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We introduce tangible immersion – virtual reality coupled with tangible interaction – to foster inter-disciplinary collaboration in a critical, yet creative design process. Integrating tangible, embodied interaction with geospatial modeling and immersive virtual environments (IVE) can make 3D modeling fast and natural, while enhancing it with realistic graphics and quantitative analytics. We have developed Tangible Landscape, a technology that links a physical model with a geographic information system and 3D modeling platform through a real-time cycle of interaction, 3D scanning , geospatial computation, and 3D rendering. With this technology landscape architects, other professionals, and the public can collaboratively explore design alternatives through an iterative process of intuitive ideation, geocomputational analysis, realistic rendering, and critical analysis. This is demonstrated with a test case for interdisciplinary problem solving in which a landscape architect and geoscientist use Tangible Landscape to collaboratively design landforms, hydrologic systems, planting, and a trail network for a brownfield site. Using this tangible immersive environment they rapidly explored alternative scenarios. We discuss how the participants used real-time analytics to collaboratively assess trade-offs between environmental and experiential factors, balancing landscape complexity, biodiversity, remediation capacity, and aesthetics. Together they explored how the relationship between landforms and natural processes affected the performance of the designed landscape. Technologies that couple tangible geospatial modeling with IVEs have the potential to transform the design process by breaking down disciplinary boundaries, but may also offer new ways to imagine space and democratize design.
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Tangible Immersion
for Ecological Design
1 Collaboravely designing and
immersively visualizing a park with
Tangible Landscape
Vaclav Petras
North Carolina State University
Helena Mitasova
North Carolina State University
Ross Meentenmeyer
North Carolina State University
Payam Tabrizian
North Carolina State University
Brendan Harmon
Louisiana State University
Anna Petrasova
North Carolina State University
We introduce tangible immersion – virtual reality coupled with tangible interacon – to foster inter-
disciplinary collaboraon in a crical, yet creave design process. Integrang tangible, embodied
interacon with geospaal modeling and immersive virtual environments (IVE) can make 3D
modeling fast and natural, while enhancing it with realisc graphics and quantave analycs. We
have developed Tangible Landscape, a technology that links a physical model with a geographic
informaon system and 3D modeling plaorm through a real-me cycle of interacon, 3D scan-
ning, geospaal computaon, and 3D rendering. With this technology landscape architects, other
professionals, and the public can collaboravely explore design alternaves through an iterave
process of intuive ideaon, geocomputaonal analysis, realisc rendering, and crical analysis. This
is demonstrated with a test case for interdisciplinary problem solving in which a landscape architect
and geoscienst use Tangible Landscape to collaboravely design landforms, hydrologic systems,
planng, and a trail network for a browneld site. Using this tangible immersive environment they
rapidly explored alternave scenarios. We discuss how the parcipants used real-me analycs
to collaboravely assess trade-os between environmental and experienal factors, balancing
landscape complexity, biodiversity, remediaon capacity, and aesthecs. Together they explored
how the relaonship between landforms and natural processes aected the performance of the
designed landscape. Technologies that couple tangible geospaal modeling with IVEs have the
potenal to transform the design process by breaking down disciplinary boundaries, but may also
oer new ways to imagine space and democraze design.
TOPIC (ACADIA team will ll in)
Recent advances in compung, sensors, and human-computer
interacon are transforming the pracce of design. With compu-
taonal modeling, analysis and simulaon designers can generate
novel forms, explore parametric variaons, and quantavely test
the performance of their designs. Digital fabricaon technologies
allow designers to precisely and rapidly build prototypes and
then complex, high performance structures, while augmented
and virtual reality enable designs to be immersively experienced.
With tangibles – technologies that couple physical objects with
digital data – designers can naturally interact with and trans-
form digital models. Synthesizing these emerging technologies
will enable designers to rapidly generate designs, quantavely
test them, and immersively experience them in a uid, seamless
creave process.
Design problems oen require collaboraon with other experts
like engineers and sciensts – to address the structural tectonics
and energy uxes of a building, the ow of trac and people
through a city, or ow of water and sediment through a land-
scape. Furthermore, design problems also involve non-experts
such as clients, stakeholders, and the general public. Designers’
creave processes, sciensts’ research methods, and public
parcipaon, however, are rarely integrated in an iterave
process. Collaboraon between scienc disciplines – even
mutually dependent disciples like ecology and geomorphology –
can be challenging due to technical, methodological, and lexical
dierences, focuses on dierent spaal and temporal scales, and
gaps in knowledge (Renscheler et al. 2007). It is especially chal-
lenging for ongoing research to connually inform a design – and
vice versa – when the soware, tools, and methods are so dispa-
rate. While landscape architects may use drawing, 3D modeling
and visualizaon, or digital fabricaon to imagine new landscapes,
sciensts such as ecologists and geomorphologists typically
use geospaal modeling and stascal inference to study the
paerns and processes that shape landscapes. Sciensts cannot
apply numerical models to hand drawn sketches or clay models
of topography; they may need to convert their geospaal and
stascal data before designers can work with it in computer
aided design plaorms.
These analycal disconnects have led to slow, complex work-
ows and stymied interdisciplinary collaboraon between
designers and sciensts. When design and research workows
are so complicated non-experts are unlikely to have technical
skills and understanding to meaningfully parcipate in the
process. In this paper we propose methods to bridge disci-
plinary divides and engage the public by synthesizing emerging
technologies such as tangibles, digital fabricaon, and virtual
environments with disciplinary tools and methods to create
integrated workows for creave exploraon and quantave
analysis. Seamless collaboraons that couple creave design and
scienc analysis have great potenal to radically transform the
pracce of ecological design (Figure 1).
Tangibles – tangible user interfaces – are systems that couple
physical objects with digital data for more natural, embodied
interacon (Dourish 2001). Tangibles give digital data an interac-
ve, physical form and presence that users can kinaesthecally
sense and manipulate. Advances in sensors, machine vision, and
robocs have radically accelerated the development of tangibles
– including tangibles designed for designers. Recent prototypes
for tangible design include the Collaborave Design Plaorm
(Schubert 2012) and CityScope (MIT Media Lab 2017) for urban
design and Tangible Landscape (Petrasova et al. 2015), the Rapid
Landscape Prototyping Machine (Robinson 2014), and Cyborg
Ecologies (Responsive Arfacts and Environments Lab 2017) for
landscape architecture.
Tangible interfaces for landscape architecture have mainly been
designed for terrain modeling. While terrain modeling is an
important aspect of landscape architecture, tangible interfaces
have not been developed for planng design. While landscape
architects typically use relavely simple techniques to digitally
illustrate planng through photomontage or 2D billboards
in 3D dioramas (Ervin 2001), there are more sophiscated
methods in computer graphics for modeling and rendering
realisc 3D plants including trees and grasses used by the
computer gaming and lm industries. The recent emergence
of aordable head-mounted displays has further accelerated
the development of realisc 3D graphics. Vegetaon modeling
has also been advanced by the development of sophiscated
methods in Geographic Informaon Systems (GIS) for producing
landscape-scale models of vegetaon that quanfy ecological
diversity and fragmentaon (Petras 2017). Seamlessly inte-
grang 3D planng with realisc rendering into the creave
design process could revoluonize the pracce of landscape
Immersive virtual environments (IVEs) combine immersion and
interacon with virtual environment to enhance presence — a
feeling of being physically present in a non-physical world. By
surrounding users with a connuous stream of visual smuli,
linked to their head and body movements, IVEs enable users to
acvely engage with and beer understand a virtual environ-
ment. In design IVEs have been used as a cost-eecve tool for
enhancing presentaons and improving communicaon between
architects, collaborators, and end-users. Furthermore, realisc
representaons can aid designers’ spaal cognive abilies by
reducing the mental eort needed to generate internal repre-
sentaons of designs. Recent advances in CPUS, GPUs, and 3D
modeling and rendering soware have enabled designers to
generate photorealisc representaons that mimic the condi-
ons through which human perceive the designed landscape.
However, generang highly immersive and realisc visualizaons
requires considerable me and eort, especially in the context of
an iterave design process. While photorealisc renderings are
the best way to represent how people will perceive a landscape,
abstract representaons are also essenal tools for communi-
cang conceptual and analycal data.
Tangible Landscape
Tangible Landscape – a tangible interface for geospaal modeling
with realisc, real-me 3D rendering (Petrasova et al. 2015,
Tabrizian et al. 2016) – was designed to bridge disciplinary
divides by coupling physical and digital landscape models so
that users can intuively transform and immersively experi-
ence 3D data. It enables 3D sketching informed by real-me
analycs. Conceptually it couples a physical and digital model of
a landscape through a real-me cycle of 3D scanning, geospaal
computaon, 3D modeling, 3D rendering, and projecon (Figure
2). It is powered by GRASS GIS, an open source scienc plat-
form for geoprocessing (GRASS Development Team) – drawing
on its extensive libraries of peer-reviewed scienc models, anal-
yses, and simulaons – and Blender, an open-source plaorm
for 3D modeling, rendering, animaon, and game development
(Blender Development Team) (Figure 3). Tangible Landscape is
an open source project with repositories at hps://
Tangible Landscape evolved from Illuminang Clay (Ra et al.
2004) and the Tangible Geospaal Modeling System (Mitasova
et al. 2006, Tateosian et al. 2010). Illuminang Clay, an early
tangible interface developed by the MIT Media Lab, augmented
a laser scanned clay model of a landscape with projected spaal
analycs such as elevaon, slope, aspect, and drain direcon. It
was designed to “streamline the landscape design process and
result in a more eecve use of GIS, especially when distributed
decision-making and discussion with non-experts are involved”
(Ra 2004). The analyses were custom implemented in C++
for the project, but many were adapted from GRASS GIS’ open
source libraries (Piper 2002a). While highly innovave this
system supported a relavely small selecon of basic terrain
analyses, the interacon was limited to surface modicaons,
Tangible Immersion for Ecological Design Tabrizian et al.
2 Tangible Landscape couples a physical and digital model through a cycle of 3D scanning, geospaal computaon, 3D modeling and rendering, and projecon.
TOPIC (ACADIA team will ll in)
and the simple, abstract visualizaons limited by the hardware
available at the me had a low degree of realism.
A call for collaboraon with the GRASS GIS community (Piper
2002b) led to a new prototype – the Tangible Geospaal
Modeling System – that was powered by GRASS GIS (Mitasova
2006, Tateosian 2010) with a library of over 350 modules
including comprehensive topographic analyses, solar irradiaon
models, robust overland water ow simulaon, and many others.
While more exible with a large open source library and higher
resoluon visualizaons, this system did not support real-me
feedback, interacon was sll limited to surface modicaons,
and it did not yet support the realisc rendering of vegetaon or
built form.
Building on the Tangible Geospaal Modeling System and
inspired by the Augmented Reality Sandbox (Kreylos 2012),
Tangible Landscape took advantage of new developments in 3D
sensors and malleable materials to replace the expensive laser
scanner with a low-cost Kinect scanner and the clay model with
polymer-enriched sand (Petrasova 2015). Rapid scanning and
imaging by Kinect supported development of a wide range of
modes of interacon such as surface sculpng through depth
sensing and digizing points, areas, and volumes through object
and color detecon. Users can sculpt landforms, place building
blocks, plant trees, draw paths, and more.
3D modeling, 3D rendering, and support for virtual reality
powered by Blender were added to the system to make
3 Soware architecture for coupling GRASS GIS and Blender.
visualizaons more immersive and give users a ground view
experience (Tabrizian 2016). Blender was chosen to power
Tangible Landscape’s 3D modeling and rendering because it has
a GIS add-on, realisc viewport rendering, and a virtual reality
add-on. The BlenderGIS add-on supports the import, export, and
processing of georeferenced data in Blender (domlysz). In Blender
the viewport supports ambient occlusion, ambient lighng,
an-aliasing, and raytracing powered by OpenGL for realisc
on-the-y rendering. The Virtual Reality Viewport add-on
supports head-mounted displays (HMD) with built-in head
tracking including the Oculus Ri DK2 and CV1 (Felinto).
3D planting and realistic rendering
To address planng design, a key aspect of landscape archi-
tecture, Tangible Landscape has now been extended with 3D
planng including trees, shrubs, and groundcover and realisc
real-me rendering. It has new modes of interacon and oers
an enhanced immersive experience. Designers can place patches
of colored felt or draw with a laser pointer to create planng
areas. They can also place color-coded wooden or 3D printed
models of trees to digize individual specimens. Plants are
immediately modeled and rendered, either on a screen or a HMD.
Tangible Landscape uses simple tangible interacons drawing
on childhood play such as sculpng sand, arranging blocks and
markers, and placing felt patches (Figure 4) because people
already know how to do these things – these are intuive acons
using exisng sensorimotor schemas. These physical media –
sand, wood blocks, and felt – have a familiar feel and aesthec,
while the computer graphics supplement them with realism.
4 Tangible Landscape supports mulple modes of interacon including a) sculpng,
b) carving, c) placing objects as points, d) drawing lines with laser pointer
e) designang views using a color-coded marker, and f) placing patches of
colored felt as areas.
Dierent species of plants are detected by color. Patches of
colored felt represenng dierent types of vegetaon are
captured as colors by Kinect, grouped using superpixel segmen-
taon (Achanta et al. 2012), and then automacally classied by
vegetaon type in GRASS GIS. The classied planng areas are
then imported into Blender and populated with 3D models of
the designated plants using a parcle system. The 3D plants can
either be procedurally generated based on custom parameters,
procedurally generated with parameters, twigs, and textures from
a plant library such as the Grove (Keulen), or imported from a
library of 3D plant models with texturing mapping such as Xfrog
(Oliver and Lintermann 2010, Xfrog). The scene is interacvely
rendered in real-me.
Designers can immersively explore the landscape that they have
modeled by tangibly idenfying views. They can place a wooden
marker on the physical model to designate both a viewpoint
and a view direcon. The marker is color coded with one end
represenng the viewpoint and the other represenng the view
direcon (Figure 4e). The marker is detected based on eleva-
on change and color. It is imported into Blender as a vector to
align an eye level camera. By simply moving the marker around
designers can quickly explore dierent views, seeing what they
have built and planted as if on the ground.
Aer individual trees or patches of trees have been planted by
the designer and automacally detected and classied, Tangible
Landscape analyses the structure of the landscape, compung
metrics that quantavely describe the paern, distribuon,
spaal organizaon, variaon, and shape of elements in the land-
scape. These metrics are projected as a dashboard of charts or
graphs beside the model as addional feedback for the designer
(Figure 6). The landscape metrics include Shannon’s diversity
index, mean shape index, edge density, and patch number (Baker
et al. 1992).
Through a case study we explored how tangible, immersive
interacon can support a collaborave, sciencally informed,
yet creave design process that bridges disciplinary boundaries.
To test a diverse set of interacons we created a hypothecal 1
square kilometer browneld study site with several mounds of
capped, contaminated soil. We tasked a landscape architect and
a geoscienst to design this site as a park. Their objecves were
to retain and phytoremediate as much surface water as possible
in order to minimize the migraon of contaminants, while
enhancing biodiversity, improving aesthecs, and planning a trail
network between two entrances.
The landscape architect and geoscienst used Tangible
Landscape with simple tools and media to develop their
designs. They worked with a polymer-enriched sand model of
the landscape cast with a CNC milled mold, wooden sculpng
tools, colored wooden markers, and colored felt (Figure 1). As
they created their design they received real-me feedback from
Tangible Landscape including maps of geospaal analycs, graphs
with design metrics, and 3D renderings.
To regrade the topography and manage the hydrology of the
site they reshaped the polymeric sand model of the landscape,
sculpng changes by hand. As they sculpted the sand the model
was scanned, interpolated as a digital elevaon model (DEM) and
a contour map was derived and projected over the model. This
new DEM was also used to simulate overland water ow and
ponding, with the results projected over the model along with
the contours, all in real-me, as the changes were made. Shallow
overland water ow was simulated as a diusive wave approxi-
maon of the bivariate form of the St. Venant equaons solved
using a Monte Carlo path sampling method (Mitasova et al.
2004), while ponding was computed using the standard depres-
sion lling technique. Elevaon, contour and water depth maps
were projected onto the model and the total water depth and
Tangible Immersion for Ecological Design Tabrizian et al.
a b
c d
e f
TOPIC (ACADIA team will ll in)
A hydrologic map with topographic
contours (top) and charts for the
surface area and depth of the pond
A classied landcover map (top)
and landscape structure metrics
(boom) showing the percentage of
remediated soil, number of patches,
species richness, mean patch size,
shannon diversity, and edge index.
7 A map of slope of the boardwalk
(top) and a chart with the prole
of the boardwalk (boom). Red,
yellow, and green signify high,
medium, and low slopes.
area were projected as bar charts beside the model to provide
analycal feedback about the performance of the proposed
changes (Figure 8a).
To design the planng they placed colored coded pieces of felt
represenng patches of trees and small wooden models repre-
senng individual trees. The felt and models were sensed and
classied as vegetaon types by color. The vegetaon – decid-
uous trees, evergreen trees, wetland trees, and shrubs – were
projected on the model as a map with colored polygons and
modeled and rendered in 3D on the display. Metrics for land-
scape structure and diversity – including patch number, richness,
Shannon index, and shape index – and the percentage of water
that could be phytoremediated by wetland planng were
projected as bar charts beside the model. Remediaon potenal
was computed as the intersecon of water and the wetland
planng root zone (Figure 8b).
To plan the trail system they placed wooden markers represenng
waypoints between the entrances. The opmal route between
the entrances and waypoints was computed as the least cost
path across an anisotropic cumulave cost surface of walking
eort (Fontanari 2002). As they placed waypoints, the trail was
dynamically adjusted and projected on the model, the prole of
the trail was projected as a graph beside the model (Figure 8c).
The trail route was extruded to create a 3D boardwalk.
The geoscienst and the landscape architect collaboravely
developed another design (Figure 9). Together they evaluated
the performance of their design using the dashboard with its
landscape structure and remediaon metrics and explored 3D
rendered views of the park from a variety of vantage points.
Aer idenfying many promising viewpoints they planned a trail
network with walkable slopes that would take advantage of the
lakeside experience, while oering panoramic views of the park.
Many design iteraons later, they had developed a looping trail
system around the lake, over one of the islands, and along the
ridges with their commanding views (Figure 9c). Finally each of
them donned an Oculus Ri to explore the nal design with a
walkthrough along the trail (Figure 9d3). Throughout the design
process the geoscienst and the landscape architect had a rich
dialogue, informed by geospaal analycs. Tangible Landscape
helped them to rapidly implement, visualize, evaluate, and
crique their ideas on the y. They were able to collaboravely
develop a high performance design with realiscally rendered
views in just an hour aer having explored many alternave
design ideas including a dozen dierent opons for the trail
network. See a video of their design process at: hps://
The landscape architect and the geoscienst were able to
collaborate eecvely because Tangible Landscape has a large,
easily extendible library of analyses, adequate resoluon for
the design problem, and fast enough feedback. The analyses
used – water ow, ponding, ecological structure, and phytore-
mediaon potenal in this case study – can easily be changed
and customized with GRASS GIS’ API and extensive library of
funcons. The analyses, projected as maps and charts, informed
the design team’s decisions. As they worked they received both
spaal and quantave feedback about the ecological impact of
their intervenons.
With the Kinect sensor mounted 60 cm above the model
Tangible Landscape has 2 mm scanning resoluon with a mean
error of 0.02 mm. Markers and colored patches of felt need to
be at least 0.5 cm2 to be detected. At this scanning resoluon
the modeling media – polymer enriched sand, wooden markers,
and felt – allow for ne-grained tangible interacons.
The rate of geospaal feedback for Tangible Landscape depends
upon the size of the physical model and the analyses used. For
8 The landscape architect’s design process
TOPIC (ACADIA team will ll in)
9 The geoscienst and landscape architect’s design process
this case study we used a small 34 cm2 scale model of the 1 km2
study landscape. For this size model the average rate of feedback
for tangible interacon with the water ow simulaon is 2.02 ±
0.05 seconds. It takes 0.97 seconds to scan the 34 cm2 physical
model and interpolate the point cloud as a DEM. Then it takes
another 1.05 ± 0.05 seconds to compute water ow. Tangible
Landscape’s rate of feedback is fast enough for users to make a
change, remove their hands, and then see the result in a rapid,
iterave process of observaon, hypothesis generaon and
tesng, and inference.
While the Blender viewport can update in real-me for simple
scenes, it can take a couple of seconds for more complex scenes
depending upon the number of trees and their polygon count.
Blender’s viewport shading supports raytraced shadows, textures,
environment lighng, and ambient occlusion. It has the level of
realism needed to quickly explore design scenarios. However, for
more sophiscated, higher resoluon rendering users can switch
to Cycles rendering engine, which uses path tracing to simu-
late so shadows, depth of eld, moon blur, causcs, ambient
occlusion, and indirect lighng. Depending on the complexity of
the scene, render sengs, and hardware, a Cycles rendering can
vary from seconds to minutes.
Future work
Planng design with Tangible Landscape could be even richer,
more immersive, and more accessible. In the near future we
intend to improve planng design by creang an open source
library of both procedural and 3D plants, preparing a variety of
plant communies for use, developing tools for plant selecon
using Blender’s GUI, and developing an ecological succession and
phytoremediaon models in GRASS GIS. We intend to create an
open source library of other 3D assets, implement architectural
and urban modeling with Tangible Landscape, develop a more
sophiscated dashboard, and support mulple render engines
for viewport shading, viewport rendering, and rendering. We
plan to use Blender’s game engine for richer interacon with the
virtual environment. We also plan to integrate digital fabricaon
into the system for physical feedback from computaon so that
a landscape evoluon simulaon could change the shape of the
physical model or an epidemiological simulaon could remove
plant markers from the model.
Tangible Landscape – a tangible interface for 3D modeling
landscapes – enables landscape architects to rapidly, iteravely
develop designs, realiscally visualize landscapes, and collaborate
with others. Coupling physical and virtual models of landscapes
can synthesize analog and digital design methods, while coupling
scienc and architectural models can bridge disciplinary
boundaries. Such tangible interfaces for design can make the
design process so natural and intuive that experts from other
disciplines or even the public can easily parcipate, collabo-
ravely understanding and reimagining space in novel ways.
Technologies like Tangible Landscape that invite public parcipa-
on and engagement in the design process could democraze
design, giving people a means of expression, giving them agency
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TOPIC (ACADIA team will ll in)
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Payam Tabrizian is a PhD student in college of Design and Center
for Geospaal Analycs at NC State University. He received a Master
of Urbanism and Strategic Planning from K.U Leuven, Belguim, and a
Bachleor in Architecture from Azad University, Iran. Payam is a Virtual
reality developer with specec interest on integrang geospaal model-
ling and realme 3D visualizaon to enhance urban design and research.
Brendan Harmon is an assistant professor of landscape architec-
ture at Louisiana State University’s Robert Reich School of Landscape
Architecture. He received a Master of Landscape Architecture from the
Harvard Graduate School of Design, a Master of Philosophy in Geography
and the Environment from the University of Oxford, and a PhD in Design
from NC State University.
Anna Petrosova is a PhD Candidate at the Center for Geospaal
Analycs at NC State University focusing on integrang dynamic geospa-
al modeling with tangible user interfaces. Anna is an acve member of
GRASS Development team developing and maintaining GRASS GIS, an
open source GIS.
Vaclav Petras Vaclav Petras has a a master degree in geoinformacs
from Czech Technical University and is currently pursuing PhD in Marine,
Earth, and Atmospheric Sciences at NC State University. His research
revolves around lidar point clouds, terrain, geospaal simulaons and
modeling. He is an advocate for open science and an open source devel-
oper and enthusiast.
TOPIC (ACADIA team will ll in)
... The manufacturing method and type of material used for creating a 3D-printed model also limited the complexity of the design and reduced the level of detail of the 3D-printed model used in the study. This is reflected in the higher MinLoD, when compared with lower MinLoD values suggested in other studies involving the use of TL (Tabrizian et al. 2017). ...
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Green infrastructure (GI) consists of modifications to the landscape to manage the impact of climate change on urban landscapes. These modifications involve the creation of swales, rain gardens, and retention ponds, among the possible solutions. Placing GI in the landscape therefore requires a good understanding of the dynamics and complexity of surface water flow in urban environments, and how changes in this urban fabric affect the flow pattern of the surface water. It also necessitates a high degree of flexibility to account for different urban configurations that occur as a function of land-use changes in time. The tangible landscape (TL) addresses these necessities by enabling simulation and comparison of different scenarios and possible models with each other, in near-real time and supported by a geographic information system (GIS). In this research, we use the TL to design and hydrologically evaluate the performance of the three GI alternatives proposed by the municipality of Oslo at Mærradal valley, in the city of Oslo.
... Thanks to the ability of IVEs to elicit a higher sense of immersion [30], presence [31], and improved spatial perceptions (e.g., distance, depth) [32]. IVEs have been widely adopted in geospatial sciences and urban planning applications, such as 3D visualization of open map data [33], real-time 3D visualization of ecological simulations [34], and geodesign [35]. However, to our knowledge, IVE has not been used for human verification of visibility simulations, particularly viewscape modeling. ...
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Visual characteristics of urban environments influence human perception and behavior, including choices for living, recreation and modes of transportation. Although geospatial visualizations hold great potential to better inform urban planning and design, computational methods are lacking to realistically measure and model urban and parkland viewscapes at sufficiently fine-scale resolution. In this study, we develop and evaluate an integrative approach to measuring and modeling fine-scale viewscape characteristics of a mixed-use urban environment, a city park. Our viewscape approach improves the integration of geospatial and perception elicitation techniques by combining high-resolution lidar-based digital surface models, visual obstruction, and photorealistic immersive virtual environments (IVEs). We assessed the realism of our viewscape models by comparing metrics of viewscape composition and configuration to human subject evaluations of IVEs across multiple landscape settings. We found strongly significant correlations between viewscape metrics and participants’ perceptions of viewscape openness and naturalness, and moderately strong correlations with landscape complexity. These results suggest that lidar-enhanced viewscape models can adequately represent visual characteristics of fine-scale urban environments. Findings also indicate the existence of relationships between human perception and landscape pattern. Our approach allows urban planners and designers to model and virtually evaluate high-resolution viewscapes of urban parks and natural landscapes with fine-scale details never before demonstrated.
... Tangible Landscape is a TUI designed to support natural, embodied interaction with 3D spatial data. Tangible Landscape couples a physical and digital model of a landscape through a continuous cycle of 3D scanning, geospatial modeling, and projection so that users can intuitively interact with the modeled landscape and the corresponding simulated physical processes in real-time [20,36,35]. During this more hands-on approach to interacting with 3D spatial data, students become active participants in the scientific inquiry process as the system allows them to iteratively observe natural phenomena, generate inferences, form hypotheses and test them, and draw conclusions. ...
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This paper presents novel and effective methods for teaching about topography–or shape of terrain–and assessing 3-dimensional spatial learning using tangibles. We used Tangible Landscape–a tangible interface for geospatial modeling–to teach multiple hands-on tangible lessons on the concepts of grading (i.e., earthwork), geomorphology, and hydrology. We examined students’ ratings of the system’s usability and user experience and tested students’ acquisition and transfer of knowledge. Our results suggest the physicality of the objects enabled the participants to effectively interact with the system and each other, positively impacting ratings of usability and task-specific knowledge building. These findings can potentially advance the design and implementation of tangible teaching methods for the topics of geography, design, architecture, and engineering.
Physical representations of data offer physical and spatial ways of looking at, navigating, and interacting with data. While digital fabrication has facilitated the creation of objects with data-driven geometry, rendering data as a physically fabricated object is still a daunting leap for many physicalization designers. Rendering in the scope of this research refers to the back-and-forth process from digital design to digital fabrication and its specific challenges. We developed a corpus of example data physicalizations from research literature and physicalization practice. This survey then unpacks the “rendering” phase of the extended InfoVis pipeline in greater detail through these examples, with the aim of identifying ways that researchers, artists, and industry practitioners “render” physicalizations using digital design and fabrication tools.
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Physical representations of data offer physical and spatial ways of looking at, navigating, and interacting with data. While digital fabrication has facilitated the creation of objects with data-driven geometry, rendering data as a physically fabricated object is still a daunting leap for many physicalization designers. Rendering in the scope of this research refers to the back-and-forth process from digital design to digital fabrication and its specific challenges. We developed a corpus of example data physicalizations from research literature and physicalization practice. This survey then unpacks the "rendering" phase of the extended InfoVis pipeline in greater detail through these examples, with the aim of identifying ways that researchers, artists, and industry practitioners "render" physicalizations using digital design and fabrication tools.
Due to human-induced climate change, traditionally water-rich environments can no longer depend on stable patterns of freshwater supply. Climate scientists advise water managers to expect warmer temperatures, changes in the distribution and intensity of precipitation, and more prolonged droughts. Together with global climate forcings, rapidly expanding cities and suburban communities are altering the spatial and temporal availability of freshwater resources. Constantly changing environments urge for integrated land- and water-use planning efforts to help inform water-efficient development patterns. This dissertation contributes to emerging research which increasingly recognizes the spatial configuration and patterns of developed land use as major factors affecting water demand. Framed around three scientific research studies, this dissertation is the first modeling effort of its kind to examine how different spatial patterns of development are likely to affect water demand and supply under a scientifically plausible spectrum of future climate conditions. The first study examines the functional linkage between water use and spatial patterns of development, while accounting for other well studied socio-economic and environmental factors. Results consistently demonstrate that clusters of compact patterns of development show potential for more efficient use of water. The main products of the first study are empirically-derived coefficients of estimated water demand; these coefficients are then used in the second study to forecast how future land and climate changes are likely to impact local and regional water demand. Lastly, the third study examines the spatial distribution and severity of future water stress conditions associated with the combined and individual effects of urban growth, water demand, and climate change. While results show global climate forcings as the dominant driver of future water demand and supply, regional land use policies that promote urban infill and higher density development have the potential to reduce future water demand and water stress. These spatially-explicit policies would be particularly effective in areas with high projected population growth. Changes in flow regime associated with future land and climate conditions are also likely to affect the ecological integrity of aquatic ecosystems, which in turn can negatively impact human well-being. Supporting more environmentally sensitive regulations is critical to ensure the future availability of water. The methodological framework described here provides a platform to scientifically evaluate land-use policies and regulations that support a more efficient use of freshwater resources under future conditions of environmental change.
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We present Tangible Landscape-a technology for rapidly and intuitively designing landscapes informed by geospatial modeling, analysis, and simulation. Tangible Landscape is a tangible interface powered by a geographic information system that gives 3D spatial data an interactive, physical form so that users can naturally sense and shape it. It couples a physical and a digital model of a landscape through a real-time cycle of physical manipulation, 3D scanning, spatial computation, and projected feedback. Natural 3D sketching and real-time analytical feedback should aid landscape architects in the design of high performance landscapes that account for physical and ecological processes. We conducted a series of studies to assess the effectiveness of tangible modeling for landscape architects. Landscape architecture students, academics, and professionals were given a series of fundamental landscape design tasks-topographic modeling, cut-and-fill analysis, and water flow modeling. Their performance was assessed using qualitative and quantitative methods including interviews, raster statistics, morphometric analyses, and geospatial simulation. With tangible modeling participants built more accurate models that better represented morphological features than they did with either digital or analog modeling. When tangibly modeling they worked in a rapid, iterative process informed by real-time geospatial analytics and simulations. With the aid of real-time simulations they were able to quickly understand and then manipulate how complex topography controls the flow of water.
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Background Point clouds with increased point densities create new opportunities for analyzing landscape structure in 3D space. Taking advantage of these dense point clouds we have extended a 2D forest fragmentation index developed for regional scale analyses into a 3D index for analyzing vegetation structure at a much finer scale. Methods Based on the presence or absence of points in a 3D raster (voxel model) the 3D fragmentation index is used to evaluate the configuration of a cell’s 3D neighborhood resulting in fragmentation classes such as interior, edge, or patch. In order to incorporate 3D fragmentation into subsequent conventional 2D analyses, we developed a transformation of this 3D fragmentation index into a series of 2D rasters based on index classes. Results We applied this method to a point cloud obtained by airborne lidar capturing a suburban area with mixed forest cover. All processing and visualization was done in GRASS GIS, an open source, geospatial processing and remote sensing tool. The newly developed code is also publicly available and open source. The entire processing chain is available and executable through Docker for maximum reproducibility. Conclusions We demonstrated that this proposed index can be used to describe different types of vegetation structure making it a promising tool for remote sensing and landscape ecology. Finally, we suggest that processing point clouds using 3D raster methods including 3D raster algebra is as straightforward as using well-established 2D raster and image processing methods.
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This book presents a new type of modeling environment where users interact with geospatial simulations using 3D physical models of studied landscapes. Multiple users can alter the physical model by hand during scanning, thereby providing input for simulation of geophysical processes in this setting. The authors have developed innovative techniques and software that couple this hardware with open source GRASS GIS, making the system instantly applicable to a wide range of modeling and design problems. Since no other literature on this topic is available, this Book fills a gap for this new technology that continues to grow. Tangible Modeling with Open Source GIS will appeal to advanced-level students studying geospatial science, computer science and earth science such as landscape architecture and natural resources. It will also benefit researchers and professionals working in geospatial modeling applications, computer graphics, hazard risk management, hydrology, solar energy, coastal and fluvial flooding, fire spread, landscape, park design and computer games.
Conference Paper
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We introduce a system for urban planning - called Urp -thatintegrates functions addressing a broad range of the fieldsconcerns into a single, physically based workbench setting. The I/OBulb infrastructure on which the application is based allowsphysical architectural models placed on an ordinary table surfaceto cast shadows accurate for arbitrary times of day; to throwreflections off glass facade surfaces; to affect a real-time andvisually coincident simulation of pedestrian-level windflow; and soon.We then use comparisons among Urp and severalearlier I/O Bulb applications as the basis for anunderstanding of luminous-tangible interactions, which resultwhenever an interface distributes meaning and functionality betweenphysical objects and visual information projectively coupled tothose objects. Finally, we briefly discuss two issues common to allsuch systems, offering them as informal thought-tools for thedesign and analysis of luminous-tangible interfaces.
Geographical information systems (GIS) are well suited to the spatial analysis of landscape data, but generally lack programs for calculating traditional measures of landscape structure (e.g., fractal dimension). Standalone programs for calculating landscape structure measures do exist, but these programs do not enable the user to take advantage of GIS facilities for manipulating and analyzing landscape data. Moreover, these programs lack capabilities for analysis with sampling areas of different size (multiscale analysis) and also lack some needed measures of landscape structure (e.g., texture). We have developed the r.le programs for analyzing landscape structure using the GRASS GIS. The programs can be used to calculate over sixty measures of landscape structure (e.g., distance, size, shape, fractal dimension, perimeters, diversity, texture, juxtaposition, edges) within sampling areas of several sizes simultaneously. Also possible are moving window analyses, which enable the production of new maps of the landscape structure within windows of a particular size. These new maps can then be used in other analyses with the GIS.
Geomorphology plays a fundamental role in controlling many ecosystem processes, and in turn, ecosystems can have a profound influence on many geomorphic forms and processes. Over the past few decades, a proliferation of research has developed at the interface of geomorphology and ecosystems ecology. The 2005 Binghamton Symposium brought together some of the leading researchers from both communities to address these critical interfaces between the disciplines. This paper reviews some of the aspects of the disciplines of geomorphology and ecosystems ecology, and the papers presented at the symposium. The papers in this volume illustrate the current status of the disciplines, the difficulties in bridging the disciplines, and the issues that are emerging as research priorities.
A path sampling method is proposed for solving the continuity equations describing mass flows over complex landscape surfaces. The modeled quantities are represented by an ensemble of sampling points which are evolved according to the corresponding Green function. The method enables incorporation of multi-scale/multi-process treatments. It has been used to develop simulation tools for overland shallow water flow and for sediment transport. The spatial pattern of sediment flow and net erosion/deposition is modeled using the closure relationship between sediment transport capacity and detachment developed for the USDA Water Erosion Prediction Project. The tools were recently implemented as modules in Open Source GRASS GIS. Their application is illustrated by the study of impact of land use and topography change on overland flow and sediment transport at North Carolina State University campus.