S HARED HABITAT COMPUTATIONAL URBAN DESIGN II
Kevin Aragón, Miguel Tinoco, Mario Gonzalez, Iván Reyes
IN DE X
Abstract Introduction
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Related Work Study Area
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Data and Variables
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Methodology
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Simulation
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Discussion and next steps
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Conclusion
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Shared Habitats
Computational Urban Design II Shared Habitats is a project of IAAC, Institute for Advanced Architecture of Catalonia developed at Master’s in City & Technology in 2020/21 by student: Kevin Aragón, Miguel Tinoco, Mario Gonzales, Iván Reyes and faculty: Alex Mademochoritis, Eugenio Bettucchi & Iacopo Neri. Key Words: Urban Biodiversity Index, Computational Design, Generative Design, Urban Habitats, Sustainability
Abstract Reversing the degradation or destruction of habitats is linked to some of the most important objectives in the fight against climate change, in general, and in the prevention of collapsing food chains. Addressing these issues within urban space is a contested, complex, yet important area of study. This work explores the creation of a set of tools that allow decisionmakers and designers to integrate ecological indexes as design variables. Specifically, this work uses the Urban Biodiversity Index as a tool for measuring impact. Through generative design procedures, the tools in this work allow its user to plan and design ecological corridors within the urban fabric.
1. Introduction negative for the species that originally populated the urbanized space. Habitat destruction, or severe degradation, is the main exchange token for the process of urbanization. Habitat loss, or degradation, has been shown to cause severe effects on both local and broader environmental systems. Amongst the effects we may recognize is the huge loss in pollinator population.1
Cities are a complex set of systems within systems. Some of these systems work within the urban fabric (as would be the green infrastructure or the public amenities) while others are heavily reliant on external unions to other systems (such as food systems or mobility systems). These systems help serve the needs and wants of those who’s lives depend on said systems. The process of manufacturing goods, shipping, storage, selling, buying consuming these systems is referred as the urban metabolism. In the process of producing cities, and in the process exponentially growing its urban metabolism, humans have severely altered the ecosystems in which cities have settled. Through industrial, cultural and political processes, humans have shaped the way in which the ecosystems that share space with the urban metabolic processes. One example of this, is the effect that urbanization has on ecosystems. The process of urbanization requires the transformation of a particular landscape into an extension of the urban fabric. This process is overwhelmingly
In recent years, researchers and designers have challenged the accepted ecology of urban space buy proposing interventions that will create space, within the existing urban fabric, in order to bring back endemic species. Examples of this push are green roofs and beehives2. While this work considers green roofs and beehives as essential stepping stones, we aim to push the transformation of the urban fabric beyond the limits of the current narrative. The aim of this work is to increase the level of urban biodiversity within our area of study. In order to do so, we have developed a set of indicators that help us evaluate the results of our work.
https://www.usda.gov/media/blog/2016/06/24/reversing-pollinator-decline-key-feeding-future Colla, Sheila & Willis, Erin & Packer, Laurence. (2009). Can green roofs provide habitat for urban bees (Hymenoptera: Apidae)?. Cities and the Environment (CATE). 2. 10.15365/cate.2142009. 1 2
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2. Related Work The architects argue that the place in which the project Is being built signifies a dubious identity. The place in question was once an extension of Hyde Park, but after new roads where built on the area, the lot was left separated from the Park and turned into an island. Marble Arch Hill is conceived as a temporary structure that highlights the contested nature of its site through the extension of Hyde Park and its transformation into a topographic feature.
Cities are a complex set of systems within sysAlthough our project takes much of its theoretical background and data background from the Urban Biodiversity Plan of Barcelona and the Green Atlas of Barcelona, the formal and spatial characteristics of our work find similarities in MVRDV’s Marble Arch Hill3 (see Image 1).
Marble Arch Hill is conceived as a topographic feature, a park and a multi-use interior (cavernous) space. Our project aims at cutting through urban space to create a morphology that resembles hill-like landscape features in which we may integrate some of the premier ecosystem engineers: plants. Image 1: Marble Arch Hill project by MVRDV
3. Study Area We’ve chosen El Born for two main reasons: The tightly packed urban fabric has severely limited the amount of public space (and public greenery) in the neighborhood. Secondly, the El Born is situated at the limits of the Ciutat Vella and borders el Parc de la Ciutadella, one of the biggest public parks in the City. In choosing El Born, we aimed at creating green habitats that would connect the inner parts of El Born with el Parc de la Ciutadella (see Image 3).
We have selected one of the densest neighborhoods of the city of Barcelona, El Born, as our area of study. Part of the Ciutat Vella district, El Born’s urban history dates to the Roman period of occupation in the Third Century of the Current Age. None the less, the urban fabric we know today was established between the 13th and 15th centuries4 (see Image 2).
Image 2: NDVI Barcelona https://www.mvrdv.nl/projects/456/marble-arch-hill https://elbornculturaimemoria.barcelona.cat/es/explora/el-conjunto-arqueologico/historia-del-born/ 5 https://ajuntament.barcelona.cat/atlesbiodiversitat/en/ 6 https://opendata-ajuntament.barcelona.cat/data/es/dataset/est-sp-taxa-mort-estand-edat 3 4
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Image 3: El Born Current Situation
4. Data and Variables
NDVI The second type of data that we used was a Normalized Difference Vegetation Index (NDVI) of the city of Barcelona7. NDVI is a remote sensing technique that uses infrared and near-infrared to help assess the levels of photosynthesis in plants. The NDVI of Barcelona helped us cement our case for the study area. El Born, as the product of an urban expansion of a different era, was not designed with the same focus on public amenities or the quality of urban space as other urban expansions of the city (namely El Eixample). The NDVI analysis showed the area of El Born as one of the poorest performing areas in the whole city, mostly due to the sheer absence of greenery (see Image 6).
This work aims at increasing urban biodiversity in the city of Barcelona through the creation of green corridors that connect el Parc de la Ciutadella with the inner parts of El Born. We were faced with two main challenges: deciding on the paths that should be converted into corridors and then designing the corridors themselves in order to increase biodiversity. Urban Biodiversity Our work is based on Urban Biodiversity Atlas5 that was generated by the Barcelona’s Ayuntamiento. The Atlas contains an index of species that have been observed to inhabit the City of Barcelona. The findings within the Atlas are organized by types of species and by their associated location within the city. Based on this data, we where able to generate our first Indicator: The Urban Biodiversity Index. The Urban Biodiversity Index shows the rate of species diversity within a given area6. From this data we also generated a short-list of species that was then used as case studies to design our green spaces (see Image 4 & 5).
Image 6: NDVI El BORN
Urban Form The third type of data we used in our study was that of the formal configuration of the urban fabric. In order to fully understand the way in which EL Born, from a tectonic perspective, works we needed to recreate its form in three dimensions. This allowed is to, not only analyze the urban fabric, but to also propose interventions and visualize their effects on the urban fabric (see Image 7).
Image 4: Biodiversity Atlas web page Ajuntament de Barcelona
Erithacus rubecula
Rosmarinus officinalis
Pipistrellus pipistrellus
Image 5: Some species that can be found in Barcelona 7
Image 7: El Born Morphology
https://scihub.copernicus.eu/dhus/#/home
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5. Methodology:
While our work uses information from various analytical environments, such as Geographical Information Systems, all of the simulations where developed and executed in the Grasshopper visual programming environment, within the Rhinoceros modelling software. In order to assess the routes of the ecological corridors as well as their layout, we have decided on two three types of simulations: Pathfinding, Subtractions and an Occupation simulation for the plants (see Figure 1).
Types of Simulations
Our procedure is a three-part process that simulates the reshaping of the urban fabric into new habitats. The output of the simulation is the process of codependent sub-procedures. The data that is used from the first procedure is then used as the basis of the second which in turn becomes the basis for the third and final procedure.
Figure 1: Diagram; model simulator intentions.
Figure 2: Diagram; corridor simulation 4
The Pathfinding Simulation was generated through the Wooly Paths Definition (see Figure 2), which was developed using components of the Kangaroo2 Plugin. The Definition allows us to generate an organic path based on two forces that can be lines (connections) which can be controlled based on parameters such as spring stiffness, rest length and stick behavior (see Figure 3). These parameters interact within a loop which allows to observe the infinite possibilities to create the new organic path between the points or objects to be connected (see Image 8).
Figure 3: Wooly
Image 8: Wooly Path
Path design examples.
The Subtraction Simulation was created through the solid difference component. This component helps generate subtractions in the urban fabric and along the paths generated by the previous simulation (see Image 9). The subtractions in the urban fabric generate different intervention typologies (see Image 10). These are based on the varying sloping degrees of these cuts. It is in these interventions that we then transform into green spaces (see Figure 4).
Image 9: generate subtractions 5
Figure 4: Diagram; Blocks deconstruction and typologies
Image 10: Catalogue - slicing and sloping 6
Trees
Height Minimum
Radius Girth Maximum
Minimum
Maximum
Small Bush
The Occupation Simulation is based on the Circle Packing definition found within the Kangaroo2 plugin (see Figure 5). This simulation’s goal was to help visualize the optimal planting schedule within the selected sites of intervention. In order to do so, the simulation uses as input raster data from the output of the Subtraction Simulation to assign places and locations for the plants. The simulation also uses the predefined radius of the plats we included in the simulation in order to generate the schedule (see Image 11). The simulation reads the output of the Subtraction Simulation as a height map and, using the radius of the selected species, allocates plants to their assigned value (see Image 12). It is with this part of the tool that we may estimate the impact on biodiversity within the urban sphere.
1 Strelitzia alba
3.6
4.5
1.8
2.4
https://images.app.g
2 Rosmarinus officinalis 'Prostratus' 3 Prunus spinosa
0.3 2.5
0.6 4
0.6 2.5
0.9 4
Rosmarinus officina Prunus spinosa Sloe
1 Ligustrum japonicum
2.1
9.4
1.3
3.2
https://www.monum
2 Jacaranda mimosifolia 3 Lagerstroemia indica
3.5 3
15 17
1.2 0.8
3.5 1.32
https://www.monum https://www.monum
1 Cercis siliquastrum
4.5
19
1.2
5
https://www.monum
2 Grevillea robusta 3 Quercus ilex
8 12
24 25
1.35 5.25
5.7 8.95
https://www.monum https://www.monum
Medium
Bigger
Nesting birds
Justification
1 Cyanistes caeruleus
scattered tree cover its nest inside old trees, street lamps or any other kind of artificial structure
2 Pica pica 3 Erithacus rubecula
trees and moderately dense shrub formations with good herbaceous coverage https://images.app.g highest values for the thick holm-oak https://images.app.g
Butterflies
Justification
1 Colias crocea
abundant blooms
https://images.app.g
2 Pararge aegeria 3 Pieris rapae
forests, shrubberies, humid areas, streams gardens, orchards and ruderal
https://images.app.g https://images.app.g
Vertebrates
Justification
1 Pipistrellus pygmaeus
Preferred habitat is one with water points
https://images.app.g
2 Alytes obstetricans 3 Pipistrellus pipistrellus
masses of water free of fish and land shelters such as stones or low and dense vegetation. holes and cracks of trees and in fissures of buildings
https://images.app.g https://images.app.g
Ponds
Justification
Vegetation 1 Pontederia cordata
The flowers attract pollinators
https://images.app.g
2 Mentha aquatica 3 Nelumbo nucifera
is aromatic, mint aroma lowers are pink, very large
https://images.app.g https://images.app.g
Animals 1 Alytes obstetricans
masses of water free of fish and land shelters such as stones or low and dense vegetation.
https://images.app.g
2 Sympetrum fonscolombii 3 Hyla meridionalis
Ciutadella and Gardens of the Pedralbes Palace. terrestrial and semi-arboreal habits, stones or dense vegetation
https://images.app.g https://images.app.g
Image 11: Descriptive morphology classification.
Figure 5: Diagram; Size and vegetation relation 1
https://images.app.g
2
3
4
Image 12: Simulation using height map and radius to select species, allocates plants to their assigned value
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Human Density One of the strategies we propose to increase biodiversity (see Image 13) is to make space within the urban fabric. In order to do so, we’ve designed a procedure that allows us to carve paths through the built environment. One of the consequences of this method is the reduction of space for humans. In order to calculate the effects on human density, we generated a scrip that would allow us to calculate the amount of basic housing units that would be lost. The metric is based on the rationale that every person living within urban space would require at least 80sqm. Our scrip calculates the estimated basic housing units that are being lost through our intervention. Increased Biodiversity (see Figure 6 & 7).
Image 13: Biodiversity comparison between current - new
Figure 6: Diagram; Density calculation.
Figure 7: Diagram; Biodiversity graph information. 8
6. Simulation In order to transform our procedures into a tool for planners and decisionmakers, we have integrated these simulations into a single environment through which users may interact with the different variables and generate new scenarios. The User Interface (UI) allows users to select the area of intervention through a map. In a second step, the UI allows the user to select the control points for the path generation simulator. Once the paths are selected, the UI can provide feedback of the areas that will be affected by the new path. (see Image 14)
In the second phase of the process, the user is then allowed to control the steepness of the slopes that will cut through the urban fabric. The final part of the process allows users to control the type of plant species that would from the basis of the Occupation simulation. This final process generates the Urban Biodiversity Index (UBI) which is shown as part of the UI. The Interface also allows the user to contrast the original UBI of the site with the simulated UBI, which helps users understand the magnitude, efficacy and efficiency of their interventions.
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3
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Image 14: User interface steps. 9
7. Discussion and Next Steps We visualize this research as an ongoing project. It is our belief that, in order to make this tool useful to planners and decisionmakers, we must further develop the analytical capacities of our procedures. There is one area we believe should be the focus of our future research: integrating spatial syntax procedures to the Occupation Simulation. The Occupation Simulator enables users to control the planting schedule of a set of plants based on the radius of their area of occupation. While this gives users some degree of control, we recognize that ecological systems are multivariate dynamics and should not be limited to one or two variables. In order to address the level of complexity this procedure requires; We aim to integrate spatial syntax procedures in order to create relational parameters that may allow to create planting schedules based on the symbiotic relationship of sets of plants.
Pica pica
Hyla meridionalis
Pipistrellus pygmaeus
Colias crocea
Sympetrum fonscolombii
Alytes obstetricans
Nelumbo nucifera
Strelitzia alba
Cercis siliquastrum
Image 15: Barcelona species from Biodiversity index. Logic Arguments Planar Surface Slope
Slope
if (x
45 ) then ( a, b, c shrubs)
if (20 if (0 Planar Surface
x x 2
0/m) then ( no plants possible)
2
N/m ) then ( d, e, f small trees) U (a, b, c shrub) y N/m) then ( g, h, i large trees) U (d, e, f small trees) U (b shrub)
if (y/m if (0/m
2
if (y/m Plant Syntax
45 ) then ( d, e, f small trees) U (b shrub) 20 ) then ( g, h, i large trees) U (d, e, f small trees) U (b shrub) 2
if (1large tree)
2
2
then ( N shrubs desired)
Figure 8: Spatial syntax example for our project.
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8. Conclusion well as a partial solution to larger environmental problems caused by the expansion of human settlements. The tool presented in this work aim to provide designers and planners the ability to input environmental variables into the equations of spatial and formal configuration. Through this methodology we are overtly stating that ecological indexes need to form the basis of design and decision making within the urban sphere if we are to address the sustainability of our systems.
Reversing the degradation or destruction of habitats is linked to some of the most important objectives in the fight against climate change, in general, and in the prevention of collapsing food chains. Addressing these issues within urban space is a contested, complex, yet important area of study. While urban space has been predominantly designed for human activity, there are a myriad of negative externalities that severely affect our health and livelihoods8,9. Integrating habitats for non-human lifeforms within urban space is both a symbolic representation of the symbiotic relationship between human and non-human systems as
Image 16: Project final vision. https://www.amnh.org/learn-teach/curriculum-collections/biodiversity-counts/plant-ecology/how-to-calculate-a-biodiversity-index Source: World Health Organization Preventing disease through healthy environments: Towards an estimate of the environmental burden of disease. 9 https://opendata-ajuntament.barcelona.cat/data/es/dataset/est-sp-taxa-mort-estand-edat 8
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