EVOLUTIONARY LANDSCAPES - Grover, Greenwald, Kurtz - UO 2021 LA 408/508

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EVOLUTIONARY LANDSCAPES Alison Grover Hillary Greenwald Lindsay Kurtz

Evolutionary Landscapes LA 408/508 School of Architecture and Environment Mary Polites + Ignacio Lopez Buson



1 ANALYSIS - location - topographic data - site - analysis - conclusions

2 EVO-DEVO

3 GALAPAGOS

- objective - populations - evaluation - highlights

- objectives - generation 1 - generation 2 - generation 3

4 VR VISUALIZATION - topo deconstruction - perspectives - evolutionary tree


1.0

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ANALYSIS

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1.0

ANALYSIS Locations

The Pacific Northwest The three sites selected for analysis span from Oregon to Washington, from the coast to the Willamette Valley. Within and among sites is a variety of topography, from mountains to riverbeds. Source: Esri, HERE, Garmin, Intermap, increment P Corp, GEBCO, USGS, FAO, NPS, NRGAN, GeoBase, IGN, Kadaster NL, Ordinance Survey, Esri Japan, METI, Esri China (Hong Kong), (c) OpenStreetMap contributors, and the GIS User Community.

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1.1

ANALYSIS Triangle Lake Coast Range

0.5 miles

Triangle Lake Coast Range The first site is located in the Oregon Coast Range, west of the town of Veneta and East of Florence. Drainage and tributaries from on site flow into the Siuslaw River which then continues on to the Pacific Ocean. The site is removed from human development aside from logging roads established for the harvesting of timber. Nearby features of interest are Triangle Lake to the Northeast, Fern Ridge Resevoir to the Southeast, and HWY 126 to the South.

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1.2

ANALYSIS Triangle Lake Coast Range

0.5 miles Triangle Lake Coast Range The site is a half-mile by half-mile, composed of varied topography typical of the central coast range of Oregon. The entirety of the site is owned and managed by the Bureau of Land Management of Oregon, therefore it is undeveloped and unoccupied by humans.Vegetative cover is assumed to be a Fir-Hemlock forest, second or third growth, managed for timber production.

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1.3

ANALYSIS Environmental analysis

40%

1000’

Elevation

400’

Slope

N

Aspect 16 |

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S

5%

1500 cfs

Runoffs

0 cfs Hillary Greenwald / Alison Grover / Lindsey Kurtz / EVOLUTIONARY LANDSCAPES

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1.4

ANALYSIS Jim’s Creek

0.5 miles

Jim’s Creek Jim’s Creek is a restored oak-pine savanna in the Willamette National Forest. The site is very steep with hot, southwest facing slopes that help the savanna and prairie persist in a matrix of Doug Fir forest. The heat and steep slopes provide an interesting topography to study solar radiation and runoff.

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1.5

ANALYSIS Jim’s Creek

0.5 miles

Jim’s Creek Site This 1/2 mile by 1/2 mile section of Jim’s Creek shows the steep southwest facing slope and some of the ridges that exist across the site. These are created by bedrock close to the surface that has resisted weathering compared to its surroundings.

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1.6

ANALYSIS Jim’s Creek

High Elevation

Elevation

Low Elevation

Steep Slope

Slope

Flat Slope

2

2 Solar Rays

High Runoff

1 Solar Ray

Solar Radiation from Two Points 22 |

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0 Solar Rays

Runoff

4

Low Runoff 5

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1.7

ANALYSIS Lake Cushman

Lake Cushman This site is within the Olympic National Forest in Washington. It is Northwest of Lake Cushman and straddles the North Fork Skokomish River.

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1.8

ANALYSIS Lake Cushman

0.5 miles

Lake Cushman Site The site is characterized by a steep south-facing slope on the north side draining into river lowlands on the south side.

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1.9

ANALYSIS Environmental analysis

45o

1800’

Elevation

900’

Slope

0o

9

Solar radiation 28 |

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0

Runoff Hillary Greenwald / Alison Grover / Lindsey Kurtz / EVOLUTIONARY LANDSCAPES

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2.0

30 |

EVO-DEVO

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2.1

EVO-DEVO Triangle Lake Coast Range

Objective Using topographic manipulation and shortest walk analysis, the goal of this study is to develop an interesting and lengthy trail from point A in the Southwest corner of the test plot, to point B in the Northeast corner.

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2.2

EVO-DEVO Shortest Walk Outcome #1

# Points: 8 Height: 200 Width: 150 Path Length: 1.15 mi

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2.3

EVO-DEVO Shortest Walk Outcome #2

# Points: 10 Height: 180 Width: 180 Path Length: 0.76 mi

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2.4

EVO-DEVO Shortest Walk Outcome #3

# Points: 4 Height: 300 Width: 250 Path Length: 0.68 mi

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2.5

EVO-DEVO Shortest Walk Outcome #4

# Points: 29 Height: 100 Width: 75 Path Length: 0.82 mi

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2.6

42 |

EVO-DEVO Populations Triangle Lake Coast Range

1

1

1

1

2

2

2

2

1. Population 1 Axon View 2. Population 1 Plan View

1. Population 2 Axon View 2. Population 2 Plan View

1. Population 3 Axon View 2. Population 3 Plan View

1. Population 4 Axon View 2. Population 4 Plan View

# Points: 8 Height: 200 Width: 150 Path Length: 1.15 mi

# Points: 10 Height: 180 Width: 180 Path Length: 0.76 mi

# Points: 4 Height: 300 Width: 250 Path Length: 0.68 mi

# Points: 29 Height: 100 Width: 75 Path Length: 0.82 mi

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2.7

EVO-DEVO Evaluation Triangle Lake Coast Range

40%

1000’ Elevation

400’

Slope

N Aspect 44 |

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S

5%

1500 cfs Runoffs

0 cfs Hillary Greenwald / Alison Grover / Lindsey Kurtz / EVOLUTIONARY LANDSCAPES

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2.9

EVO-DEVO Jim’s Creek

Objective The goal of this simulation is to create a landscape that has the most possible area with a slope of 20 degrees or less. This is the starting topography with its total slope areas of 20 degrees or less.

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2.10

EVO-DEVO Slope Outcome #1

# Points: 26 Height: -200 Width: 50 Total Area: 4.2 Slope 20 degrees or less.

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2.11

EVO-DEVO Slope Outcome #2

# Points: 26 Height: -100 Width: 50 Total Area: 4.8 Slope 20 degrees or less.

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2.12

EVO-DEVO Slope Outcome #3

# Points: 26 Height: 100 Width: 50 Total Area: 4.6 Slope 20 degrees or less.

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2.13

EVO-DEVO Slope Outcome #4

# Points: 26 Height: 300 Width: 60 Total Area: 3.2 Slope 20 degrees or less.

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2.14

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EVO-DEVO Populations Jim’s Creek

1

1

1

1

2

2

2

2

1. Population 1 Axon View 2. Population 1 Plan View

1. Population 2 Axon View 2. Population 2 Plan View

1. Population 3 Axon View 2. Population 3 Plan View

1. Population 4 Axon View 2. Population 4 Plan View

# Points: 26 Height: -200 Width: 50 Total Area: 4.2 Slope 20 degrees or less.

# Points: 26 Height: -100 Width: 50 Total Area: 4.8 Slope 20 degrees or less.

# Points: 26 Height: 100 Width: 50 Total Area: 4.6 Slope 20 degrees or less.

# Points: 26 Height: 300 Width: 60 Total Area: 3.2 Slope 20 degrees or less.

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2.15

EVO-DEVO Evaluation Jim’s Creek

Steep Slope

High Elevation

Elevation

Low Elevation

Flat Slope

Slope

2 Solar Rays

High Runoff

1 Solar Ray

Solar radiation 58 |

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0 Solar Rays

Runoffs

4

Low Runoff

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2.17

EVO-DEVO Lake Cushman

Objective This topography was manipulated to reduce runoff flow length. By adding topographic variation, the runoff flow length changes.

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2.18

EVO-DEVO Runoffs Outcome #1

Points: 72 Width 50 Height 100 Flow Length 108,771’

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2.19

EVO-DEVO Runoffs Outcome #2

Points: 72 Width 50 Height 200 Flow Length 94,339’

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2.20

EVO-DEVO Runoffs Outcome #3

Points: 72 Width 50 Height 300 Flow Length 91,927

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2.21

EVO-DEVO Runoffs Outcome #4

Points: 72 Width 50 Height 400 Flow Length 96,559

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2.22

EVO-DEVO Populations Lake Cushman

1

1

2

70 |

1

2

2

2

1. Population 1 Axon View 2. Population 1 Plan View

1. Population 2 Axon View 2. Population 2 Plan View

1. Population 3 Axon View 2 . Population 3 Plan View

Points: 72 Width 50 Height 100 Flow Length 108,771’

Points: 72 Width 50 Height 200 Flow Length 94,339’

Points: 72 Width 50 Height 300 Flow Length 91,927

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1

1. Population 4 Axon View 2. Population 4 Plan View Points: 72 Width 50 Height 400 Flow Length 96,559

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2.23

EVO-DEVO Analysis Lake Cushman

2000’

Elevation

900’

45o+

Slope

0o

9

Solar radiation 72 |

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0

Runoffs Hillary Greenwald / Alison Grover / Lindsey Kurtz / EVOLUTIONARY LANDSCAPES

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3.0

74 |

GALAPAGOS

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3.1

GALAPAGOS Generation 1: Selected Genome

Objective Using the Galapagos definition, the aim of this study is to determine the ideal variance of topography that produces the maximum land area of slopes 15% or less.

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3.2

GALAPAGOS Generation 1: Best Outcome

Best Slope Count/Seed: 51 Height: -20 Width: 37 Total Area <15% : 1,683,582 sq. ft.

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3.3

GALAPAGOS Generation 1: Selection 1

Selection #1 Count/Seed: 21 Height: 53 Width: 120 Total Area <15% : 1.042,336 sq. ft.

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3.4

GALAPAGOS Generation 1: Selection 2

Selection #2 Count/Seed: 18 Height: 199 Width: 74 Total Area <15% : 6,272,648 sq. ft.

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3.5

GALAPAGOS Generation 1: Worst Outcome

Worst Slope Count/Seed: 80 Height: 182 Width: 63 Total Area <15% : 348,487 sq. ft.

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3.6

86 |

GALAPAGOS Generation 1: Slope Analysis

1

1

1

1

2

2

2

2

1. Best Outcome Axon View 2. Best Outcome Plan View

1. Selection 1 Axon View 2. Selection 1 Plan View

1. Selection 2 Axon View 2. Selection 2 Plan View

1. Worst Outcome Axon View 2. Worst Outcome Plan View

Count/Seed: 51 Height: -20 Width: 37 Total Area <15% : 1,683,582 sq. ft.

Count/Seed: 21 Height: 53 Width: 120 Total Area <15% : 1.042,336 sq. ft.

Count/Seed: 18 Height: 199 Width: 74 Total Area <15% : 6,272,648 sq. ft.

Count/Seed: 80 Height: 182 Width: 63 Total Area <15% : 348,487 sq. ft.

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3.7

GALAPAGOS Selected Genome

Objective The goal of this simulation was to find the topography that maximized runoffs. The algorithm ran for 32 generations before selections were made.

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3.8

GALAPAGOS Generation 2: Best Outcome

Best Runoff Count/Seed #: 29 Height: 7 Width: 32 Total Runoff Length: 219,285.0

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3.9

GALAPAGOS Generation 2: Worst Outcome

Worst Runoff Count/Seed #: 98 Height: 171 Width: 65 Total Runoff Length: 127,427.3

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3.10

GALAPAGOS Generation 2: Selection 1

Selection #1 Count/Seed #: 35 Height: 2 Width: 51 Total Runoff Length: 207,455.4

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3.11

GALAPAGOS Generation 2: Selection 2

Selection #2 Count/Seed #: 37 Height: 34 Width: 51 Total Runoff Length: 202,441`.8

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3.12

98 |

GALAPAGOS Generation 2: Runoff Analysis

1

1

1

1

2

2

2

2

1. Best Outcome Axon View 2. Best Outcome Plan View

1. Worst Outcome Axon View 2. Worst Outcome Plan View

1. Selection One Axon View 2. Selection One Plan View

1. Selection Two Axon View 2. Selection Two Plan View

Count/Seed #: 29 Height: 7 Width: 32 Total Runoff Length: 219,285.0

Count/Seed #: 98 Height: 171 Width: 65 Total Runoff Length: 127,427.3

Count/Seed #: 35 Height: 2 Width: 51 Total Runoff Length: 207,455.4

Count/Seed #: 37 Height: 34 Width: 51 Total Runoff Length: 202,441`.8

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3.13

GALAPAGOS Generation 3

Objective: Solar Using topography generated to optimize runoff length, we manipulated the topography further to optimize for solar radiation.

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3.14

GALAPAGOS Generation 3: Best Outcome

Best Solar Points: 98 Width: 160 Height: 200

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3.15

GALAPAGOS Generation 3: Selection 1

Selection #1 Points: 92 Width: 159 Height: 194

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3.16

GALAPAGOS Generation 3: Selection 2

Selection #2 Points: 99 Width: 156 Height: 197

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3.17

GALAPAGOS Generation 3: Worst Outcome

Solar Worst Outcome Points: 99 Width: 157 Height: 187

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3.18

110 |

GALAPAGOS Generation 3

1 1

1

2

2

1

1

2

2

1. Best Outcome Axon View 2. Best Outcome Plan View

1. Selection One Axon View 2. Selection One Plan View

1. Slection Two Axon View 2. Selection Two Plan View

1. Worst Outcome Axon View 2. Worst Outcome Plan View

Points: 98 Width: 160 Height: 200

Points: 92 Width: 159 Height: 194

Points: 99 Width: 156 Height: 197

Points: 99 Width: 157 Height: 187

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3.19

GALAPAGOS Final Selected Genome

After running three generations of Galapagos with three seperate topographic analysis objectives (slope, runoff, and solar) this is the final topography we developed to take forward into visualization.

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4.0

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VR VISUALIZATION

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4.1

VR VISUALIZATION Mesh segmentation

Objective The topography was deconstructed by slope % in order to determine representitive landscape cover assuming soil accumulation and depth. The steepest slopes (60-90 degrees, shown in red) were assigned rock/ice/snow. The second steepest (40-60 degrees, shown in orange) were given a mossy rock face. The third (20-40 degrees, shown in yellow) were given grasses, and the fourth (020 degrees, shown in green) were given perrenials.

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4.2

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VR VISUALIZATION Topo deconstruction

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Topography

Understory population

Landcover

Tree population Hillary Greenwald / Alison Grover / Lindsey Kurtz / EVOLUTIONARY LANDSCAPES

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4.3

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VR VISUALIZATION Seasonal changes

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4.4

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VR VISUALIZATION Perspectives

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4.5

124 |

VR VISUALIZATION Perspectives

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4.6

126 |

VR VISUALIZATION Perspectives

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4.6

128 |

VR VISUALIZATION Perspectives

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4.7

VR VISUALIZATION Evolutionary tree

ORIGINAL TOPOGRAPHY

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GENERATION 1 (slope)

GENERATION 2 (runoff)

GENERATION 3 (solar)

SEGMENTATION (slope)

FINAL LANDSCAPE

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5.0

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CREDITS

UO LA 423/523 ADVANCED DIGITAL MEDIA

Hillary Greenwald

Lindsey Kurtz

Alison Grover

Hillary is currently a candidate for the Master of Landscape Architecture degree at University of Oregon in Eugene, OR. She holds a Bachelor of Science in Natural Resource Conservation & Technology from Oregon State University-Cascades in Bend, OR. After working as a Landscape contractor for a few years in Bend she became interested in design and decided to pursue a degree in Landscape Architecture. Her interest lies in combining her background in resource conservation with landscape development to produce aesthetically pleasing, functional, and ecologically minded private and public landscapes within and outside of the urban locale. Her current work is based upon developing a computer generated landscape analysis sequence paired with ground-truthing to inform design for outdoor recreational spaces located in natural areas.

Lindsey Kurtz is currently a master’s candidate in Landscape Architecture at the University of Oregon. She graduated from the University of Wisconsin-Eau Claire with a Bachelor of Science in environmental geography with a geospatial certificate. Her senior capstone project focused on using growth rings of oak trees to research flooding history on the Chippewa River near Eau Claire. She also studied abroad in Central Europe and Belize learning about ecosystems and the idea of ‘space and place.’ These experiences and her work in geography led her to landscape architecture at the University of Oregon. Her interests have always been centered around the ecosystems at work in her environment and how people interact and are influenced by them. Lindsey’s current research focuses on a restored oak-pine savanna in the Willamette National Forest in Oregon and explores how these fire-adapted ecosystems can be successfully restored and used to help communities adapt to wildfire.

Alison is currently a master´s student in her final year of Landscape Architecture at University of Oregon. She is interested in clean energy, urban ecology, democratic public space and sustainable transportation. Making public spaces lush and equitable while increasing the multifunctionality of our cities are important topics of research of hers. Her master’s project combines environmental justice, multifunctinality, and sustainable energy landscapes in order to increase energy access and integration in the urban built environment. She realized her passion for landscape architecture and urban design during an immersive semester in Copehnagen as an undergraduate. Her background is in sculpture and anthropology from Colby College, and she is originally from the Boston Area.

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Evolutionary Landscapes LA 408/508 School of Architecture and Environment Mary Polites + Ignacio Lopez Buson


Evolutionary Landscapes LA 408/508 School of Architecture and Environment Mary Polites + Ignacio Lopez Buson


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