Seminar Catalogue: VU Landscape and Territorial Strategies vs SE City Vision

Synthetic Landscape Lab, Prof.Claudia Pasquero Institute of Urban Design, University of Innsbruck

[BOOKLET]

VU Landscape and Territorial strategies vs SE City Vision

[FACULTY] TUTORS: Prof.Marco Poletto Maria Kuptsova Apostolos Mouzakopoulos

ASSISTANTS: Emiliano Rando Elena Hasanramaj

[STUDENTS] Armin Aziz Caspar Nagenrauft Evis Storke Julian Edelmann Luca Guarino Michael Hetzenauer Mirco Fantini Sabrina Dorner Aileen Larcher Alexandra Morales Alex Kerschbaumer Denis Novotny Drenusha Lokaj Eren Kargi Eugen Halbhuber Fatama Baltaci Katharina Kienzel Kristian Walder Leonhard Shedel Leopold Pretzel

Linda Kick Lukas Rangger Maja Link Milena Thurner Noah Balla Nico Oberbeck Patrick Testerman Peter Jensen Sonja Mair am Tinkhof Stepanie KĂźng Tamer Acar Thomas Rothschopf Zoran Mirceta

UIBK | IOUD | SLL 2020 A

Julian Edelman Se City Vision ss2020

[NASA]

Encoding

Filter: alpine + urban

The topography is analysed and redescribed trough mathematical definintions and generative algorithmns. In this way we can decode the datascapes, unfold and read it in order to prompose a new kind of computational panorama of this territory and create a form of representation that is capable of engaging with the processes that are often invisible or not often directly related to the build environment.

In order to to get more information than we as humans can perceive with our senses, in this chapter NASA landsat satelite datasets are used to unfold our landscapes which we are surrounded of.

Technical sensors detect structural and material characteristics of the landscape and represents them in different colors and patterns. The output drawings are a medium to discuss the condition of the environment in we live today.

Aerial drones are scanning the topography in order to generate a high resolution large scale colored and textured pointcloud of an 50x50km area around Innsbruck using a photogrammetry algorithmn.

Topographic regions: Innsbruck 50x50km

Programs: surface reflections red: urban blue: agriculture brown: forest white: snow Actor+Agents: NASA landsat 5 satelite

3

[sim.1] simulation 1

50.000 particles

Karwendel

Abstraction

[zoom x5]

The data from the previous chapter feeds a computational design apparatus which is used to sharpen and deepen the speculation forward. Everything that typically is assigned to infrastructure could become the landscape. It sort of simulates the possibilty of the landscape to assume perfomances and functions that are typically related to infrastructure. Landscape and city are no more physically separated, they are merging into each other. Gradients of structure and gradients of color indicates to a high terrain and biodiversity. This signifies a dynamical landscape which is always adapting to it´s environment.

The NASA satelelite images and the pointclouds are used as an input for the computational simulation, whereas each point of the pointclouds represents a xyz position of a particle and each rgb value of the satelite images represents a material.

Filter: alpine

Topographic regions: Innsbruck 10x10km Programs: surface reflections red: urban blue: agriculture brown: forest white: snow

Actor+Agents: NASA landsat 5 satelite

[sim.2] simulation 2

300.000 particles

Karwendel

5

[disp.3] displacement 3

4.734.976 vertices Innsbruck-Amras

Abstraction

[zoom x100]

The technique described from before is now applied on a smaller scale. Instead of simulating a large alpine territory, we are now investigating on an urban scale.

The xyz position input for the computational design apparatus is this time provided by a satelite image based displacement map instead of a large scale pointcloud scan.

Thereby we can compare alpine and urban territories in terms of it´s material and structural characeristics.

Filter: urban

Topographic regions: Innsbruck 500x500m Programs: surface reflections green: meadow brown: agriculture grey: infrastructure

Actor+Agents: NASA landsat 5 satelite

[sim.4] simulation 4

10.000 particles

Innsbruck-Amras

7

[trails]

Metamorphosis

Filter: alpine + urban

The computational design apparatus of the previous chapter is sending the simulated data in realtime back to the aerial drones which are using this data for tracking.

The drones are following the paths of the simulated trails and they are equipped with a fertilizer which they apply to the landscape in order to stimulate the biodiversity.

According to the color code the drones know how to adjust the fertilizer in order to react to the simulated material conditions.

In this way we can prompose a new kind of dynamical and artifcial landscpape which is always adapting and corresponding in realtime to the given site.

Topographic regions: Innsbruck 50x50km

Programs: surface reflections red: urban blue: agriculture brown: forest white: snow

Actor+Agents: NASA landsat 5 satelite

9

Armin Azizi Se City Vision ss2020

Proximity Studies [01]

Density in cities

[00]

Cities are complex structures, which behave like a living or-ganism. They keep growing, as society is moving to cities. In 2020 the percentage of people living in cities is at 56%, the prognose for the year 2050 is at 68,4%.

Somes structures are well organized and can handle this abrupt population surge, other structures are more known as natural grown cities, they adapt to the topography of the sorroundings.

Filter: like territory, typology or archaeology

Topographic regions: Urban region of the cities

Topographic regions: Urban region of the cities

The first city I analyzed was Athens. A very ancient city, which had a very fast growth. Athens was one oft he first cit-ies, where the hippodamic grid was applied to. It gives prop-erties of a compact, well organized and efficient city.

On the other hand there is the city of Lisbon. The capital city of Portugal has a heterogenous structure, that means that it’s growth was more natural than well organized and planned. The intersection of different eras and people is vis-ible, because there was no guiding line of urban planning from the beginning on.

Also the accomodation of the city due to its topography of the hills and valleys is visible.

The study concentrates on comparing Lisbon and Athens by their density of inhabitants and buildings. To get a valid and realistic comparison, there have been applied a grid on an area of 2x2km. Furthermore, the choosen regions where the ones, where there were most of the buildings distributed. It clearly showed, that the city of Athens had much more con-nections.

Also the aspects of how this denseness is influencing the city structure and the citizens, how the mobility is organized and how reachable important spots are (for example train sta-tion, commercial zone, etc.) represent important references for the analysis.

The project shows, how the types of cities interact with the inhabitants and how the mobility with public transportation are influenced by that.

Programs: Proximity network, shortest walk lines, public transportation

Programs: Proximity network, shortest walk lines, public transportation

Actor+Agents: Buildings, mobility, infrastructure

Actor+Agents: Buildings, mobility, infrastructure

Filter: Territory of 6x10,6km

Showing the different build-ings foodprints of the cities through the figure ground plan and the overlay of the proximity network, which show the next possible con-nection of one building to the other one with different settings of line length.

With the variation of the set-tings you can display more connections and visualize the proximity of the build-ings density in different ways, as the picture of the proximity studies shows.

13

[02] Filter: Railway stations Topographic regions: Urban region of the cities

Programs: Proximity network, shortest walk lines, public transportation

Actor+Agents: Buildings, mobility, infrastructure

Public Transportation An important aspect of density is how it influences the mobil-ity of the citizens and how it’s structure brings positive values for the people, which have to move day by day from point A to point B. In this study the attracting point of the shortest walk was the rail-way station in both cities, which shows how much buildings in this specific area are connected to the railway station.

15

[03] Filter: Commercial area Topographic regions: Urban region of the cities

Programs: Proximity network, shortest walk lines, public transportation

Actor+Agents: Buildings, mobility, infrastructure

Commercial area An important area, which peo-ple have to reach every day is the commercial area.

The reach-ability and the connection to the public transportation is fun-damental to assure the citizens a smooth connection from the residential area of the city to their work place.v

17

[04] Proximity network

Overview mobility

[04]

The last type of analysis helps to get a general overview of the situation of public transportation in the cities.

It turned out that Athens had a view regions, where the inhabitants had to walk for more than 2km to reach the first public stop. My personal ap-proach to find a solution to this lack of connection is to put car/bike/ scooter sharing on this certain parts of the cit-ies, where you can move with those means of transport to the bus stops. In the city of Lisbon the situation of public transport is quite well con-nected, applying a proximity network helps to visualize the high quantity of the public stop connections. The lines have a maximum length of 1km, so that you can see how much distance there can maximum be from one stop to the other.

Filter: Territory of 6x10,6km

2.000x2.000m grid

Lisbon

[04] Proximity network

2.000x2.000m grid

Athens

Topographic regions: Urban region of the cities

Programs: Proximity network, shortest walk lines, public transportation

Actor+Agents: Buildings, mobility, infrastructure

19

Caspar Nagenrauft Se City Vision ss2020

Public Transport IBK

[00]

Pollution caused by vehicles in the city has grown to a big issue. In Shanghai for instance there is besides the weather map a air pollution map which shows the user the amount and risks of pollution in his destination areas. To prevent situations like in Shanghai the people in Europe searching for new ways to keep private traffic as low as possible. In many german cities there are Park and Ride Areas in the edge of big cities with direct public transport connection, reachable in less than three minutes footway.

Public Transport is highly important for reducing private vehicles in inner cities. The better the public connections are built the lesser people tend to use their car to drive to work. But it is limited to the cities infrastructure like wideness of the streets and possibilities to build railways. In Europe cities are mostly historically grown. They have a dense city core with several kathedrals, churches and kapelles in it, and in an exposed position a central station, a hospital and other necessary infrastructural buildings. As Schools, Postoffices, Policestations, Banks ect. pp.

As the cities itself the Public Transport is also historically grown and always in change. For instance in Innsbruck there will be soon a Tram connection for the Technik to Hall, or in other words from the West to the East in one Tramline measuring more then 14 km. With the change of Innsbruck in the industrialization there grew several villages very fast and added up to Innsbruck. Pradl is one of these, formerly like the most villages in agriculture use, its number of inhabitants increased rasant and today it is the district of Innsbruck with the most inhabitants.

But are all areas of a town well connected with public transport. or causes fast growth of housing and people sometime a vacuum on public transport infrastructure due to the slow mills of burocracy in the townleadership? Is there even a mismanagement in public transport? Or where are the good points in a town compared to another town?

To find answers on these question the first step is to analyze the network and lines of public transport in relation to the streets and very important in relation to housing and public density.

Another step can be to find out the hidden centres of a city and the knotpoints of infrastructure. This can be related to as some words up explained the central station, schools, hospital, bank and so on. The goal has to be to reduce private vehicles as less as possible with still permitting the inhabitant of a town maximal freedom. Freedom with responsibility of course.

Filter: Innsbruck 10kmx10km

Topographic regions: Inntal

Programs: GIS Data

23

[01]

Public Transport

Filter: territory

Innsbruck is a pretty dense city.

This is related to its special spatial position. The city lays in the “Inntal� and the possibilities to grow mostly goes East-West. There are very less Options for Innsbruck to expand North-West. The points shown in the image are the public transport stations. The colors show the amount of numbers of buildings which are reachable in a walking distance of 600m from the relating public transport point.

Topographic regions: Inntal

Programs: GIS

25

[02]

ProximityLines

[02]

ProximityLines of Public Transport Staions

Innsbruck has a basically good Public Transport Network.

My first step was to visualize the Network of Public transport Stations. I made this by using Proximity Lines of a radius of 600 meters and maximum of 6 connections.

After visualizing the network i analysed the cells and highlighted the Ares of low density of public stations.

Filter: territory

Topographic regions: Inntal

10kmx10km

Innsbruck

Programs: PrroximityNetwork

[02] Problem Areas of the Public Transport Network

10kmx10km

Innsbruck

27

[03] Existing Public Transport Routes

10kmx10km

Innsbruck

Public Transport Routes [03] At this Point i analysed the Public Transport Routes existing in Innsbruck. After this i use the Shortest Walk tool with center in in the central station in Innsbruck. The comparsion between to two path systems shows the most efficent way to guide a new public transport system through Innsbruck.

Filter: territory

Topographic regions: Inntal

Programs: Shortest Walk

[03] Shortest Walk

10kmx10km

Innsbruck

29

Luca Guarino Se City Vision ss2020

Pandemic Dublin

Luca Guarino

In the seminar of city visions 2020 we are analyzing city struc-tures, human patterns in and around cities as well as natural phenomena and how these aspects affect each other, create new pattern to reveal knowledge and inspiration for future projects and ideas.

Filter: Dublin City Center; urban landscape; parks;

After getting in touch with the tools we work with (mainly grasshopper) for the first times, playing around and figuring out how everything works, I focused on the city center of the Irish capital Dublin. Due to the current situation of Co-vid-19 I was interested in the patterns of human interaction and movements in a situation like this. Furthermore I try to find correlations of these systems in the urban structure of Dublin in this extraordinary times.

Topographic regions: cityscape

Programs: catchment areas; accumulations; density

I then tried to visualize where people mainly interact in times of pandemic and stay at home policy. I thought people man-ly meet in parks and green areas. I started by mapping all the public parks in the area of Dublin City. In order to find out about the amount of usage, i analyzed the catchment areas of each park.

This illustrates a certain scope in which I assume is a lot more encounter then elsewhere right now.

The cachment areas and the shortest walks from the bui-dings to it´s nearest park, create a pattern of density in which individuals clash and a higher amount of infections might take place.

The goal of my work is to make patterns of movements and interaction more visible in urban areas and how they might change in times of Covid-19 and possibly finding solutions for evolving problems.

33

DENS.1 ~ 4.8 km

Filter: leisure; accumulation

Topographic regions: parks; city center

Actor+Agents: neighborhood Since the topic of my work was the current COVID-19 pandemic, my main interest was focussing on density and accumulation parts of the city. I figured in times of lockdown, this has to be the public parks.

So i startet my work by having a closer look at all the parks in dublin city center and where they where located.

~2.6 km

Dublin City Centre - Buildings and green areas

35

~ 4.8 km 320

AREA.1

13 26

247

AREA

25 181

15 78 323

384 60

Filter: chachment area; accesibility by food

55 98

Image description cachment area around the parks

25

56

27

205

61 123 72

144 111

9

29

56

62

70

140 263 7

29

209

135

80

~2.6 km

277

Resolution 4,8km x 2,6km

Topographic regions: city center

72

67

131

53

67 25 4

19

151

4

12

128

103

47

24 98

153

140

8 5

59

27

747 76

3 28

Location dublin city center; parks

35 31

10

121

49

27

2

205

394

230 6

22 23 13 37

72

Actor+Agents: locals; neighborhood

198 9 198

339

99

370 58 57 69

136

65

17

Dublin City Centre - Catchment area of each park

~ 4.8 km 320

AREA.2

13 26

The next step was to analyse the cachment area of each park. The reason was to show the relation between the park size and the amount of usage.

247

25 181

15 78 323

384 60 55 98

Image description cachment area around the parks

25

56

27

205

61 123 72

144 111

9

29

56

62

70

The cachment area of the parks include all the buildings to which this park is the nearest.

140 263 7

29

209

135

80

~2.6 km

72

67

131

277

Resolution 4,8km x 2,6km

53

67 25 4

19

12

151

4

128

103

47

24 98

153

140

8 5

59

10

27

747

121

76

3 28

Location dublin city center; parks

35 31

2

205

49

230 6

27 22 23 13 37

72

394

The number shows the amount of buildings, that are closest to this park.

198 9 198 370

99

339

58 57 69

136 17

65

Dublin City Centre - Catchment area of each park

37

DIST Filter: distance; desnity; cesibility by food

~ 4.8 km

ac320

13 26

247

25 181

15

Topographic regions: parsk; city center

78 323 384 60 55

Actor+Agents: locals

98

25

56

27

205

72

111

9

61 123

144

29

56

62

70

140 263 7

29

209

135

80

~2.6 km

72

67

131

277

53

67 25 4

19

12

151

4

128

103

47

24 98

153

140

8 5

59

10

27

747

121

76

3 28

To get an overview of pandemic spread it´s not only important to have a look at the places of accumulation, but also the networks that lead to these places.

Therefore i observed the paths the users take to access these areas.

35 31

2

205

49

230 6

27 22 23

394

13 37

72 198

9 198 370

99

339

58 57 69

136 17

65

Dublin City Centre - Catchment area of each park and shortest walk from particular buildings

39

DENS.2 Filter: density; network

~ 4.8 km

Topographic regions: parks; city center

Actor+Agents: neighborhood

This last vizualisation shows the relation between the cachment areas of the parks and the density of the surrounding buildings.

It is important to show, that city users potentially could interact everywhere and especially in dense living areas. So in other other words, i connected two different layers of density, the density of parks with the density of housing areas.

~2.6 km

Dublin City Centre - Catchment area of each park juxtaposed with building density

41

Mirco Fantini Se City Vision ss2020

[CO DE]

First Step

Filter:

In a first attempt I divided the two cities in such a way that all building s are co nnected to the nearest park, reg ardless o f the distance that peo ple have to travel to reach it, the impo rtant thing was that each building has access to o nly o ne park. Thanks to this map yo u can see that many building s are very distant fro m the nearest park.

City density, parks

To po g raphic reg io ns: Milan 7 x1 0 km

Pro g rams: Sho rtest walk

Acto r+ Ag ents: Building s, peo ple, parks

45

[CO DE]

First Step

Filter:

In a first attempt I divided the two cities in such a way that all building s are co nnected to the nearest park, reg ardless o f the distance that peo ple have to travel to reach it, the impo rtant thing was that each building has access to o nly o ne park. Thanks to this map yo u can see that many building s are very distant fro m the nearest park.

City density, parks

To po g raphic reg io ns: Ing o lstadt 7 x1 0 km

Pro g rams: Sho rtest walk

Acto r+ Ag ents: Building s, peo ple, parks

47

[CO DE]

Second Step

Filter:

fo r my seco nd attempt I applied a radius o f o ne kilo meter aro und all parks, so that the park is near the building and can be reached o n fo o t witho ut using public o r private means o f transpo rt. With this ray yo u can see ho w many building s are included, ho w many are excluded and what ro ad peo ple have to travel to g et to the park. By relating the number o f building s included in this radius to the size o f the park, yo u can make an estimate o f ho w cro wded it can be.

City density, parks

To po g raphic reg io ns: Milan 7 x1 0 km

Pro g rams: Sho rtest walk

Acto r+ Ag ents: Building s, peo ple, parks

49

[CO DE]

Second Step

Filter:

fo r my seco nd attempt I applied a radius o f o ne kilo meter aro und all parks, so that the park is near the building and can be reached o n fo o t witho ut using public o r private means o f transpo rt. With this ray yo u can see ho w many building s are included, ho w many are excluded and what ro ad peo ple have to travel to g et to the park. By relating the number o f building s included in this radius to the size o f the park, yo u can make an estimate o f ho w cro wded it can be.

City density, parks

To po g raphic reg io ns: Ing o lstadt 7 x1 0 km

Pro g rams: Sho rtest walk

Acto r+ Ag ents: Building s, peo ple, parks

51

[CO DE]

Third Step

Filter:

As a next step, I mo dified several existing parks and added new o nes. The chang es made to the existing parks were: displacements and extensio ns o r decreases in their rang e o f invo lvement o f the surro unding building s based o n the size o f the park o r o n the need fo r peo ple to have a g reen area nearby. These chang es have also been made in such a way as to avo id o vercro wding in so me parks o r lo w use in o thers. After these chang es, the analyzed area o f Milan has 2 6 parks and 2 1 Ing o lstadt distributed in a better way.

City density, parks

To po g raphic reg io ns: Milan 7 x1 0 km

Pro g rams: Sho rtest walk

Acto r+ Ag ents: Building s, peo ple, parks 0 ,5 0 km

1 ,2 5 km

0 ,7 5 km

1 ,0 0 km

1 ,5 0 km

53

[CO DE]

Third Step

Filter:

As a next step, I mo dified several existing parks and added new o nes. The chang es made to the existing parks were: displacements and extensio ns o r decreases in their rang e o f invo lvement o f the surro unding building s based o n the size o f the park o r o n the need fo r peo ple to have a g reen area nearby. These chang es have also been made in such a way as to avo id o vercro wding in so me parks o r lo w use in o thers. After these chang es, the analyzed area o f Milan has 2 6 parks and 2 1 Ing o lstadt distributed in a better way.

City density, parks

To po g raphic reg io ns: Ing o lstadt 7 x1 0 km

Pro g rams: Sho rtest walk

Acto r+ Ag ents: Building s, peo ple, parks 0 ,5 0 km

1 ,2 5 km

0 ,7 5 km

1 ,0 0 km

1 ,5 0 km

55

Sabrina Dorner Se City Vision ss2020

Accessibility in Innsbruck

[00]

In my City Visions work I looked at Innsbruck and tried to find criteria and Patterns that show how accessible the city is depending on different kinds of Information. At first, I worked on accessibilies of everyday activities in one single neighbourhood. In the second part I wanted to focus on only one activity and one target group, so I worked on how convenient it is for students to reach their university campuses by bike and the accessibility of biking infrastructure and services.

Filter: Innsbruck//Austria

Topographic regions: Inn Valley

Programs: Bike Infrastructure, Shop Infrastructure Actor+Agents: City of Innsbruck, Students

59

[01.1] Proximity networks on different kinds of densities within the City

6100 x 6100 Innsbruck

[01.2] Shortest walk lines to destinations inside and outside of Wilten

Accessibility in everyday life

[01]

My goal was to visualize the necessity of going out of your neighbourhood daily, during a situation, that requires you to move as little as possible as the current Pandemic. I set multiple Locations with different topics, that people might want to use, for the neighbourhood of Wilten. those are: supermarkets, pharmacies, sport areas, parks, bars and restaurants. Secondly I also added, college campuses and gondolas, which are interesting in times with less strict moving regulations.

Proximity Networks of all those locations and the households of Wilten are shown in the first map, to make visible desities and how they interact.

The second Map shows the generated shortest connections frome every single household in Wilten to every single one of the locations. The lineweights get thinner, the longer the line is. In addition I definded radiuses showing the borders of walking distance, biking distance and at what point you would have to use public transportation.

Filter: Innsbruck//Austria

Topographic regions: Inn Valley

Programs: Bike Infrastructure, Shop Infrastructure Actor+Agents: City of Innsbruck, Students

Households of the neighbourhood Destinations of everyday life inside of Wilten (Supermarkets, Pharmacies, Sport, Parks, Bars/ Restaurants) Destinations of everyday life outside of Wilten (University Campuses, Gondolas)

6800 x 6800

Innsbruck

61

[01.3]

Accessibility of everyday life activities per household

Filter: Innsbruck//Austria

The generated Lines of the shortest walks built my input for the third Map. I used their lenght and quantity to apply values from 0 to 1 to each house in Wilten and connected it to a gradient that goes from dark (value 1) to bright (value 0).

My achievement was a map showing the accessibility of everyday activities for each household in Wilten.

Topographic regions: Inn Valley

Programs: Bike Infrastructure, Shop Infrastructure Actor+Agents: City of Innsbruck, Students

Range 0 to 1 (1 = less than 10 m / 0 = more than 400 m) 63

[02.1] proximity network households

5900 x 5900

Innsbruck

[01]

[02.2]

Accessibility of university campuses and biking convenience

[02]

In 2017 the City of Innsbruck registered nearly 4 million bike rides in the city and there are plans to constantly enlarge bike services for the citizens to make going by bike more convenient. Especially students that need to get to the university tend to choose their bike over bus or tram, because it’s more flexible, a lot of times faster (see example graph) and you don’t have to squeeze into a small bus with everyone else. During times like the pandemic there is a lower risk of infection for everybody if you travel by bike rather than public transportation and people that are physically unable to perform this kind of activity are given more space and safety in public transportation.

Ther first sheet shows proximity networks of all the Important Inputs, which are: the households(01) i set as starting points, the university campuses(02) that need to be reached, parking(03) for bikes, free bike repair(04) stations, the Stadtrad(05) rental stations and the new bike counting stations(06), the city introduced to collect Information about the use of Bike Infrastructure.

Filter: Innsbruck//Austria

Topographic regions: Inn Valley

Programs: Bike Infrastructure, Shop Infrastructure Actor+Agents: City of Innsbruck, Students

proximity network university campuses

5900 x 5900

Innsbruck

[02]

Maria-Theresien StraĂ&#x;e >>> Technik Campus 65

[02.3-6]

Accessibility of university campuses and biking convenience

Filter: Innsbruck//Austria

Topographic regions: Inn Valley

Programs: Bike Infrastructure, Shop Infrastructure Actor+Agents: City of Innsbruck, Students [03]

[04]

[05]

[06] 67

[02.7]

Accessibility of university campuses and biking convenience

Filter: Innsbruck//Austria

All those Proximity networks are shown in one Map together so you can see where the densities are the highest and if they overlap for differnt kinds of inputs.

Topographic regions: Inn Valley

Programs: Bike Infrastructure, Shop Infrastructure Actor+Agents: City of Innsbruck, Students

Inn and Sill river gradient of houses by height from 5 to 50m university campuses contour lines every 10m proximity networks overlapped to make visible densities of decisive factors road network bike only paths

69

[02.8]

Accessibility of university campuses and biking convenience

Filter: Innsbruck//Austria

In my third map I generated a frequency network displaying bike traffic. Startpoints are several households in Innsbruck, spread evenly over the city (see proximity network) and end points are the university campuses. Where the bike traffic accumulates and proper Infrastructure would therefore be Important the Paths are shown in darker gradients. In addition I made visible the existing paths that are only meant for bikes to show that they very often do not lie, where they would be needed according to the frequency network.

Topographic regions: Inn Valley

Programs: Bike Infrastructure, Shop Infrastructure Actor+Agents: City of Innsbruck, Students

Inn and Sill river gradient of houses by height from 5 to 50m university campuses contour lines every 10m frequency network showing bike traffic intensity road network bike only paths

71

Eren Kargi

Vu Landscape and territorial strategies ss2020

Melting ICE A glacier is a huge mass of ice that moves slowly over land. The term “glacier” comes from the French word glace (glah-SAY), which means ice. Glaciers are often called “rivers of ice.”

Filter: Reservoir Glacier

Glaciers fall into two groups: alpine glaciers and ice sheets.

Location: Schlegeis Stausee (Zillertal) Hintertuxer Glacier Border Tyrol / South Tyrol Austria

Alpine glaciers form on mountainsides and move downward through valleys. Sometimes, alpine glaciers create or deepen valleys by pushing dirt, soil, and other materials out of their way. They are found in high mountains of every continent except Australia (although there are many in New Zealand). Alpine glaciers are also called valley glaciers or mountain glaciers.

Glaciers begin forming in places where more snow piles up each year than melts. Soon after falling, the snow begins to compress, or become denser and tightly packed. It slowly changes from light, fluffy crystals to hard, round ice pellets. New snow falls and buries this granular snow. The hard snow becomes even more compressed. It becomes a dense, grainy ice called firn. The process of snow compacting into glacial firn is called firnification.

Programs: Electricity generation Sports

Actor+Agents: Eren Kargi University of Innsbruck

As years go by, layers of firn build on top of each other.

When the ice grows thick enough—about 50 meters—the firn grains fuse into a huge mass of solid ice. The glacier begins to move under its own weight. The glacier is so heavy and exerts so much pressure that the firn and snow melt without any increase in temperature. The meltwater makes the bottom of the heavy glacier slicker and more able to spread across the landscape.

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Filter: Reservoir Glacier

With glaciers like the Stubaier Glacier or the Hintertuxer Glacier, Tyrol is a Glacier Paradise and both are typical alpine glaciers like the other Glaciers in Tyrol. The Hintertuxer Glacier is the first Glacier, which opened 1968 for Skiing in Tyrol.

And it is the only Glacier, which is used in Summer for skiing. At the east side of the Glacier the Schlegeis reservoir is situated. The dam for it was build between 1965 and 1973 to produce electricity. My Project will analyse how erosions of the melting glaciers would affect this landscape in future.

Location: Schlegeis Stausee (Zillertal) Hintertuxer Glacier Border Tyrol/South Tyrol Austria

Programs: Electricity generation Sports

During the last few years the ice melted three-times faster as in the hole 20th Century, especially in the Alps.

Up to 50 Meters the Glaciers are losing yearly. The rapidly melting ice is also dangerous for the landscape, because a glacier always provides resources. For example, the most important resource provided by glaciers is fresh water, which is supports the surrounding area.

1.1 AREA

Resolution: 18x18 km

Location: Schlegeis Stausee Hintertuxer Glacier Austria

1.2 AREA Schรถnbichler Horn 3134m Rotbachlspite 2897m Riepenkopf 2900m Olperer 3476m Schrammacher 3410m

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Location: Schlegeis Stausee (Zillertal) Hintertuxer Glacier Border Tyrol/South Tyrol Austria

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A reservoir is, an enlatged natural or artificial lake, pond or impoundment created using a dam or lock to store water. Transforming the existing natural landscape to genererate electricity ist very common in Austria especially in Tyrol. This method chanced the enviroment very immense. The project simiulates the hydro erosion at the area of the Schlegeis reservoir and shows how climate change can impact of the landscape.

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Filter: Reservoir Glacier

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Programs: Electricity generation Sports

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2.3

Evolution of Hydro Erosion

Evolution of Hydro Erosion

Resolution: 18x18km

Resolution: 18x18km

Location: Schlegeis Stausee (Zillertal) Hintertuxer Glacier

Location: Schlegeis Stausee (Zillertal) Hintertuxer Glacie

2.2

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Evolution of Hydro Erosion

Evolution of Hydro Erosion

Resolution: 18x18km

Resolution: 18x18km

Location: Schlegeis Stausee (Zillertal) Hintertuxer Glacie

Location: Schlegeis Stausee (Zillertal) Hintertuxer Glacie

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The melting of the glaciers, a phenomenon that intensified in the 20th century, is leaving our planet iceless. For a great part he humans are responsible for this. Producing carbon dioxide and other greenhouse gas emissions have raised temperatures. So glaciers are rapidly melting, as result the groundwater level increases.

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Programs: Electricity generation Sports

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Location: Schlegeis Stausee (Zillertal) Hintertuxer Glacier Border Tyrol/South Tyrol Austria

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since the early 1900s, many glaciers around the world have been rapidly melting. human activities are at the root of this phenomenon. specifically, since the industrial revolution, carbon dioxide and other greenhouse gas emissions have raised temperatures, even higher in the poles, and as a result, glaciers are rapidly melting, calving off into the sea and retreating on land. scientists project that if emissions continue to rise unchecked, the arctic could be ice free in the summer as soon as the year 2040, as ocean and air temperatures continue to rise rapidly.

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Filter: Reservoir Glacier

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Erosion

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83

Zoran Mirceta

Vu Landscape and territorial strategies ss2020

Analysis Innvalley

Zoran Mirceta

Our planet has been shaped by its natural processes and ecosystems for millions of years. Tectonic movements caused the creation of mountains and elevational differences in the planets surface. Throughout the development of an inhabitable atmosphere, concentrations of carbon dioxide, oxygen and water changed heavily and developed an ecosystem of natural processes, which are the underlying factor of the planets landscapes.

With the evolution of the Humankind, the planet got inhabited and shaped differently. As the human progressed further, we developed more advanced systems of cultivating and using the planets landscapes. Gathering resources through hunting and collecting have been the first advancements in human history and progressed into a technical utilization of the planet to an extent of completely exploiting it. Agricultural systems for example, such as large scale farming installations are part of an evolution, which introduced a new way of generation. The Anthropocene era sees landscapes in a different way and utilizes already existing structures.

Through analysis of existing landscapes of the human planet, I tried to depict anthropocene landscapes, which have been heavily shaped and transformed by the human species. In my project, I am trying to examine the characteristics of natural and artificial processes and compare how these processes shape landscapes differently. What are the similarities? Can natural processes be described through digital scripts? How do artificial processes affect existing systems?

As both types of processes occur simultaneously in a human environment, it is part of my project to examine their deep relation and work with different landscapes and parameters.

Filter: Innvalley, Tirol (Austria)

Topographic regions: mountain Programs: Hydro-Erosion Thermal-Erosion

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The Innvalley

Analysis

Hydro-Erosion

Topographic regions: mountainouus region

One of the biggest problems our planet will have to face in the near future is global climate change.

I am well aware of the fact, that global climate change really is happening at the moment and that if we do not start changing something, our world will face severe problems. However, this was my motivation for this project. I decided to take a look at what effects global climate change could possibly have on the city of Innsbruck (my hometown). The reason why I chose the city of Innsbruck was not just because it is my hometown, but also because of its beneficial topographical sights, namely the high alpine region surrounding the city of Innsbruck, which I can use for my project.

The aim of my project is to see what effects global climate change could possibly have on the high alpine region surrounding the city.

In order to do so, I made use of the programme called “Hoodini�, which allowed me to rebuild a topographical map of Innsbruck and to fast forward the process of climate change in Innsbruck and to see how it could possibly affect the alpine region there. My main intention was to take a look at what effect the erosion caused by the climate change will have on the surrounding alpine region.

Programs: natural and artificial erosion of resource heavy terrain

Simulation of the Global-warming on the example of the Innvalley.

Experiment with Hydro Erosion

Nordkette

Innsbruck

Patscherkoffel

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Topgraphy lines of the Innvalley without hydroerosion.

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Rastersize: 1600m x 1600m

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Experiment with Thermal Erosion to show differece of the landscape

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Programs: natural and artificial erosion of resource heavy terrain.

Topgraphy Render of the Innvalley Thermoerosion

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While doing the project, I have also learned new stuff about the different types erosion. For example, Hydroerosion and Thermoerosion are some of the terms I came across during my research. Hydroerosion for example can happen, if the glaciers start to melt due to global climate change.

After rebuilding the Landscape of the Inn-valley, I decided to show the effects by using contour lines with different thickness. So, for example the thick lines are at the lower part of the landscape and the higher parts have thinner lines.

I also used grids as an overview for the scale of the topographical map. These were helpful tool for a better understanding of the map.

The animation off the hydroerosion on the Inn- valley, shows the effects climate change could bring us in future. Here you can see were the problems of fluts can ivolve.

By using different colours I would like to distinguish between higher and lower level of the landscape.

This should show similar properties as the mountains in real life. The Peaks are white because of the snow and the lower parts are more green because of the nature.

For next I would like to make a similar analysis but with Thermoerosion to show the difference, by doing the experiment at the same topography of Innsbruck.

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Topographic regions: mountainouus region

Topogr.

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Analysis

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Topogr.

Topgraphy Render of the Innvalley Thermoerosion Rastersize: 1600m x 1600m

Erosion 3d-Simulation of the Thermal Erosion Change of the Landscape completly dirferent as the first experiment with the Hydroerosion

1600m x 1600m

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Patrick Testermann

Vu Landscape and territorial strategies ss2020

Free the Colorado

[RESTORE]

Originating high in the Rocky Mountains, the waters of the Colorado River provide drinking water and agricultural irrigation for some 40 million inhabitants in the southwestern United States. Flowing 2.400km from Colorado to the Gulf of California, the Colorado River represents an interconnected natural system that is critical to human existence in this arid region.

Filter: Southwestern United States

For the purposes of this seminar, the focus will be one small portion of this interconnected system: Lake Powell on the border between Utah and Arizona. This area clearly represents the name “Colorado”, meaning “painted red” in Spanish. Sandstone mesas and bluffs dominate the landscape, and the Colorado River forced its way through the terrain over the last 5 million years to form a prominent canyon.

In the 1960s the natural flow of the river was altered by the construction of the Glen Canyon Dam. This created Lake Powell—essentially a large water reservoir—and the ability to seasonally control the flow of the lower Colorado River. By constructing this dam, the adjacent canyons have been flooded and the natural erosion pattern has thereby been altered.

Topographic regions: River system in a high desert environment

Programs: Dam Removal

Actor+Agents: U.S. Bureau of Reclamation U.S. National Park Service U.S. Department of the Interior State of Colorado State of Utah State of Arizona State of California State of Baja California (Mexico)

To address the morphology of this geography, we will assume that the dam no longer exists, and the river can once again flow freely. This approach focuses on the interconnected effects of the natural debris and hydrological flows to create an accurate representation of the future topography.

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[1.1]

Hydro/Thermal

Filter: Southwestern United States

Although a removal of the Glen Canyon Dam is highly unlikely in the near term, we shall assume it will ultimately be removed due to material decay and rising environmental concerns. This will restore the natural erosion flows of the Colorado River through the Lake Powell region and begin to alter the surrounding terrain.

Topographic regions: River system in a high desert environment

Programs: Dam Removal

Actor+Agents: U.S. Bureau of Reclamation U.S. National Park Service U.S. Department of the Interior State of Colorado State of Utah State of Arizona State of California State of Baja California, Mexico

This synthetic landscape looks approximately 100.000 years into the future and utilizes an aggressive hydro erosion technique along the river canyon and the surrounding tributaries. An increased thermal erosion technique is then applied to the bordering sandstone landscape, creating a vision of a restored natural erosion system.

The primary result of this erosion process is a sculpting and deepening of the river channel, as well as resulting erosion and sediment removal in the surrounding canyons where the river once again flows freely..

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[1.3] Image description Hydro/Thermal erosion Resolution 150ppi 1000x1000px Location Lake Powell, UT

[1.3] Image description Hydro/Thermal erosion Resolution 150ppi 1000x1000px Location Lake Powell, UT

[1.5] Image description Hydro/Thermal erosion Resolution 150ppi 1000x1000px Location Lake Powell, UT

[1.5] Image description Hydro/Thermal erosion Resolution 150ppi 1000x1000px Location Lake Powell, UT

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[2.1]

Thermal

Filter: Southwestern United States

As the region has been in a drought since 2000, we can assume that climate change and particularly thermal erosion will be a dominant force in the ongoing morphology of this landscape.

Topographic regions: River system in a high desert environment

Programs: Dam Removal

Actor+Agents: U.S. Bureau of Reclamation U.S. National Park Service U.S. Department of the Interior State of Colorado State of Utah State of Arizona State of California State of Baja California, Mexico

To address a future heavily informed by climate change, this digital landscape assumes a warmer, drier climate with heavily reduced hydrological flows.

This focus on thermal erosion techniques creates a dimpled, sun-cupped landscape with much sharper geological formations.

At the same time, the river carves a variegated path and exposes a series of benches, beaches, and sediment deposits as it crosses the region.

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[2.3] Image description Thermal erosion Resolution 150ppi 1000x1000px Location Lake Powell, UT

[2.3] Image description Thermal erosion Resolution 150ppi 1000x1000px Location Lake Powell, UT

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Milena Thurner

Vu Landscape and territorial strategies ss2020

Glacier Evolution In the course of the landscape and territorial strategies class we were asked to generate and analyze landscapes.

The emphasis here was on the geological composition of the area and the natural forces that cause the terrain to erode.

Depending on parameters like precipitation, wind loads and rock breaking, there are infinite possibilities how a terrain can develope over an extended period of time.

Garibaldi Park, Canada topographic regions: glacier park shaped by alpine glaciation and volcanic activity program: exposion to hydro erosion

After spending so much time on this project one can conclude that the development of territories can be as multi-faceted as the landscapes themselves. So many different aspects have an impact on the evolution, therefore a prediction is pretty much impossible. Yet, one thing is certain, mother nature will come up with something fascinating.

VU landscape and territorial strategies SS 2020 Milena Thurner 11716501

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[CODE]

Chapter Title

Garibaldi Park, Canada

For my project I chose the Garibaldi Provincial Park on the coastal mainland of British Columbia, Canada. The park is located just about 70 kilometers north of Vancouver and is named after its towering 2.678 meter peak, Mount Garibaldi.

The geological history, diverse vegetation, snow-capped mountains, iridescent waters, abundant wildlife and scenic vistas all contribute to the parks natural beauty that it is known for.

I cropped out a small area that still gives an impression of the fascinating variety of the landscape.

My chosen frame contains several waters like part of the Pitt Lake or the Tingle Lake but also mountain ranges, including the Osprey Mountain, are visible and that is what I started out with.

What I wanted to have a closer look on was how this specific landscape could possibly develop over time according to an erosion that is applied to it.vv

topographic regions: glacier park shaped by alpine glaciation and volcanic activity program: exposion to hydro erosion

VU landscape and territorial strategies SS 2020 Milena Thurner 11716501

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Hydro Erosion initial terrain

1000m x 1000m

Garibaldi Park, Canada

I decided to expose the landscape to a hydro erosion and set it on a runtime of 120 frames. This mechanical process is caused by precipitation that carries sediment with it.

During heavy rain, water rushes down the cracks and the moving water flows against the banks and riverbeds.

This action of dislodging and transporting rock particles leads to valley formations. As a result, the eroded landscape gets a lot more detail than the initial one.

In my simulation, it is mainly caused by the spread iteration parameter, that was set quite high and that causes long and deep incisions. Also, the removal rate is rather low, so the amount of debris that is carried away by the wind is small and the rocks are pilling up at the bottom.

Another striking feature of the hydraulic eroded landscape are the rounded ridges.

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Garibaldi Park, Canada

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height map initial terrain contour lines initial terrain

5m distance Garibaldi Park, Canada Garibalid Park, Canada

height map eroded terrain contour lines eroded terrain

5m distance Garibaldi Park, Canada Garibaldi Park, Canada

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Peter Jensen

Vu Landscape and territorial strategies ss2020

Image description: Patterns in the salt

Tectonics of desiccated

Year: 2020

Landscapes

Location: Utah, USA

Image description: Algorithmic

erosion

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Function:

The Project seeks to investigate how the presence of anthropogenic erosion works in symbiosis with natural forces in reshaping landscapes. Specifically, it investigates the Salt desert areas around the Great Salt Lake in Utah, that has emerged, as the Salt Lake is shrinking due to mineral exploration in the area and the need for fresh water to accommodate the expansion of Salt Lake City. In detail, the traces in the salt, are investigated to document the tectonics of the erosion, driven by humans and nature.

The ground of salt and minerals acts as a canvas, where the very essence of the relationship of humans and nature is depicted with indefinite resolution. In an almost poetic way, it displays the relationship, as indefinite amounts of salt grains are moved by the water streams, released by the mineral farms, out into the desiccated salt desert. As algorithms capable of imitating natural erosion raise the question of a second nature, where algorithms act in symbiosis with biology, it also raise questions on the relationship of humans to the origin, the first Nature.

Filter: Great Salt Lake territory

Topographic regions: Dried out salt dessert

Programs: Natural reaction on antropocenic dessication

Name: Peter Marius Jensen SE Städtebau und Raumplanung IOUD Innsbruck

Detail investigation of the tectonics

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Image description:

Desiccation process 1984

Satellite image of the Great salt lake.

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Year: 1984

Location: Utah, USA

Image description: Satellite image of the Great salt lake.

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Year: 2020

Location: Utah, USA

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Description

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Patterns in the salt

Year: 2020

Location: Utah, USA

Description image2: Algorithmic erosion and flowlines

Function: Investigating the patterns in the Salt.

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Morphology of Patterns Description: Water from the nearby mineral industry floating out into the salt desert.

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Sonja Mair am Tinkhof

Vu Landscape and territorial strategies ss2020

the way This semester I concerned with the question: What effects do natural influences have on our landscapes? What form can landscapes take over the time?

In order to be able to carry out these analyzes in the best way, I decided to work in a familiar environment. It is an area near my home in Italy - Lappach, north in the Alps.

This area is crossed by two deep gorges, through which a river flows. Because the gorges converge, they merge.

There are several waterfalls along the course of the river.

Throughout the area, the rock is very brittle, which often results in rock breaks - mainly after heavy rainfall or in the spring after thawing. The sediment also tends to slide.

Most of the vegetation is very sparse and young. Perennial plants are most common, which is due to the fact that erosions often occur.

Filter: territory_northern Alps Topographic regions: mountainous gorge

Programs: natural erosion

Actor+Agents: Sonja Mair am Tinkhof 11822225

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terrain Filter: territory_northern Alps

Topographic regions: mountainous gorge

Programs: natural erosion

Actor+Agents: Sonja Mair am Tinkhof 11822225

[03]

There are strong seasonal differences in the Northern Alps, be it weather and erosion. The gorge reflects these natural events. Every time I hike through the gorges, I can see changes. These are due to the aggressive natural erosion in this area. The path into the gorge always leads along the course of the river until the first waterfalls [01]. The force of the water has formed a hole of water below each of the waterfalls. On this side of the gorge you hike up over brittle sediment [02]. Due to the frost in winter, the rock has got rifts and is now crumbling. Sometimes whole boulders block the way.

The existing path along the opposite course of the river is hardly recognizable. The heavy rain in spring softened the ground [03] and the debris slided in several places into the river. Where the protective vegetation is missing, the soil has been eroded much more.

[01]

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precipitation Filter: territory_northern Alps

Topographic regions: mountainous gorge

Programs: natural erosion

Actor+Agents: Sonja Mair am Tinkhof 11822225

Since the area to be explored is heavily influenced by water, I mainly work with water erosion, rainfall and water flow. This works mainly with the two main rivers through the gorges and the smaller tributaries, which also run into the riverbed. Precipitation includes rain, heavy rain and also snow.

Climate change is increasingly bringing heavy rainfall. The question therefore arises as follows: How does the landscape behave during heavy rainfall in the next 50 years?

Heavy rain slowly forms many small side valleys, which each merge into the two main gorges. These tributaries bring the sediment of erosion into the main riverbed.

It is important to look under the water layer. The most interesting details can be found in several areas of the waterfalls [01]. An important aspect here is the erosion underwater, which has an enormous impact on the entire landscape.

[01]

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change Filter: territory_northern Alps Topographic regions: mountainous gorge

Programs: natural erosion

Actor+Agents: Sonja Mair am Tinkhof 11822225

[03]

Based on the estimated conditions in 200 years, the erosion gets more aggressive. Also in the examined area there are often strong erosions in the area of the riverbank. The gorges dig remarkably quickly into the surrounding landscapes. To the side there are narrow, small valleys that merge into the main gorges.

The slopes to the gorges become steeper, but these themselves widen and become flatter. Because the brittle rock [03] breaks and the loose sediment slides down.

The constantly changing vegetation does not give the soil enough stability.

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[02] detail

50 years later

[03] detail

200 years later

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Tamer Acar

Vu Landscape and territorial strategies ss2020

Stubai Valley My name is Tamer Acar and I am studying the lecture VU Landscape and Territorial Strategies in the group landscape. We are analyzing different types of landscapes and rebuilding them, to get interesting and for the future helpful Information. We are living in the year 2020, the atmosphere and the vegetation was never as important as it is now. Glaciers are melting causing extreme environment changes around the World, the average temperature is rising as the water in the oceans. So it is important to study these points and collect Information. In my project i am analyzing my nearest environment, my hometown the Stubaivalley. The topography is 30 km away from the city Innsbruck and 30 km far away from the Stubaier glacier. The Lowest point is about 900m above sealevel, the highest about 3500m above sealevel. Why this landscape ? Besides that it is a very interesting and valuable place, it is a good topography to show my point of this semester. I am analyzing the hydro erosion in the alps with realistic settings and aspects. Analyzing how the water is flowing and causing mountain Peaks to be Rocky. The settings for the Erosion, have been chosen in relation to the environment.

After I rendered the erosion from Frame 1 till 10, I could clearly see how the settings had effected the mountain. In general the mountainsides lost a lot of volume due to the water which washed away the ground. In this process something very spectacular happened. The mountain peaks got a very steep contour and I could see the Geometry of the Mountain peaks in a sharp form. So as the hydro erosion effected the mountain the ground underneath the peaks got washed away and the rocky peaks stayed. Beside the peaks I could see another very interesting fact. After the erosion I could see how the contour lines of the valley got very smooth and symmetrical. The explanation for that is very easy when you think about it, as the water runs down the mountain it collects it self in the valley, due to the steep landscape the water also runs down the valley and has left a very smooth ground contour as we can see in riverbeds.

Located in Austria / Tirol 30km far away from IBK Alpine Region Lowest point: 900m above sealevel.

Highest point: 3210m above sealevel.

Hydro erosion due to raindrop and spring water.

VU Landscape and Territorial Strategies SS2020 TAMER ACAR

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A01

Topography

Satellite

The topography is 30 km away from the stubaier glaciar 3210 m. the area has a high hydro erosion due to large raindrops and large amount of saved spring water in the mountains.

12km to 12km

Average temperatur : 8-10 c°

Stubai Valley

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Topview 3D-Model

Perspective 3D

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Stubai Valley

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Landscape without Erosion

Rendering with Skylight

B02

Landscape with Hydro Erosion

Rendering with Skylight

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Hydro Erosion

Stubai Valley Located in Austria Tirol

I want to give you short explanation about the Settings: The bank angle has been set on 40, this has the effect that the erosion effects more the mountainside, so I can analyse the full potential about the water flow.

The spreadIteration has been set to 30, this gives me a realistic spreading of the erosion.

Removal rate has been set to -0.1, because the Stubaivalley is outstandingly windy and has nearly no straight surfaces, the water is always in movement.

Setting the grid bias to 0 helps me visualize the water movement and the erosion.

Putting the ramp up to 6 gives me a slower erosion and is a big help in analyzing in detail.

Precipitation amount and density are on a high amount, this setting gives me a intense erosion. The most important setting is the debris flow spread, In my erosion it is at 5, it controls how smooth the waterflowlines are visualized on the mountenside.

Rendering without Skylight Hydro erosion due to raindrop and spring water.

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D01 Topview Rendering without Erosion 9km to 9km

C01 Topview Zoom

The marked area shows the valley.

The natural valley has a asymmetrical landscape structure.

The contour lines are not in a specific order, more chaotic.

2.5km to 2.5km The Hydro Erosion is creating mountain ridges due to the waterflow.

C02 Topview Zoom 2.5km to 2.5km The Mountain Ridges are controlling the waterflow in the mountain side. The contour lines are getting smoother in the troughs.

D02 Topview Rendering with Hydro Erosion.

9km to 9km The process of the Hydro Erosion forces the water to flow into the valley. Due to the fact that the Stubaier valley has an inclinaten, the valley gains on width and gets a symmetric smooth contour line.

151

Kristian Walder

Vu Landscape and territorial strategies ss2020

Shade for Guatemala This Project`s focus lies in demonstrating how deforestation and roding of untouched rainforests can lead to reshaping of massive areas of land, due to erosion and landslides. In this case, in the Guatemalan highlands, massive slopes of untouched rainforests are roded for sought after exotic wood and less dense farmland for shrubs plants.

Filter: Highlands of Guatemala

The Project proposes a possible solution on how to redensivy/ recreate a highly rooted topsoil which then again allows for larger areas of cultivation on top of the loose, though multiple erosions exposed, vulcanic bedrock.

Programs: Long-sighted planing on usefull reforestation

The method proposed here is to cultivate special shade grown coffee, which as the name states, can only be cultivated under larger trees and vegetation. They provide the rich mothersoil again with the much needed structural root support, aswell as protect it from too much sun exposure and thereby preventing it from drying out.

Topographic regions: Eroded Rainforests

Actor+Agents: Kristian Walder Ioud Uibk Innsbruck Se Städtebau und Raumplanung

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[01] [CODE]

[03]

Erosion 1 Thermal

Erosion 3 Hydro

Contour 0.1pt

Contour 0.1pt

Guatemala

Guatemala

[02]

[04]

Erosion 2 Thermal

Erosion 4 Hydro Contour 0.1pt

Contour 0.1pt Guatemala Guatemala

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[01]

[03]

Green = Cultivable Red = Exposed Rock

Green = Cultivable Red = Exposed Rock

After 5 Years

After 15 years

Guatemala

Guatemala

[02]

[04]

Green = Cultivable Red = Exposed Rock

Green = Cultivable Red = Exposed Rock

After 10 years

After 20 years

Guatemala

Guatemala

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Eroded Rainforest Guatemala

in

Rendered Terrain with Contour Lines and a Colour-overlay to visualize steep areas (red) and mellow areas (green)

Through overlaying a high resolution render of an artificially created landscape representing highly eroded areas in the Guatemalan Highlands, with a red-green colour-code, the project trys to emphazise the drastic change and shaping of landscapes through reckless and short sighted roding of rainforest.

Programs: Visualizing the area loss through erosion

6

161

Drenusha Lokaj

Vu Landscape and territorial strategies ss2020

Mount Mazama and Crater Lake In this exercise I looked out for exciting natural phenomena and decided to look more into volcanoes and craters/ calderas.

Filter: mountain region, volcano, crater

One of the largest calderas in the world is situated in Oregon, United States.

The Crater Lake is one of the deepest and most beautiful craters in the world.

Mount Mazama was destroyed during an enormous explosive eruption 7,700 years ago.

Topographic regions: crater

So much molten rock was exposed that the summit area collapsed and formed a large volcanic depression, or also called caldera.

Actor+Agents: LOKAJ Drenusha University of Innsbruck

Programs: erosion thermal erosion

Subsequent smaller eruptions occurred as water began to fill the caldera to eventually form the deepest lake in the US. My goal was, to analyse the landscape and look further into the crater.

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STEP 1 Filter: mountain region, volcano, crater Topographic regions: crater Programs: erosion thermal erosion

First I started with a terrain analysis. I noticed that the landscape around the crater varies a lot. Using erosions, I tried to bring out this contrast and make it more clearly recognizable.

top view: crater lake

erosion hydro: erodability 0.3 erosion rate 1.3 bank angle 86 spread iterations 15

On the western side of the crater higher and denser mountains can be seen. Though the landscape to the east of the crater is very flat.

thermal: erodability erosion rate cut angle

0.14 0.03 35

precipitation: amount 0.1 density 0.34 evaporation rate 0.04

Actor+Agents: LOKAJ Drenusha University of Innsbruck

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close up southeast top view: crater lake

erosion hydro: erodability 0.3 erosion rate 1.3 bank angle 86 spread iterations 15 thermal: erodability erosion rate cut angle

0.14 0.03 35

precipitation: amount 0.1 density 0.34 evaporation rate 0.04

close up top view: crater lake

The interesting part about thecrater lake, are the hidden islands in the crater itself.

The island one can see in the middle of the lake is called Wizard Island. Eruptions from new vents within the caldera built the base of Wizard Island, and also for other islands.

However, these have not reached the height to be visible at the previous depth of the lake, which is almost 600m.

In the erosion that I made, the lake almost covered Wizard Island, but I would also find it interesting to see how the landscape would change if the lake dried out, for example.

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For my last step I rebuild only the caldere to analyse how the crate would react to a drought.

The water started to disappear within the crater.

As the lake was drying out, hidden islands started to appear on the surface.

The crater and the landscape are getting a rougher texture and are rich in details.

top view: crater lake

erosion hydro: erodability 1 erosion rate 0.4 bank angle 12 spread iterations 74 thermal: erodability erosion rate cut angle

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precipitation: amount 0.1 density 0.34 evaporation rate 0.04

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Sabrina Dorner

Vu Landscape and territorial strategies ss2020

Desertification in Spain [00] In Spain 80% of water use goes in to artificial watering for agriculture. This leads to declining rivers, wetlands, springs and groundwater resources all of which feed the process of Desertification. Desertification is defined as “land degradation in arid, semi-arid and dry sub humid areas resulting from various factors, including climatic variations and human activities”. It occurs on all continents except Antarctica and its effects are experienced locally, nationally and globally.

Filter: Almeria//Andalusia//Spain

Topographic regions: Sierra Nevada Mountain Regions, Farmlands

Programs: agriculture, greenhouses

Actor+Agents: Agroponiente, Unica Group, CASI, Alhóndiga La Unión, Agroiris, Vicasol

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[01]

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Greenhouses and neighbouring mountain regions

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[02] Input Topography

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Almeria

[01/02]

In my work I am looking at an agricultural heavily used area in Spain called Almeria. Traditionally farmers there used to grow resource-saving dry crops like almonds, olives and wine but a few decades ago concerns started buying the land. So now the stretch along the coast is populated by thousands of greenhouses that grow plants like brokkoli, citrus fruit, peppers and salad which need a lot of water. As a result, the Landscape will eventually be facing desertification which manifests itself in a shortage of water, degradation of soil and erosion of the land.

I am going through several scenarios of erosion in the area, trying to see what the factors of desertification could do to the region. The taking away of groundwater could cause the plant cover in the nearby mountain regions to dry out. The plants would either be replaced by dryer plants that do not have as deep roots which cannot stabilize the ground anymore. Or there will be no plants at all, the soil dries out and starts eroding, transporting the soil downward and leaving behind Rocky Mountain tops. The eroded soil could get into the greenhouse areas as landslides, covering a large amount of the area and the rest of the flatlands would probably consist of hard, dried out soil. Wrong watering strategies and monoculture of plants wash nutrients out of the earth and lead to a saltification of the ground that leaves behind a crust in the farmland.

This hard and salty soil in flat desert areas mostly looks like a cobblestone pattern interspersed by cracks.

Filter: Almeria//Andalusia//Spain

Topographic regions: Sierra Nevada Mountain Regions, Farmlands

Programs: agriculture, greenhouses

Actor+Agents: Agroponiente, Unica Group, CASI, Alhóndiga La Unión, Agroiris, Vicasol

36°44’14’’N 2°44’31’’W

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Erosion

Filter: Almeria//Andalusia// Spain

My strategy was to try different erosion settings and see which ones come closest to the described Impacts that desertification normally has. The first pair of erosions was focusing more on the sediments going down the mountain which formed kind of even ponds of sediments in between the mountains.

Topographic regions: Sierra Nevada Mountain Regions, Farmlands

Programs: agriculture, greenhouses

Actor+Agents: Agroponiente, Unica Group, CASI, Alhรณndiga La Uniรณn, Agroiris, Vicasol

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Recess area Acuumulation of Sediments Loose sediments start getting into the flat areas, burying the farmland [01]

In the second pair of erosions I also added water that goes through the area after it dries out, washing out nutrients and forming the mountains and flatlands into a more dramatic landscape than in the first part.

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Crust consisting of harder soil and salt in cobblestone like formation [03]

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Erosion 04

Filter: Almeria//Andalusia// Spain

Topographic regions: Sierra Nevada Mountain Regions, Farmlands

Programs: agriculture, greenhouses

Actor+Agents: Agroponiente, Unica Group, CASI, Alhรณndiga La Uniรณn, Agroiris, Vicasol

Detail 01 Detail 02

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In addition, I reran the erosions on smaller parts of the area to get a more detailed view on the affects. The first one shows the intersection of mountains and farmlands in the north-western part of my area. You can see how the sediments go into the valley as landslides and afterwards the streams cut through the dry flatlands. In the second detail I am zooming into the main mountain area, making visible how rocky and sharp the mountaintops can become after all the loose earth is gone.

Filter: Almeria//Andalusia//Spain

Topographic regions: Sierra Nevada Mountain Regions, Farmlands

Programs: agriculture, greenhouses

Actor+Agents: Agroponiente, Unica Group, CASI, Alhóndiga La Unión, Agroiris, Vicasol

[04.2]

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Leonhard Schedel

Vu Landscape and territorial strategies ss2020

Deforming Landscapes Landscapes deform and are always in a process of change.

They are customized by e.g. designed and exposed to the climate and other natural influences. But what if two different locations that are completely geographically separated are exposed to the same natural influences. What would they look like?

In my project I exposed Innsbruck and South Cove, located in the Grand Canyon National Park, to the same climatic conditions. To compare the same shape changes at different locations, I compared the locations Innsbruck and South Cove using the same parameters.

I made two erosions per location with the same parameters. Erosion 1 for Innsbruck therefore has the same settings as erosion 1 for South Cove. I compared the results to how much influence the parameters have on the landscape.

Topographic regions : Alpine Landscape Inntal Valley Desert Grand Canyon National Park Location 1: Innsbruck, Inntal Austria Location 2: South Cove, Arizona Actor+Agents: Leonhard Schedel University of Innsbruck

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Satellite Image

Topographic regions: Alpine Landscape Inntal Valley

Innsbruck is located at 574 m in the Tyrolean Inn Valley. It´s urban area extends to over 2,500 meters in the north, and with the Patscherkofel by 2,247 m to the southeast.

The city location is at the intersection between Inntal (west-east) and the Wipptal (north-south).

Location: Innsbruck, Inntal Austria

Innsbruck generally has a temperate climate, but with an alpine character.

The weather phenomenon of the foehn is very well known, which is favored by the north-south orientation of the Wipptal. The warmest months are July and August with an average of 18.1 and 17.4 ° C, the coldest December and January with -1.1 and -2.8 ° C on average.

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Satellite Image

Topographic regions: Desert Grand Canyon National Park

Soth Cove is located in Grand Canyon National Park and a subarea of the 450-kilometer-long gorge of the Grand Canyon. The Canyon is in the north of the US state of Arizona.

Location: South Cove, Arizona

Tthere are regularly freezing temperatures from November to March; from May to September the temperature rises regularly above 20 ° C during the day; July is the warmest month with an average of 29 ° C ,while January is the coldest month with an average temperature of −8 ° C.

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Settings (High) Erosion 1 Frame 1:

Settings (High) Erosion 2 Frame 1:

Grid Bias: 0,9 Slope Factor: 0,8 Sediment Capacity: 10 Density: 0,64

Grid Bias: 0,9 Slope Factor: 0,8 Sediment Capacity: 10 Density: 0,64

Location: Innsbruck, Inntal Austria

Location: South Cove, Arizona

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Settings (High) Erosion 1 Frame 20:

Settings (High) Erosion 2 Frame 20:

Grid Bias: 0,9 Slope Factor: 0,8 Sediment Capacity: 10 Density: 0,64

Grid Bias: 0,9 Slope Factor: 0,8 Sediment Capacity: 10 Density: 0,64

Location: Innsbruck, Inntal Austria

Location: South Cove, Arizona

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2.4 Settings (Low) Erosion 3 Frame 1: Grid Bias: -1 Slope Factor: 0 Sediment Capacity: 0,44 Density: 1

2.6 Settings (Low) Erosion 4 Frame 1: Grid Bias: -1 Slope Factor: 0 Sediment Capacity: 0,44 Density: 1

Location: Innsbruck, Inntal Austria

Location: South Cove, Arizona

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Settings (Low) Erosion 3 Frame 20: Grid Bias: -1 Slope Factor: 0 Sediment Capacity: 0,44 Density: 1

Location: Innsbruck, Inntal Austria

Settings (Low) Erosion 4 Frame 20: Grid Bias: -1 Slope Factor: 0 Sediment Capacity: 0,44 Density: 1 Location: South Cove, Arizona

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Conclusion

The grid bias and density with high parameters had the greatest impact on the landscapes. In the Inn Valley, more contour lines and wider mountain passes and valleys were formed.

In South Cove, on the other hand, you only notice small changes. The landscape equalized and became calmer due to the reclamation of some gorges. In addition, the rivers and lakes spread a little.

The low settings did the opposite. Both landscapes, both in the Inn Valley and in the South Cove gorges, became more winding and exciting. The contour lines became more and the rivers, lakes and valleys became smaller.

In the further course I want to change the settings of the parameters so that I have an even greater input on the landscapes in order to achieve major changes.

199

Lukas Rangger

Vu Landscape and territorial strategies ss2020

Volcanism Since the early days in our earth’s history several natural events were giving and still are givingour planet it’s shape.

One of these specific eveents is volcanicity. Depending on the intensity of a volcano eruption, volcanism can lead to an immense climat change.

Topographic regions: island mountain volcano sea

Volcanism is one of the scientists theories about the extinction of the diying out of the dinosaur. In the 19th century the erruption of the Indonesian volcano Tambora caused a climate change bringing cool summers worldwide and hunger crisis in North America and Europe.

Location: Volcano Stromboli Italy

There are countless volcanos on the ocean’s floor and about 1,500 active ones above the earth. Mainly volcanos are located where tectonic plates meet.

Lava is bubbling miles underneath the earth, waiting to burst through the surface of a volcano or through the fractures in a crust. But if a volcano erupts, he does not only throw out lava, he also spies out ash, rocks, stones, hot gases and/ or toxic gases and C02. These hot gases can move downhill with a speed of 161 km/h, while it is burning everything in its way. Lava usually has a temperature between 700 and 1.200 °C.

Programs: erosion lava flow sediment

Actor+Agents: Lukas Rangger University of Innsbruck

Due to its hot temperature and being a fluent mass, lava is forming the landscape by finding a way down the slopes of a volcano giving him a new shape. The hot lava can evoke new canyons and craters by erosion.

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Topographic regions: Volcanic Landscape Volcano

The island of Stromboli is the target of the investigation, because the volcano himself is forming a 12,6 km² big island being surrounded by the Tyrrheninan Sea. According to this the complexity of the topic volcanism can be reduced by focusing on a small piece of land which is patterned by its permanent active volcano.

Location: Stromboli Italy Programs: Infrastructure erosion lava flow sediment Resolution: 3500x3500

Moreover, Stromboli attracted my attention as it is said that the island is populated since about 7000 years and that it was already known to the ancient Greece. In my opinion that sounds crazy as the crater opens in unsteady time periods of minutes or hours what leads to smaller or bigger eruptions.

Heavy eruptions of Stromboli even let to a increase at the beginning and to a decrease of the sea level at the end of the eruption.

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Topographic regions: Volcanic Landscape Volcano

The phenomena of volcano eruption was always dangerous for life on earth. But it is also shaping our planets landscape. The focus of this analysis is to explore how eruptions of the volcano Stromboli in the Italian sea, could transform its island.

Location: Stromboli Italy Programs: Infrastructure erosion lava flow sediment Resolution: 3500x3500

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Topographic regions: Volcanic Landscape Volcano

On the one hand it is true that many people on earth living close by a volcano are living endangered, because of the volcano’s activity. But one the other hand volcanism also comes along with positive things like excellent soil for agriculture. Therefore f.e. our ancestor settled down next to dangerous active volcanos like the Vesuv and found wonderful cities like Naples. In addition, one should keep in mind that volcanism is pattering landscape, once lava is cooling down and transforming itself into stones and rocks.

Location: Stromboli Italy Programs: Infrastructure erosion lava flow sediment Resolution: 3500x3500

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211

Noah Balla

Vu Landscape and territorial strategies ss2020

Polar Ice Cap Pools

[CODE]

The basis behind the research and design concept of my landscape midterm project was the polar ice caps in Greenland. Recently, satellite imagery has become strong enough where they started to examine and discover small turquoise dots on these impeccable white ice sheets. These dots are lakes that are forming on the ice due to the effects of global warming. Over time, streams start to form on the ice during the summer months and funnel into these pools of water, creating lakes. Over the winter months they freeze over, but not completely, making them the first spot for water to fill up again next summer.

I took inspiration from this and tried to simulate these effects to see if the software of Houdini can properly predict these conditions in the case that this started to happen in other places around the world. Also because global warming is such a growing global issue, I found it important to use this as an awareness that the flooding can become an is-sue in a widespread region of areas.

In my project, I tried to form my own landscaping, mimicking certain aspect of the Greenland terrain in the satellite image I have been studying. From there, I change the hydro and thermal erosion levels to a fairly high range in order to speed up the process of the creation of these lake forms. What I no-ticed from doing this is that the smaller peaks within the landscape began to diminish and the contour curves flat-tened out. In the regions where the landscape was alre-ady relatively flat, the peaks would erode to these points, creating a couple of valley or stream spots, that funneled into the low point.

Filter: Arctic Typography Topographic Region: Ice Caps Programs: Generation and expansion of streams and pools Actor+Agents: NASA, NOAA, NJIT

215

[CODE]

Ice Cap Pools

Filter: Arctic Typography

The main problem with this landscape is that the terrain is so flat, that when these streams and pools are formed, it is hard for the landscape to flatten out again over the winter months. The water then flows to the ocean, raising sea levels, and then the ocean surges further and further onto the land with storms. It is a exponential process that injures the landscapes identi-ty as well as posses a threat to the ecosystem.

Topographic Region: Ice Caps Programs: Generation and expansion of streams and pools Actor+Agents: NASA, NOAA, NJIT

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Polar Ice Cap Pools

[CODE]

Due to these changes in the landscape and climate, the ecosystem, mainly the wildlife of animals, get affected be-cause the flooding and warmer temperatures makes their environment less ideal. Increased amount of precipita-tion and water flow causes deeper divets that make the rivers easier to grow year after year meaning the pools will grow more as well. This will create larger slopes and craters in the ice which can grow more from the increa-sed angle and exposure from the sun and the increased amount of water being retained in these spots.

The basis of my study and project will try to simulate these con-ditions in a way that correlates to the satellite changes and can predict over time how much different the land-scape can be with a constant change. We are experien-cing exponential change which would make conditions potentially even worse than expected. In the next pages, you will be able to see the progression of erosion on the landscape and how the effects previously mentioned are being displayed. The renders show a detailed version of how the peaks and slopes start to take on more detail through erosion down the side of the slope and the flat ice caps show the increased area of pools on the surface. Over time they grow so much that some overlap. Also the increased water flow chews away at the bottom of a por-tion of one of the mountain sides, making a large water basin that can hold water that will eventually feed or spill onto the ice surface.

Filter: Arctic Typography Topographic Region: Ice Caps Programs: Generation and expansion of streams and pools Actor+Agents: NASA, NOAA, NJIT

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Erosion 1

Time Stamp 5

Erosion 2 (cont.)

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Erosion 3

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Erosion 2

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Contour Comparison

Original Landscape

After Erosion 1

After Erosion 2

After Erosion 3

After running multiple simulations of erosion on the created landscape, I was able to properly analyze the ice cap surface pools. The mountains along the coast began to flatten as displayed through the loss of contours and definition going down the slope. In the right sector of the landscape, the pools grew into each other and then created a large region of low level landscape that is deep and wide, being able to carry more water. The edge of the water basin becomes more steep and the bottom becomes more flat and wide. This analysis proves the settings to be accurate to predicting fu-ture effects on this landscape and around the world.

223

Thomas Rothschopf

Vu Landscape and territorial strategies ss2020

Melting Glaciers a glacier is a persistent body of dense ice that is constantly moving under its own weight. glaciers form where the accumulation of snow exceeds its melting over many years. glaciers cover about 10% of the earths land surface, mostly in the polar regions but they can also be found on high mountain ranges on every continent. glacial ice is the largest reservoir of fresh water on earth. many glaciers from temperate, alpine and seasonal polar climates store water as ice during the colder seasons and release it later in the form of meltwater, as warmer summer temperatures cause the glacier to melt, creating a water source that is especially important for plants, animals and human uses. since glacial mass is affected by long-term climatic changes, glacial mass changes are considered among the most sensitive indicators of climate change and are a major source of variations in sea level. glaciers not only transport material as they move, but they also sculpt and carve away the land beneath them. a glaciers weight, combined with its gradual movement and melting water, can drastically reshape the landscape over thousands of years. the following example shows a region, located in the biggest national park of austria, and explores how glacier erosions have created large green valleys with two big lakes in it, which then have been transformed by humans in the last century.

Topographic regions: Alpine Landscape Glacier

Location: Hohe Tauern Austria

Programs: Infrastructure generation of energy Sports and Tourism

Actor+Agents: Thomas Rothschopf University of Innsbruck

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Satellite Image

Topographic regions: Alpine Landscape Glacier

the glockner group is a sub-group of the austrian central alps and is located in the centre section of the high tauern. the highest summit of the glockner group and also the highest peak in austria is the groĂ&#x;glockner (3.798m), which gives the mountain group its name. also found here is the pasterze, the largest glacier in austria. another famous mountain and a popular ski area in the group is the kitzsteinhorn (3.203m). east to this mountain two huge water reservoirs - stausee moserboden and stausee wasserfallboden - are located. the water is gathered primarily from melting water of the pasterze and is used to generate electricity. the three dams were completed after the second world war in the 1950s and were funded with money from the marshallplan. The 120m high dams can hold back a total water volume of 166 million mÂł and became a symbol of rebuilding the country after the war.

Location: Hohe Tauern Austria

Programs: Infrastructure generation of energy Sports and Tourism

Resolution: 6000x6000 scale 1:24.000

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Landscape

Topographic regions: Alpine Landscape Glacier

what is interesting about these infrastructure projects is, how the engineers and workers have transformed the existing natural landscape in a short period of time to fit it to the needs of the local population. without the dams the landscape would look completely different.

The project tries to explore how erosions of the melting glaciers would affect this landscape in the next couple of thousand years.

Location: Hohe Tauern Austria

Programs: Infrastructure generation of energy Sports and Tourism

Resolution: 6000x6000m contours every 10m scale 1:24.000

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Erosion Process

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Resolution: 6000x6000m

Location: Hohe Tauern Austria

Location: Hohe Tauern Austria

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Erosion Process

Resolution: 6000x6000m

Resolution: 6000x6000m

Location: Hohe Tauern Austria

Location: Hohe Tauern Austria

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Erosion

Topographic regions: Alpine Landscape Glacier

since the early 1900s, many glaciers around the world have been rapidly melting. human activities are at the root of this phenomenon. specifically, since the industrial revolution, carbon dioxide and other greenhouse gas emissions have raised temperatures, even higher in the poles, and as a result, glaciers are rapidly melting, calving off into the sea and retreating on land. scientists project that if emissions continue to rise unchecked, the arctic could be ice free in the summer as soon as the year 2040, as ocean and air temperatures continue to rise rapidly.

Location: Hohe Tauern Austria

Programs: Infrastructure generation of energy Sports and Tourism

Resolution: 6000x6000m contours every 10m scale 1:24.000

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Synthetic Landscape Lab, Prof.Claudia Pasquero Institute of Urban Design, University of Innsbruck

[BOOKLET]

VU Landscape and Territorial strategies vs SE City Vision

[FACULTY] TUTORS: Prof.Marco Poletto Maria Kuptsova Apostolos Mouzakopoulos

ASSISTANTS: Emiliano Rando Elena Hasanramaj

[STUDENTS] Linda Kick Armin Aziz Lukas Rangger Caspar Nagenrauft Maja Link Evis Storke Milena Thurner Julian Edelmann Noah Balla Luca Guarino Nico Oberbeck Michael Hetzenauer Patrick Testerman Mirco Fantini Peter Jensen Sabrina Dorner Sonja Mair am Tinkhof Aileen Larcher Stepanie KĂźng Alexandra Morales Tamer Acar Alex Kerschbaumer Thomas Rothschopf Denis Novotny Zoran Mirceta Drenusha Lokaj Eren Kargi Eugen Halbhuber Fatama Baltaci Katharina Kienzel Kristian Walder Synthetic Landscape Lab, Prof.Claudia Pasquero Leonhard Shedel Leopold Pretzel Institute of Urban Design, University of Innsbruck

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