his discussion only on Heidegger’s early understanding of the clearing. It will be further argued that according a place to our new neighbour - technology - is just as essential both for humans and for the functioning of the city as an ecosystem.
Refine the Model
Program Evaluation
Chapter 5. The place of technology in the Forest City The following chapter will propose technology as the new “clearing” and the solution to appropriating a place to humans in our new technological era. By following Heidegger’s later understanding of the clearing, we can recognize technology as a medium to reveal to us the essential form of being (Heidegger, 1977). Thus we will develop an open relationship to it, restricting it from taking control over us, and live in symbiosis. Once we allow technology to help us see nature as physis (Dicks, 2017) and use it to investigate the system ruling this natural process, we might be able to find a place for humans in, and a model for, the new biomimetic city.
Elicit Feedback
11
Chapter 1 The Anthropomimetic city model
12
{
The human being has for centuries been the fundamental underlying model of Western cities, although it has experienced several changes of its focus. ;
{
The anthropomimetic political and social philosophy can be emphasized through three key points which all prove that a single organism has served as a city model. ;
{
Firstly, regarding the political philosophy, the soul and mind of the human individual are mimicked and appropriated at the level of the State. This can be seen in Plato’s work relating the three distinct parts of the soul to their mimetic attributes in the State (Fine, 1999). Similarly, Rousseau’s political philosophy focuses on the analogy between the mental faculties of human individuals and their corresponding counterparts in the State, highlighted in his invocation of the individual will as a model for the general will. However, it is worth considering Rousseau’s article on political economy which, on the other hand, associates the parts of the human body to the parts of the State (Rousseau, 1987). ;
{
The second point is that despite the emergence of sociology in the nineteenth century, the anthropological model, favored by political philosophers from Plato to Rousseau, did not change to a new physiological or biological one but it rather experienced a shift in focus within the same basic model. The previous emphasis on the mind which corresponded to the activities of government and science was replaced by a focus on the body, and therefore on socio-economic activity. ;
{
}
Thirdly, human beings not only provide the form but also the matter of the traditional view of the State. This statement holds true because the philosophy which is discussed above considers a political and social community composed only of human beings. Both Plato’s and Rousseau’s States consist of human beings, not things. Likewise, in Comte (1995) and Durkheim’s (1893) work, the parts of the social organism, which according to them correspond to the parts of the biological organism, are all different categories of people. ;
Later on, the model of the city shifted from the human mind to the human body. According to the French urban historian Françoise Choay (1974, p.247), this transition was brought about by the “scandal of homo artifex” which poses the question of what form should humans follow when building because unlike other living organisms they don’t have a predetermined by Nature path to follow and therefore they should establish their own laws of construction. Choay’s (1974) explanation is that the form of the human body is the most perfect creation of Nature, combining fundamental attributes of all the various different spheres of creation. The result was a new approach to the planning and design of cities that would dominate Western architecture for hundreds of years. ;
} { }
By analysing different philosophical theories, it can be concluded that the basic model for the design of our cities is the human form and being. This model, identified by Henry Dicks as “anthropomimetic” (Dicks, 2018, p.6), is the problem to which the research will seek to propose a solution or at least a possible direction. ;
13
Chapter 2 Towards a Biomimetic City How can biomimicry serve as the tool for transformation
{
Can this new discourse fundamentally change the way that our cities are functioning or will it just offer another form of the same process? The chapter will seek to answer this question by arguing that the new discourse of biomimicry can only help us transform our cities if we base our investigation on the intricate systems that are dictating the existence and organization of ecosystems rather than that of single organisms. ;
{
An aesthetic approach to building was manifested in the renovation of Barcelona which followed the perfect form of the human body. The proportions of the human body were the basis for the planar distribution of urban elements of the city as explained by Antonio Lopez de Aberasturi (Lopez de Aberasturi, 1979, p.22). On the other hand, Cerda (1867) proposed a functionalist approach to building in his General Theory of Urbanization, which according to Choay (1966) marks the beginning of the shift from anthropomimetic to biomimetic understanding of the city. Cerda viewed the city as a biological organism and dissected all its physiological functions such as digestion, circulation, consumption and evacuation of waste. This shift was in unison with Auguste Comte’s founding of sociology as a positive science which required society to be also seen as a biological organism. Later on, Janine Benyus’s Biomimicry: Innovation inspired by Nature (1997) could be considered as the work which highlighted the beginning of a new paradigm by establishing three main principles - “Nature as model, Nature as measure, and Nature as mentor” - of Biomimicry and highlighting the potential of this new discourse. Although this new discourse advocates for a functionalist approach and a new understanding of the model as a biological organism, it can still be argued that the model itself hasn’t changed fundamentally but rather the way it is viewed. If cities are to be based on living organisms by using a different approach, then there isn’t much difference from what was done in the past but rather another shift in human understanding of the same model. However, the following paragraph will aim to highlight the radical difference between the current anthropomimetic and the new advocated model that can help our cities transition into biomimetic. ;
} {
14
In order to get an insight into the breadth and potential of this new model, we can consider Braungart and McDonough’s (2009, p.139) vision of a new “city like a forest”. Their manifestation which is visually represented on Figure 2. is far more intricate and advocates for a fundamental change in the way that our cities currently operate as opposed to architect Stefano Boeri’s Liuzhou “Forest City” that merely acts as a host for various plants and trees which can be seen on Figure 1.They imagine buildings which instead of simply minimizing carbon footprint are active participants in an ecosystem and support life by being energy positive and distribute excess energy to other buildings that have not met their requirements through a similar system which trees in the forest use to pass on excess sugars to mycelium in the soil and thereby onto other trees.
{
Figure 1. Linzhou Forest City by Stefano Boeri
} {
Figure 2. Cradle to Cradle strategy- a
biomimetic approach to the design of products and systems promoting circular economy approach
}
;
Similarly, Evan Greenberg and George Jeronimidis (2013) envision cities with differentiated microclimates, finely coordinating various flows of energy and information, imitating the natural processes and the spatial two and three dimensional distribution of patterns of trees in the rainforest. This spatial logic has been developed over thousands of years through cycles of growth and decay, competition and adaptation (Greenberg and Jeronimidis, 2013). It can therefore be extracted and developed as a model for cities which are capable of generating dynamic spatial and cultural effects through sectional height variation and share excess resources through intricate systems such as the mycorrhizal networks formed between forest trees. ;
} {
This potential shift of the basic model on which cities are currently based may transform them from individual biological organisms into an active natural ecosystem. Through this system, our cities can evolve from consumers to producers. ;
}
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Chapter 3 A Forest City Which forest systems can be applied to the design of our cities?
{
If we want to understand how an ecosystem functions and extract those principles to design a model , we need to take a closer look at the processes and systems orchestrating a forest. ;
{
Over 360 million years ago through the evolution of primitive plants and water algae, the first forests emerged (Benyus, 1997). Currently they cover roughly 30 percent of the earth’s land mass. Their highly complex and diversified morphological growth depends on the collection, negotiation and exchange of energy (Greenberg and Jeronimidis, 2013). Through mycorrhizal networks, the relationship between individuals is negotiated (Leake et al., 2004; Selosse et al., 2006; van der Heijden and Horton, 2009). Trees are constantly communicating with each other, competing for resources, developing stronger root systems, varying branching strategies, creating complex flow structures and developing according to their access to light and water thus forming varied environments and microclimates, accommodating a vast number of animal and plant species (Greenberg and Jeronimidis, 2013).Despite their differences, they all grow following particular mathematical models. They conform to their predetermined set of genetic rules while still allowing some particular morphological development according to specific competitive pressures (Greenberg and Jeronimidis, 2013). Through careful investigation of the mathematical and functional patterns ruling the growth and spatial distribution of trees in a forest as well as the mycorrhizal networks, through which resources are shared, we can be mentored how to design better performing and more efficient cities which are based not on a model of consumption but on production. By understanding the spatial distribution of trees we can discover how and applying this set of genetic rules to the design of cities we can generate highly performative urban organisations which are capable of sharing resources, managing flows of energy, recycling materials and negotiating growth and decay. Before we investigate the different mathematical models to which tree growth complies and propose a way of implementing them to city design, we have to understand the intricate system through which trees communicate and evaluate the place of humans if the city is to be based on the model of a forest.
{
Forest trees are interconnected through a symbiotic association with fungi, called mycorrhizae. They encompass the tips of the roots and form the mycelium through countless branching thread-like hyphae, which are illustrated on Figure 3. The mycelium spreads across a much larger area than the tree root system, connecting the roots of different trees together to form the mycorrhizal network which is also known as the Wood Wide Web (BBC News, 2018). Through this network, fungi can pass resources and signaling molecules between the trees. Since fungi are unable to photosynthesize, they trade nutrients and water, especially phosphorus and nitrogen, for photosynthate (Simard, 2016). Professor of forest ecology Suzanne Simard (2016), who is also responsible for the advanced discoveries related to mycorrhizal networks, states that this very system is responsible for the impeccable functioning of forest ecosystems. The communication between trees, realized though mycorrhizal networks, is the key to the longevity and adaptability of the forest (Simard, 2014; Klironomos et al., 2011; Van der Heijden et al., 1998).
16
Figure 3. Diagramatic representation of mycorrhizal networks
} {
This dissertation will aim to take a step forward towards proposing a way in which we can implement this system to our cities. This constant communication and exchange of resources and information, is what our buildings currently lack. Therefore this dissertation will aim propose a way in which we can implement this system to our cities.
}
17
The first step of a growing forest
Trees are slowly growing and
As trees continue to grow,
1stand
2developing root systems
3their roots become bigger and
take a closer look between 4 Let’s the trees
we understand how trees 5Can communicate if we go in the
secret to their success, 6The lies under the ground
The vast root systems hold
7the key to the answer 18
forest?
Let’s take a closer look at
8those roots
spread wider
We can notice that symbiotic
9fungi are partnering with the roots
10
They are trading sugars for nutrients
11
The roots have countless branching thread0like hyphae
12 branching thread-like hyphae
The roots have countless
13
The mycelium spreads along a much larger area than that of the tree roots
14
Through the mycelium, connections between different trees are formed, comprising the mycorrhizal networks
15 networks, fungi can pass
16
Both the trees and the fungi benefit from exchanging resources thus forming a symbiotic relationship
17
Trees which grow in the shade and have less opportunity for synthesize receive shugars from older trees
18 system works
that form the mycelium
Through mycorrhizal resources
This is how that wonderful
19
Chapter 4 The place of the human in a Biomimetic City {
After the initial version of the model was proposed, this chapter will evaluate it by examining its possible effect on humans and society. It was established that the model for turning cities into biomimetic, which is to be later developed in this dissertationfor, will be based on forests and more specifically, on the systems that enable the communication between trees and the exchange of resources. However, this raises the question of the place of the human in the new city based on a forest ecosystem, since cities were initially developed through the process of clearing forests in order to dwell in open spaces. Through Heidegger’s later understanding of the clearing, a new place will be accorded to both humans and technology. ;
{
20
According to Dicks, Heidegger sees the clearing as “the open region for everything that becomes present and absent” (Heidegger, 1993, p.442). Dicks argues that for Heidegger the clearing is the space in which humans use their unique ability of understanding the Being in order to become present and see themselves as - as other humans, as animals, as Gods etc. In other literature writings it is widely assumed that the clearing in the forest is a metaphor used to describe the uniquely human ability to realise the as(Capobianco, 2010; Sheehan, 2015). It is believed that the clearing can, in particular, describe the spatiality of this human understanding. However, Dicks argues that by using contemporary interpretations of human evolution, it can be proven that the forest clearing can be a rather insightful description of the “there” which is seen as the space where the as reveals and realizes itself (Heidegger, 1993, p.442). According to both French paleo-anthropologist Pascal Picq(2009) and Hublin (2008) the driving force behind human evolution was the deforestation of tropical forests and the need for living in open environments. Due to a transition from the previous anthropomimetic model of the city - based on the human - to the new biomimetic - based on a natural ecosystem - there has to be a change in human self-understanding and a new place for humans in the biomimetic city. Dicks (2018) is proposing that using Heidegger’s ontological thinking of clearing, humans should see themselves not as “composites of an animal body with a human mind” but rather as “former forest-dwellers who have come to dwell in open environments and who, in doing so, have ultimately acquired an open relationship to Being, hence the possibility of conceiving States as “artificial men,” societies as “organisms,” cities like “forests,” and so on and so forth” (Dicks, 2018, p.14). Thus Dicks (2018) believes that by changing the traditional distinction between the body and the mind to an opposition between the forest and the clearing, the human would accord himself a new place in the biomimetic city. However, I will argue that his point is rather limited as it considers only Heidegger’s early understanding of the clearing. It further leaves out a new species - technology- that also needs a place in our biomimetic cities if they are to resemble ecosystems. ;
{
The concept of the clearing is probably the most prominent in Heidegger’s philosophical career (Schatzki, 1989). His whole philosophical career revolves around understanding the nature and constitution of the realm of illumination in which entities can reveal themselves to people, or what he called the clearing. When investigating his earlier writings, one can discover that the clearing is identical with human existence and that the light which constitutes the clearing can be related to human understanding. However, in his later career, Heidegger doesn’t identify the human understanding with the clearing (Schatzki, 1989). “The light in whose illumination things can manifest themselves to us is something distinct from human understanding and existence, and the latter are now viewed as that by which we apprehend (in Heidegger’s language, are “open for”) this light and what appears in it” (Schatzki, 1989, p.13). It can be seen that there is a shift in the concept of the clearing and perhaps the human understanding of clearing is also developing as the human itself is evolving. We will further discuss what this shift might be and how we can use it to appropriate a place not only to humans but also to technology. ;
} }
21
Chapter 5 The place of technology in a Biomimetic City {
If we recognize technology as clearing, it can reveal to us the essential form of being. Once we allow technology to help us see nature as physis, we might be able to find a place for human, nature and technology to live in symbiosis in the new technological era. ;
{
In order to understand the importance of accepting and benefiting from the role of technology in our future cities and society we need to start by defining technology. Technology can be described as means to an end or a human activity (Lovitt, 1977). In this dissertation, technology is considered as both. The word “techne” was linked to the word “episteme” both meaning knowing in the widest sense (Lovitt, 1977, p.13). They further carried the sense of being entirely at home in something, fully being aware of it and even an expert in it (Lovitt, 1977). This knowledge provides an opportunity for opening up, a mode of “revealing” (Lovitt, 1977, p.13). The distinction between the two was stated by Aristotle and it was manifested in the distinction between the ways in which techne and episteme reveal(Parry, 2003). Techne reveals what is yet to be discovered, that which does not come forth and does not yet lie before us. It represents the envisioning of the construction process and the end product in order to choose the right tools needed, rather than the manufacturing process itself. ;
{
What we already discussed about the clearing can be synthesized as the understanding of being. We don’t produce the clearing, but on the contrary, it produces us. Thus described by Heidegger the clearing is: “Beyond what is, not away from it but before it, there is still something else that happens. In the midst of beings as a whole an open place occurs. There is a clearing, a lighting. . . . This open center is . . . not surrounded by what is; rather, the lighting center itself encircles all that is. . . . Only this clearing grants and guarantees to human beings a passage to those entities that we ourselves are not, and access to the being that we ourselves are” (Heidegger, 1936, p. 53). ;
{
Therefore in a sense the clearing defined by Heidegger can be seen as a mode of revealing the way of being to humans. If we accept that both the clearing and technology offer a mode of revealing to humans then what kind of relationship do they have? What is the essence of technology and the technological understanding of being as well as the technological clearing? To start with, Heidegger doesn’t have clear answers to those questions. According to him, technology is as old as civilization and it can be precisely defined as a “means” and a “human activity” (Lovitt, 1977, p.4). However he believes that this definition is merely instrumental and anthropological and when discussing the essence of technology and the technological understanding of being, Heidegger believes that it is something new and distinct. For him, modern technology seeks constant optimization only for the sake of efficiency. ;
22
Although he finds flaws in modern technology, he doesn’t oppose or attack it. He confirms that technological devices challenge us to achieve even greater advances and proposes a way in which we can use the benefits of technology to reveal the potentials of the future development whilst staying true to ourselves (Lovitt, 1977). In order to understand how to strike the balance between benefiting from the new technological devices whilst denying their dominance over us, we need to discuss Heidegger’s important distinction between technology and the technological understanding of being. Once we recognize our essential receptivity that technology is our latest understanding of being, we can escape our restricted understanding of being as a form of efficient enhancement. This transformation in our sense of reality is precisely what Heidegger describes as the answer to freeing ourselves from the dependence upon technology (Lovitt, 1977). Once we set ourselves free from the technological imperative, we will stop our compulsion to force everything into one efficient order and rather give this task to technology. This realization can allow us to get the right relation to technology - recognizing it as clearing. Heidegger also sees that this recognition can be the answer to finding our new place in the technological era which can be seen in the following quote:
{
“That which shows itself and at the same time withdraws [i.e., the clearing] is the essential trait of what we call the mystery. I call the comportment which enables us to keep open to the meaning hidden in technology, openness to the mystery. Releasement toward things and openness to the mystery belong together. They grant us the possibility of dwelling in the world in a totally different way. They promise us a new ground and foundation upon which we can stand and endure in the world of technology without being imperiled by it.” (Heidegger, 1966, p. 55). However, we can notice that Heidegger believes that this gift of new understanding of being can only “promise” us a “possibility” of ”dwelling in the world in a totally different way”. This means that the releasement towards the mystery can offer us a new vision of rootedness that might be able to transform the current disappearing rootedness into a new essential form. ;
} {
I will further proceed to argue that seeing technology as clearing or the space which reveals to us the new form of being might help us unfold and realise one of the things which differentiate us from other living organisms. As mentioned earlier, humans, unlike other living forms, don’t have predetermined laws of building and are therefore free to choose how to construct. Françoise Choay (1974) saw the human body as the perfect model for construction as the most complex creation of Nature. ;
23
{
However, as previously mentioned, this dissertation will continue by arguing that a biomimetic model is better suited for our future cities that should aim to take an active part in the regeneration of our environment rather than its destruction. I will follow Dicks in his argument which defines Nature as physis or “self-production” thus constituting the requisite ground for the main principles of biomimicry defined by Janine Benyus and expand the scope of his concept by proceeding to argue that if we see Nature as physis, we, humans, will discover our new form of being and building the new essential model that will help us endure in the world of technology without being imperiled by it. ;
{
The contemporary view of biomimicry starts to narrow down the potentials of biomimicry by reducing Nature to a sort of database or a catalogue which offers us tested design solutions. This understanding of Nature is further encouraged by websites such as asknature.org. In order to counter this problem, Janine Benyus has developed a canon of laws, strategies, and principles which she believes dictate the fundamental ways in which Nature works. These main principles which she outlines in the beginning of her book - Nature as model, Nature as measure, and Nature as mentor - set the tone for a new philosophical discourse of biomimicry. Although their value for the biomimetic discourse is undoubted, the principles are rather descriptive instead of explanatory. They describe the laws of Nature rather than the nature of Nature. Freya Mathews (2011, p.368) recognizes those limitations and aims to expand the theory by proposing two new principles which she considers fundamental and distinctive of Nature: the “principle of least resistance” and the “principle of conativity”. They are both connected and propose that living organisms fulfill their will to “maintain and increase their own existence” through the “path of least resistance” (Mathews, 2011, p.368). What she calls conativity is referred to as autopoiesis in recent systems theory. By agreeing with Mathews and considering Nature as autopoiesis there is a scope for constituting a suitable ground for biomimicry. However, the autopoiesis that will be discussed and used in further arguments differs from Mathews’ position. The self-production is not seen as a will and the concept can apply to other non-biological entities such as stars and ecosystems (Maturana and Varela, 1980, 85-87). By expanding the theory of autopoiesis beyond the realm of biology and to the one of ecology, the notion of the trophic cycle has come to light. Both Lynn Margulis (1995) and Fritjof Capra (1997) have discussed the idea that nutrients circulate between producers, consumers and decomposing organisms. This notion supports Barry Commoner’s (1971) view that the emergence of these closed trophic loops is precisely what sustains life on earth. ;
{
Furthermore, not only biological and ecological systems can depend on autopoiesis. Physical systems are just as much self-producing and through investigating this exact process, Morin (1977) sets out with the intention to discover the nature of Nature. ;
24
He, however, referred to autopoiesis as “physis” and believed that it can be seen in both living entities and nonliving which also exhibit such dynamic circular organization. He further states that if it wasn’t for self-production, there would be nothing but chaos. How can this view of Nature as physis help us expand the current biomimetic discourse and see Nature as a model for cities that will let beings be? Firstly, this allows us to look beyond the etymological boundaries set by the word “bio-mimicry” and view Nature not only as a source of inspiration but as life - as autopoiesis or self-production. By following the specifically ecological form of self-production - the sharing of excess resources and recycling of nutrients in trophic loops - we can transform the “linear, self-destructive course” of our economy (Commoner, 1971, p.299) to a circulating, renewable one. ;
}
}
Thus, by expanding the concept of biomimicry and using technology to investigate the complex systems dictating the ecological physis, we can simultaneously free ourselves from the technological imperative by appropriating a place for both human and nature, and discover a new model for the redevelopment of our cities. ;
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Chapter 6 Forest City algorithm { {
In Forestry, although there are various interpretations, two main methods of sampling are used in the analysis and prediction of forest stands’ growth and spatial distribution (Diggle, 1983). Both methods will be briefly examined in order to grant the reader basic understanding of the currently available different methods. Although both methods have proven to give reliable estimations, the real algorithm behind the distribution of trees is much more complex and has not yet been fully discovered. The first one is called fixed-area plot and is associated with Poisson forests. Thereby the reliability of the data as well as the outcome varies according to the selected sample plot. The second one is distance sampling which uses as its sampling unit a point and performs simulation according to the provided information for neighbouring events (Diggle, 1983). The latter yields more detailed information regarding the exact location and distribution of individual trees whilst the former is more effective when analysing the type of forest stand (Stamatellos and Panourgias, 2005). However, none of the methods considers the different layers of three dimensional density within the forest that comprise various species which form its stratum. The spatial distribution of trees further reflects the microenvironmental differences, access to sunlight, competing vegetation and the individual characteristics of different species that inform their ability to endure and withstand various environmental conditions thus forming the forest mosaic (Benyus, 1997). Therefore this dissertation recognizes the limitations which those methods face by relying on mathematical models that work on the principle of randomness to describe a non-random process.;
{
Although there are various different interpretations of the main methods for recording and analyzing data related to the spatial patterns of forest trees, to my knowledge, the simulation is always dependent on the Poisson distribution. The model works on the basis of a fundamental assumption of randomness. ;
} {
26
Stamatellos and Panourgias (2005) have attempted at simulating the spatial distribution of forest trees by using data from common forest inventories. Having analysed various methods of spatial distribution simulation, the Poisson cluster process proved most suitable for the purpose of their research which is to enable a more effective future management of the forest stands. The adopted fixed area plot sampling method provides an adequate approximation of the cluster patterns which proved to be a useful tool for forest ecosystems managers (Stamatellos and Panourgias, 2005). ;
Characterizing the spatial distribution patterns of trees can reveal insightful information about the forest’s history and underlying biological processes that have formed it (Moeur, 1993), thus contributing to the generation of more effective forest management strategies. However, the method used faces three significant limitations. First, the outcomes and results are dependent upon the sample plot’s size (Stamatellos and Panourgias, 2005), which may yield misleading information, unless the selected sample size is big enough, which is rarely the case. Second, despite being useful when defining the spatial model of trees (random, clustered or regular) (Pielou, 1960), this method is unable to identify the exact tree location. Last but not least, the main assumption upon which the spatial simulation is dependent, can be argued as inaccurate when attempting to simulate an ecosystem. According to Stamatellos and Panourgias (2005, p.311) the assumption made is that “the locations of trees are generated by some underlying random mechanism”. Here the word “random” is key as the results yielded by the Poisson distribution model are dependent on this very assumption. On the other hand, Janine Benyus (1997) argues that nature builds following very precise algorithms which have been developed and tested over the course of 3.8 billion years and assuming that the spatial distribution of trees in a forest is a random process might be seen as an act of ignorance. ;
{
Having considered the aforementioned factors which limit the first method, this dissertation will continue by investigating the second method for spatial pattern analysis and simulation. Both point processes and marked point processes are accurate and reliable methods for forest stand simulation, offering exact tree location (Panttinen et al., 1992; Gavrikov and Stoyan, 1995; Stoyan and Penttinen, 2000). In particular, the nearest neighbour cumulative distribution function, proposed by Ripley (1977), will be analyzed. The nearest neighbor analysis is based on a probability density function for d, which stands for the distance from an arbitrary point (in our case, a mapped tree within a given study plot) to its nearest neighbour. The basic process used to generate the tree locations, however, is again Poisson. The area which is encompassed by a circle with a center tree i and radius di and equals the distance to the nearest neighbouring tree, is a random variable, independently and identically distributed with exponential density:
represents the intensity of trees on the plot. stands for F(d), which is a cumulative distribution function defining the probability that a nearest neighbouring tree i is within distance d of a specified region of area. F(d) is obtained by integrating the following probability density function: Therefore both models share one significant disadvantage which is their fundamental assumption of randomness. This triggered my intention to start a discussion and the development of a new algorithm which operates according to the fundamental natural principle of autopoiesis. The method is dependent upon the notion of physis which was previously discussed. What I believe we should understand in forests is this process of self-production of trees and their relationship to each other. Therefore the algorithm developed is based on this very intention. It is not fully developed but it is starting a discussion of how can this knowledge, using technology allow us to open for the regeneration of our cities. ;
}
27
{
The concept of autopoiesis is essential in the field of biology, substantially aiming at providing an integrated characterization of the very nature of living organisms, offering a clear distinction from a mere listing of arbitrary properties. The first significant contribution to this field was made by Humberto Maturana and Francisco Varela (1947). They studied autopoietic systems and proposed a computer model, working in two dimensional discrete space. This algorithm proved that the complex concept of autopoietic organization can relatively easily be simplified and visualized with the help of technology. Although several flows have been discovered later, the algorithm proved to be a concrete example of the concept of autopoiesis (McMullin and Varella, 1997). The algorithm represents the dynamic interactions that occur between particles based on discrete timesteps. There are three distinct particle types - the substrate (S), catalyst (K) and the link (L) which engage in three different reactions (McMullin and Varella, 1997). The algorithm represents the whole process of chemical reactions which lead to the formation of a bond. However, the algorithm which is developed in this dissertation aims to represent only the already formed bonds in two dimensional space. ;
{
The algorithm itself will not be explained in detail as the results, which it yields, are not exact due to the very limited initial data provided and currently the algorithm distributes the points in a linear manner rather than radial. We will rather focus on the concept behind it and the principle on which it is based. It is designed in such a way so that it starts by giving you the choice to enter the region for which this simulation will be applied, in meters. It is then providing the user with the opportunity to pick one out of four different patterns which represent the mean distances between the trees in Vitosha forest and the data is taken from the Bulgarian Forestry association. Once the pattern is chosen, the program automatically generates the x and y coordinates of the tree locations in two dimensional space. Every yielded result will be unique as the position of each tree depends on that of all of the previous ones. The algorithm is thus simulating the spatial distribution of trees in the forest by oversimplifying the autopoietic process but it advocates the need for further development and research in this particular field and its application to urban design. ;
{
An initial test was conducted which aimed at visualizing the idea behind the implication of the algorithm to the urban tissue, transforming it into a biomimetic one. Once the algorithm calculated the results,visible on the right, they were inserted into AutoCad as the centers of circles with 0.5m radius, in order to produce the spatial distribution, shown on Figure 4. These circles are then used to show the optimal location of devies that should be placed in the city which will act as a source of resources. Thus those devices can be called the “trees” of the city. Each building, after undergoing renovation under the “renovation wave” set by the European Union Commission, will be able produce its own energy and share it with its neighbours through those “tree-like resource devices”. All the buildings which have produced extra energy will be linked to the “tree-like resources”,whose proposed location is shown on pages 32-33, and pass it on through mycorrhizal-like networks, shown on pages 34-35, to the buildings that haven’t managed to produce enough on their own. ;
{
This can be the first step of how cities can be transformed into ecosystemscommunicating and sharing resources. ;
28
{
Figure 4. Data from the algorithm visualized in AutoCad
30
Figure 4. Isometric 3D model showing the proposed locations of the “tree-like resource devices” on the territory of Sofia
31
32
33
34
35
Conclusion {
In conclusion, this dissertation advocated for a change in the way that our cities currently work. Through thorough investigation and evaluation of various philosophical and urbanizational resources, the basic model according to which our cities currently work proved to be anthropomimetic. By criticising its functions as the biggest consumer of limited natural resources instead of an active producer and a participant in the natural world, the need for metamorphosis was promoted. The use of biomimicry to open for the discovering of the new model on which our cities should be based, prooved valuable to society. Thus a direction for further investigation was provided by laying the foundations of the philosophical arguments supporting the development of a biomimetic model for our cities and their transformation from organisms into an ecosystem. ;
{
The theoretical arguments were followed by an attempt at the creation of an algorithm using an innovative method, working on the principal dictating life- autopoiesis. This developed algorithm supported the vision of a city which enables the communication between buildings and the exchange of resources, by applying the principles behind the systems dictating those process in the forest. ;
{
The final part of the dissertation offered a visual representation of the idea in order to show how the simulation of the spatial distribution of forest trees, yielded by the algorithm, can be applied to identify the location of “tree-like resource devices” that will act as points for distribution of energy and information between the buildings thus resembling the very process that sustains life in the forest. ;
}
36
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Stoyan, D. and Penttinen, A. (2000) Recent applications of point process methods in forestry statistics, Statist. Sci, 15 , pp.61–78. Simard, S. W. et al. (2012) “Mycorrhizal Networks: Mechanisms, Ecology and Modelling”, Fungal Biology Reviews, 26(1), pp. 39–60. doi: 10.1016/j.fbr.2012.01.001. Simon, F. (2020) EU launches ‘renovation wave’ for greener, more stylish buildings Available at: https://www.euractiv.com/section/energy/news/eu-launches-renovation-wave-for-greener-more-stylishbuildings/ (Accessed: 06 Nov 2020) Simard, S. W. (2012) Do trees communicate. Available at: https://www.youtube.com/watch?v=iSGPNm3bFmQ (Accessed: 27 Nov 2020) Simard, S. W. (2014) The networked beauty of forests. Available at: https://www.youtube.com/ watch?v=dRSPy3ZwpBk&feature=emb_title (Accessed: 27 Nov 2020) Ritter, S. (2020) Fungal network distributes resources. Available at : https://asknature.org/strategy/ fungal-network-distributes-resources/ (Accessed: 15 Dec 2020) Rousseau, J. J. (1987) Basic Political Writings. Translated by D.A. Cress. Cambridge:Hackett Publishing Company. SCHATZKI, T. R. (1989) “Early Heidegger on Being, the Clearing, and Realism,” Revue Internationale de Philosophie, 43(168 (1), pp. 80–102. Senechal, M., Okabe, A., Boots, B. and Sugihara, K. (1995) “Spatial Tessellations: Concepts and Applications of Voronoi Diagrams”, The College Mathematics Journal, 26(1), pp. 79–79. doi: 10.2307/2687299. Senechal, M. et al. (1995) “Spatial Tessellations: Concepts and Applications of Voronoi Diagrams,” The College Mathematics Journal, 26(1), pp. 79–81. doi: 10.2307/2687299 Schreuder, H.T., Gregoire and Wood, G.B. (1993) Sampling Methods for Multiresource Forest Inventory. New York:John Wiley & Sons. Spanish Foundation for Science and Technology (2018) A genetic algorithm predicts the vertical growth of cities. Available at: https://phys.org/news/2018-05-genetic-algorithm-vertical-growth-cities.html (Accessed: September 20, 2020) Stamatellos, G. and Panourgias, G. (2005) “Simulating spatial distributions of forest trees by using data from fixed area plots”, Forestry: An International Journal of Forest Research, 78(3), pp. 305-312. doi: 10.1093/forestry/cpi028 Stoyan, D. and Penttinen, A. (2000) Recent applications of point process methods in forestry statistics, Statist. Sci, 15 , pp.61–78. Simard, S. W. et al. (2012) “Mycorrhizal Networks: Mechanisms, Ecology and Modelling”, Fungal Biology Reviews, 26(1), pp. 39–60. doi: 10.1016/j.fbr.2012.01.001. Simon, F. (2020) EU launches ‘renovation wave’ for greener, more stylish buildings Available at: https://www.euractiv.com/section/energy/news/eu-launches-renovation-wave-for-greener-more-stylishbuildings/ (Accessed: 06 Nov 2020) Simard, S. W. (2012) Do trees communicate. Available at: https://www.youtube.com/watch?v=iSGPNm3bFmQ (Accessed: 27 Nov 2020) Simard, S. W. (2014) The networked beauty of forests. Available at: https://www.youtube.com/ watch?v=dRSPy3ZwpBk&feature=emb_title (Accessed: 27 Nov 2020)
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Figure references Figure 1. Boeri, S.(2016) Liuzhou Forest City. Available at: https://www. stefanoboeriarchitetti.net/en/project/liuzhou-forest-city/ (Accessed: 21.12.2020) Figure 2. debyemm (2014) Cradle to Cradle. Available at: https://whatisnewinecomaterials. wordpress.com/2014/07/06/cradle-to-cradle/ (Accessed: 17.12.2020) Figure 3. Beiler, et al (2010) A diagram of a fungal network that links a group of trees, showing the presence of highly connected “mother trees.” Available at: https://e360.yale.edu/ features/exploring_how_and_why_trees_talk_to_each_other (Accessed: 23.12.2020) Figures on pages 18-19 Sketched by Rada Daleva from source: BBC News (2018) How trees secretly talk to each other. Available at: https://www.youtube.com/ watch?v=yWOqeyPIVRo&list=PLEebob7K2Mdj4wzronMzoNvC3RIdmij34&index=4 (Accessed: 12 Jan 2021) Figure on page 29. Author (2020) Results from the algorithm Figure 4. Author (2020) Data from the algorithm visualized in AutoCad Figure 5. Author (2020) Isometric representation of “tree-like resource stations” distributed around the city Figure on pages 32-33. Author (2020) Forest City Figure on pages 34-35. Author (2020) Forest City.1
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Appendix using System; using System.Collections.Generic; using System.Linq;
var random = new Random();
namespace SpatialDistributionSimulator { public class Program { public static void Main() { Console.WriteLine(“X:”); var lenght = double.Parse(Console.ReadLine()); Console.WriteLine(“Y:”); var hight = double.Parse(Console.ReadLine()); var pattern = new List<double>(); var pattern1 = new List<double> { 2.2, 3.6, 4.5 }; var pattern2 = new List<double> { 2.2, 3.6, 4.5, 4.6 }; var pattern3 = new List<double> { 2.2, 3.6, 4.5, 4.6, 5.0 }; var pattern4 = new List<double> { 2.2, 3.6, 4.5, 4.6, 5.0, 5.1, 5.2 }; while (true) { Console.WriteLine(); Console.WriteLine(“Select Pattern”); Console.WriteLine($”1: {string.Join(‘;’, pattern1)}”); Console.WriteLine($”2: {string.Join(‘;’, pattern2)}”); Console.WriteLine($”3: {string.Join(‘;’, pattern3)}”); Console.WriteLine($”4: {string.Join(‘;’, pattern4)}”); Console.WriteLine(“9: EXIT”); var selectedPattern = int.Parse(Console.ReadLine()); if (selectedPattern == 9) { break; } switch (selectedPattern) { case 1: pattern = pattern1; break; case 2: pattern = pattern2; break; case 3: pattern = pattern3; break; case 4: pattern = pattern4; break; default: break; } if (!pattern.Any()) { Console.WriteLine(“Pattern is not selected properly.”); return; }
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var trees = new List<Tree>(); trees.Add(new Tree(0, 0)); var timesNotAdded = 0; var i = 0; while (timesNotAdded < 5000) { var treeAdded = false; foreach (var distance in pattern) { var currantTree = trees[i]; var var = 1; var x = 0.0; var angle = random.Next(0, 360); if (angle >= 180 && angle < 360) { var = -1; } if (angle == 0) { x = distance; } else { x = Math.Sin(angle) * distance; } var y2 = Math.Pow(distance, 2) - Math.Pow(x, 2); var y = (Math.Sqrt(y2)) * var; var cosY = Math.Cos(angle) * distance; if (currantTree.X < 0) { if (x < 0) { if (Math.Abs(currantTree.X + x) > length / 2) { continue; } } else { if (Math.Abs(currantTree.X - x) > length / 2) { continue; } } } else { if (x < 0) { if (Math.Abs(currantTree.X + x) > lenght / 2) { continue; } } else {
if (Math.Abs(currantTree.X + x) > lenght / 2) { continue; } } } if (currantTree.Y < 0) { if (x < 0) { if (Math.Abs(currantTree.Y { continue; } } else { if (Math.Abs(currantTree.Y { continue; } } } else { if (x < 0) { if (Math.Abs(currantTree.Y { continue; } } else { if (Math.Abs(currantTree.Y { continue; } } }
hightCheck = true; }
}
if (hightCheck) { continue; } var tree = new Tree();
+ y) > hight / 2)
if (currantTree.X < 0) { if (x < 0) { tree.X = currantTree.X } else { tree.X = currantTree.X } } else { if (x < 0) { tree.X = currantTree.X } else { tree.X = currantTree.X } }
- y) > hight / 2)
+ y) > hight / 2)
+ y) > hight / 2)
if (currantTree.Y < 0) { if (x < 0) { tree.Y = currantTree.Y } else { tree.Y = currantTree.Y } } else { if (x < 0) { tree.Y = currantTree.Y } else { tree.Y = currantTree.Y } }
var lengthCheck = false; foreach (var currantX in trees.Select(x => x.X)) { if (!CanBeSeeded(currantX, x, 1)) { lengthCheck = true; } } if (lengthCheck) { continue; } var hightCheck = false; foreach (var currantY in trees.Select(x => x.Y)) { if (!CanBeSeeded(currantY, y, 1)) {
}
+ x;
- x;
+ x;
+ x;
+ y;
- y;
+ y;
+ y;
trees.Add(tree); treeAdded = true; i++;
45
if (!treeAdded)
}
}
{ }
public double Y { get; set; } timesNotAdded++;
public Tree() {
}
}
private static bool CanBeSeeded(double tree, double currantTree, double distance) { var result = true; if (tree < 0) { if (currantTree < 0) { if (Math.Abs(tree { result = false; } } else { if (Math.Abs(tree + { result = false; } } } else { if (currantTree < 0) { if (Math.Abs(tree + { result = false; } } else { if (Math.Abs(tree + { result = false; } } }
}
}
}
return result;
namespace SpatialDistributionSimulator { public class Tree { public double X { get; set; }
46
}
foreach (var item in trees) { Console.WriteLine($”{item.X:f2}:{item.Y:f2}”); } Console.WriteLine(trees.Count);
currantTree) >= distance)
currantTree) <= distance)
currantTree) <= distance)
currantTree) <= distance)
}
public Tree(double x, double y) { X = x; Y = y; }
47