Document [original]

Virtual Worlds—Real Decisions: Model- and

Visualization-based Tools for Landscape Planning in

Switzerland

Authors: Walz, Ariane, Gloor, Christian, Bebi, Peter, Fischlin, Andreas,

Lange, Eckart, et. al.

Source: Mountain Research and Development, 28(2) : 122-127

Published By: International Mountain Society

URL: https://doi.org/10.1659/mrd.0965

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Changes in the traditional Alpine

landscape

Traditional Alpine landscapes are consid-

ered to be one of the major elements of

Switzerland’s cultural heritage, as well as

an important resource for national and

international tourism. These landscapes

have evolved over centuries of agricultural

use. Nowadays, slow processes, such as

changing cultivation patterns or gradual

land abandonment, as well as high-impact

interventions, eg extensive construction

projects or infrastructure development,

contribute to the rapid and profound

alteration of Alpine landscapes (Box 1).

Computer-based tools in landscape

planning

To make it easier to assess long-term

effects in landscape planning, decision-

makers need the best information avail-

able. Computer-based tools are able to

deal with the complexity of the decisions

that need to be taken, and offer appropri-

ate techniques to visualize and communi-

cate relevant information. In the present

article we distinguish between 2 types of

computer-based tools:

1. Models serve to generate and add

information in the planning process.

They are abstract and well-defined

depictions of the real world that help

us to break up and reconstruct com-

plex systems (ie nature and society)

Virtual Worlds—Real Decisions: Model- and

Visualization-based Tools for Landscape

Planning in Switzerland

Ariane Walz

Christian Gloor

Peter Bebi

Andreas Fischlin

Eckart Lange

Kai Nagel

Britta Allgöwer

122

Mountain Research and Development Vol 28 No 2 May 2008: 122–127 doi:10.1659/mrd.0965

Prominent construction projects in Switzer-

land, such as the Sawiris luxury resort in

Andermatt planned by Orascom Hotels &

Development, Cairo (Egypt), or the idea of a

hotel and apartment tower at Schatzalp,

Davos, demonstrate how rapidly Alpine land-

scapes may undergo major changes. Deci-

sions on whether or not such changes are

supported by policymakers should be based

on the best information available and in agree-

ment with the local population to ensure long-

term sustainable development. The present

article investigates the potential and limita-

tions of computer-based tools to support such

decisions in the area of landscape planning,

with a particular focus on Alpine landscapes.

Large construction projects planned

in the Swiss Alps

•Sawiris luxury resort, Andermatt, Switzer-

land: “Egyptian tycoon plans Alpine oasis.

[…] One of the Middle East’s biggest hotel

groups is on course to transform Ander-

matt into a luxury resort, complete with a

golf course and a pool with its own sandy

beach.” (Imogen Foulkes, BBC News,

9 April 2007, http://news.bbc.co.uk)

•Schatzalp Tower, Davos, Switzerland: “After

a vote by the population of Davos on

10 October 2004, the local government

decided upon alterations to local spatial

planning in order to enable the construc-

tion of the 105-m high tower at the

Schatzalp.” (Translated from P. App, “Die

Schatzalp—vom Zauberberg zum Zauber-

turm.” Speech at the Summer University

Davos 2007, 24 August 2007)

FIGURE 1 Application of up-to-

date visualization techniques in

landscape and spatial

planning—here at an exhibition

on the occasion of the ETHZ’s

150th anniversary, 22 April to

8 May 2005 in Zurich. (Images

by authors; photos courtesy of

ETHZ)

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Development

123

and to predict their reaction as a

response to external changes. In the

context of landscape planning, they

are often referred to as decision-sup-

port tools. Although they do not nec-

essarily have to be computer-based,

they often appear as software applica-

tions.

2. Visualization tools help to communicate

complex information in a comprehen-

sive, intuitive manner (Figure 1).

Apart from well-processed graphs,

such as diagrams, tables or maps, pho-

torealistic or, in general, image-based

depiction has become common in

landscape planning. Visualization does

not have to be computer-based. But

the increasing availability of digital

information and advances in visualiza-

tion technology have made computer-

based visualization a powerful and

attractive tool.

Within the National Research Pro-

gram NRP48 on “Landscapes and Habitats

in the Alps,” several projects focused on

landscape modeling and visualization.

These projects were brought together and

discussed with regard to their contribu-

tion to the development of computer-

based planning tools in Synthesis V of the

NRP48 on virtual representation.

Visualization in landscape planning

Especially when visual qualities of the

landscape are a key focus of the plan-

ning process, illustrations are needed,

as planners and decision-makers must

be able to see and to demonstrate to

others how a development might

change the appearance of the land-

scape. Visualization has been used for

centuries, for instance in architecture,

and is slowly playing a more important

role also in landscape planning. From

drawings and 3D cardboard models to

photomontages, the latest developments

in visualization technique are fully com-

puter-generated views of the planned

intervention.

Fully computer-generated visualization

allows changing the viewpoint in an arbi-

trary way to reveal new perspectives. This

can give completely new insights. For

FIGURE 2 Example of visualization of the planned visitor center for the Swiss

National Park at Zernez, Canton of Grisons, Switzerland. (A) 3D model created by

the architect, (B) profiles for the planned building, (C) computer-based simulation

of the building. (Images courtesy of Pro Chaste da Zernez)

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Ariane Walz, Christian Gloor, Peter Bebi, Andreas Fischlin, Eckart Lange, Kai Nagel, and Britta Allgöwer

Mountain Research and Development Vol 28 No 2 May 2008

124

instance, such computer visualization effec-

tively demonstrated that the planned visi-

tor center for the Swiss National Park

would cover the line of sight to the histori-

cal chateau in Zernez, Canton of Grisons

(Figure 2). This had not been obvious

before, either from the 3D cardboard mod-

el or from the in-situ profiles. As a result,

the new center was realized at a different

location, leaving the surroundings of the

historical building complex untouched.

Once the required input data are

available and the system is set up, comput-

er-generated visualization also drastically

reduces the time needed to create images

of alternative scenarios. Not only “real

world” data can be used as inputs for such

visualization: the numerical output of a

model can also be transferred directly into

a photorealistic representation based on

this technique.

Modeling in landscape planning

The user-friendliness and number of mod-

el-based tools for planning are consider-

ably lower compared to visualization tools.

Still, also in the area of modeling, we find

computer-based tools. One example is

RiskPlan at the Swiss Federal Office for the

Environment (FOEN) and the Swiss Fed-

eral Office for Civil Protection (FOCP).

This is a strongly simplified risk analysis

tool that provides first-order support for

decision-making in risk and natural haz-

ard management. Another example, partly

enhanced within the NRP48, is the protec-

tion forest model by Peter Brang of the

Swiss Federal Institute for Forest, Snow

and Landscape Research (WSL), a tool to

optimize the protection function of moun-

tain forests against rockfall. These applica-

tions are niche products addressing very

specific and well-defined tasks.

However, in landscape planning the

complexity of decisions is often high and

encompasses multiple, interdependent

aspects, such as land use, economy, biodi-

versity, and recreation potential. When

multiple aspects of the landscape have to

be combined in practical planning, mod-

el-based tools are hardly used. One of the

Selected NRP48 modeling and visualization projects

•ALPSCAPE: Within the ALPSCAPE project, future scenarios of regional development were simulated for the region of Davos,

one of Switzerland’s major tourist regions. A key focus was the integration of multiple modeling approaches, including 3 simu-

lation models (economy, natural resources fluxes, land use) and a valuation tool (based on ecosystem services). Within a par-

ticipatory process, the knowledge base was established to develop 3 scenarios influenced by agricultural policy, climate

change, and the realization of a big sports event. Profound changes in agricultural policies showed the largest impact on the

landscape, but economic consequences were minor compared to the impact of a climate change scenario with decreasing snow

reliability. Among the evaluated ecosystem services, protection from snow avalanches by forests was the most important.

•ALPSIM: The model simulates hikers’ behavior as a response to landscape change and interactions between them. The virtual

hikers move in a virtual landscape with their plans and expectations, and they experience the landscape. At the end of the

hiking day, their satisfaction is measured, and consequences are drawn from this satisfaction for the next day. The scenarios

encompassed the expansion of forest and the closure of lifts and mountain railways over the summer in the study area of

Schönried, near Gstaad. The project focused mainly on the methodological and technical aspects of agent-based modeling,

visualization, and animation (Figure 3). It resulted in strong advances in computer realization, and revealed research gaps in

the explanation of tourist behavior, and thus the knowledge base, needed to calibrate the model accurately.

•IPODLAS: Linking dynamic modeling with a Geographic Information System and real-time visualization was the overall, mainly

technical objective of the project. By formulating detailed use cases, software architecture was developed that suited the

requirements of several case studies. Besides a case study on wildfires, another case study looked at the migration patterns

of the larch bud moth population in the Upper Engadine valley, Switzerland. In this case, the direct link between the spatio-

temporal (ecological) model, the GIS and the visualization tool made it possible to study and visualize these migration pat-

terns comfortably at different scales, ie from the entire Alpine arc to the extent of the Upper Engadine valley (Figure 4).

•SULAPS: A main focus was to identify the collective impact of multiple, independent “agents” (farmers) in response to chang-

ing agricultural policies. The model simulated scenarios of changes in agricultural policy and subsequent landscape impact

for 2 rural regions within the Canton of Grisons, Switzerland. To this purpose, an optimization model at the farm level was

combined with spatially explicit land use data and an assessment tool to measure changes in landscape structure. One of

the major findings shows that in a liberalization scenario, the number of farms within the 2 study regions decreases by about

20% until 2015, and agriculturally used land declines as well (Figure 5).

For more information on the 4 projects, see www.nfp48.ch

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Development

125

main reasons is that the interfaces

between different modules within such a

multidisciplinary model are hard to cali-

brate and often include many assump-

tions. This, of course, makes it difficult to

elaborate transferable, ready-to-use tools.

Another reason is that most land-

scape models to date have been devel-

oped within a research environment. The

outcome of a research project, however, is

hardly ever a fully operational tool. It

would require software developers and

special techniques to actually produce

such tools. One possible and promising

technique could be the formulation of

“use cases.” “Use cases” consist of small

narratives that reproduce the users’

requirements in great detail, and break

them down into a number of small indi-

vidual tasks requested from the computer

applications. The generation of “use cas-

es” is, among other things, a technique

for improving communication between

the actual user of a tool and its developer.

Although they have been used for many

years in software development, they have

hardly ever been applied in landscape

planning.

Apart from applying fully operational

tools, modeling can also be considered as

a sophisticated method to analyze existing

or newly surveyed data in a planning

process. For instance, the extrapolation of

an observed trend might not fully reflect

the expected development. But a simple

model can already give a better estimate

of future development.

Implementing models in planning:

potentials and current limitations

The following examples based on NRP48

models (Box 2) serve to highlight the

potential of state-of-the-art research,

and to demonstrate the problems in

developing highly complex operational

tools.

Example 1: Agricultural change and

tourism attractiveness

One eminent question that arises in dis-

cussions about landscape conservation in

the Alps tackles the consequences of agri-

cultural change for Alpine tourist regions.

To address this question, it appears logical

to hypothetically combine the highly com-

plementary NRP48 modeling projects

briefly introduced in Box 2.

Thus, SULAPS could hypothetically

simulate the reaction to changing agricul-

tural policies at the level of individual

farms and output spatially explicit land-

use changes as well as changes in agricul-

tural productivity. ALPSCAPE would then

approximate the economic effects of

changing agricultural production on the

local economy and resource management.

Further, IPODLAS would simulate forest

growth on abandoned land, based on

empirically derived growth curves. Then

ALPSIM would focus on changing hiking

patterns, recreational behavior, tourist sat-

isfaction, and the number of days spent at

the holiday destination as a response to

landscape alteration. The changing num-

ber of days spent at the destinations could

finally be fed back to the economic model

FIGURE 3 (A) shows the 2-

dimensional output produced by

an ALPSIM simulation. It

visualizes the movement of the

agents (white dots) and agent-

related data, for example the

agents’ IDs (in green). (B)

produces a more realistic, 3-

dimensional simulation. The

agents are rendered at 10 times

their natural size for better

visibility. (Images courtesy of

Duncan Cavens)

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Ariane Walz, Christian Gloor, Peter Bebi, Andreas Fischlin, Eckart Lange, Kai Nagel, and Britta Allgöwer

Mountain Research and Development Vol 28 No 2 May 2008

126

of ALPSCAPE to estimate the impact on

the local economy.

Although this looks like an ideal cou-

pling of the existing models and a great

opportunity to fully exploit their potential,

the technical and methodological chal-

lenges, particularly at the interfaces

between models, are remarkable. Basic

problems are (1) the limited exchangeabil-

ity of data (content, scale, extent, purpose,

validity range, etc) among the models, (2)

implicit assumptions often closely connect-

ed to the modeling techniques and algo-

rithms, including temporal and spatial

scales of validity, and (3) the increase in

uncertainties which add up with the num-

ber of models that are consecutively used.

Example 2: Animation of hikers’ behavior

in the vicinity of the proposed Schatzalp

Tower

In the second example, the ALPSIM mod-

el (Box 2) was transferred to the munici-

pality of Davos to assess the effect of the

proposed Schatzalp Tower (Box 1) on hik-

ers’ behavior. Based on the primary input

data on topography, land cover, and the

tower itself, the ALPSIM model ran simu-

lations and produced an animation as a

key visualization product (see Figure 5).

Although no special adjustments, eg in

agents’ behavior, or extra data surveys

were accomplished, the preparation of the

input data, the simulation runs and the

production of the animation totaled up to

37 workdays.

This example shows that the model

can technically be transferred to a differ-

ent setting, but the effort involved and the

lack of user-friendliness are still major

problems. If such models are to be estab-

lished as easy-to-use tools in planning, the

availability of the required input data

needs to be ensured; and convenience in

operational application, including trans-

fer to other regions, would still have to

improve significantly.

Developing better planning tools

Modeling and visualization in landscape

research and in planning practice do not

have much in common these days. But

with regard to the ongoing alteration of

the Alpine landscape, planners and deci-

sion-makers should profit more from the

FIGURE 4 IPODLAS user

interface to calculate and

visualize the migration of larch

bud moth populations. (Screen

shot by authors)

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127

great potential of state-of-the-art modeling

and visualization.

While computer-based visualization is

increasingly used in planning processes,

the application of models is still rare.

The outputs of the research community

represent mostly prototype models for

specific case studies. They are too com-

plex to be easily transferred and often

too time- and labor-intensive in their

application.

To get beyond the development of

such prototypes, and to establish tools

for practical planning, the models would

need to focus on similarities in regularly

arising planning questions. They would

need to encounter a degree of detail

that is required to add to the “real

world” problem, and at the same time

still allow for transfer to different

regions. And the operability and user-

friendliness of these models would need

to be improved. Although the research

community, and also the NRP48, can

contribute to such tools with many find-

ings and methodological advances, the

actual elaboration of a model-based tool

for operational use might be better

accomplished by software developers.

Still, when looking at the course that

landscape visualization has taken over

the last 20 years, one can speculate that

landscape modeling will also eventually

make it into the planning mainstream.

This would certainly improve the knowl-

edge base for the fundamental decisions

that need to be taken with regard to the

Alps in the near future.

FIGURE 5 Visualization of the

planned Schatzalp Tower,

Davos, Canton of Grisons,

Switzerland and its Alpine

setting. (Image by authors)

AUTHORS

Ariane Walz, Peter Bebi

WSL–Swiss Federal Institute for Snow

and Avalanche Research SLF, Flüela-

strasse 11, 7260 Davos, Switzerland.

[email protected]; [email protected]

Ariane Walz is a geographer who

did her doctoral research on land use

change modeling within an integrated

approach to regional development,

within the NRP48 project ALPSCAPE.

Peter Bebi is an environmental sci-

entist with a special focus on mountain

forests and interdisciplinary research

(director of ALPSCAPE).

Britta Allgöwer, Christian Gloor

Geography Department, GIS Division,

University of Zurich, Winterthurer

Strasse 190, 8057 Zurich, Switzer-

land.

[email protected];

[email protected]

Britta Allgöwer is a senior research

scientist with a special focus on nature

conservation, GIS, and disturbance

dynamics research (director of IPODLAS).

Christian Gloor is a computer scien-

tist who did his doctoral research with-

in the ALPSIM project on distributed

intelligence in Multi-Agent Systems.

Andreas Fischlin

Terrestrial Systems Ecology, Swiss

Federal Institute of Technology (ETHZ),

8092 Zurich, Switzerland.

andreas.fischlin@env.ethz.ch

Andreas Fischlin is a biologist with

a strong focus on ecosystem and cli-

mate change modeling (co-director of

IPODLAS). He was “Coordinating Lead

Author” of the second book of the 4th

United Nations Climate Report, pro-

duced by the IPCC, which won the

2007 Nobel Peace Prize award togeth-

er with Al Gore.

Eckart Lange

Department of Landscape, University

of Sheffield, Floor 3, Arts Tower, West-

ern Bank, Sheffield S10 2TN, United

Kingdom.

[email protected]

Eckart Lange is a landscape plan-

ner with a strong focus on visualization

and participation for environmental

decision-making (co-director of ALPSIM).

Kai Nagel

Department of Mechanical and Trans-

port Engineering, TU Berlin, D-10587

Berlin, Germany.

[email protected]

Kai Nagel is a physicist and com-

puter scientist with considerable

expertise in complex systems modeling

(co-director of ALPSIM).