Area Preserving Dynamic Geospatial Visualization on Physical Globe

Shima Dadkhahfard, Katayoon Etemad, John Brosz and Faramarz Samavati

Department of Computer Science University of Calgary, Calgary, Canada

Keywords:

Geo-visualization, Dynamic Visualization.

Abstract:

We present a methodology for creating dynamic visualization of geospatial data on physical globe. To achieve

this goal, we use a piecewise curved-display and multi-projector setup. The curved-display is a physical

representation of the globe and provides closer approximation of the Earth and reduce distortions. In our

method, we use a Discrete Grid Global System (DGGS) for discretizing the Earth to hierarchical cells in

different resolutions. This DGGS employs an area preserving projection for on the ﬂy integration of geospatial

datasets. There is a one-to-one correspondence between pieces of our curved-display and DGGS cells in a

speciﬁc resolution. We use 3D printing technology for fabricating of each piece of the display. For controlling

the projection, we developed software that takes data from DGGS, warp it and then feeds it to the projectors.

The fabrication of the cells and the generation of projection feed follow the same structure of DGGS. We

demonstrate the ﬂexibility of our construction with several example setups and apply them to visualize multiple

datasets, including time-varying geospatial data.

1 INTRODUCTION

As the only livable planet for human beings, the

Earth is important and knowing different aspects of

this huge and live organism helps us in our critical

decision-making. Since the recent advancement of

geospatial sensors has resulted in several technologies

for collecting data (e.g. satellites, smart phones, me-

teorological instruments, and LIDAR), today we are

faced with the explosion of the volume and variabil-

ity of geospatial data. An important challenge is how

to integrate and process this huge dynamic dataset.

This challenge has been tackled by GIS and recently

Digital Earth systems (Mahdavi-Amiri et al., 2015a).

However, another important challenge, is visualizing

this large and dynamic dataset to help the general pub-

lic understand and analyse our live planet and make

decisions about the Earth.

The common approach for geospatial visualiza-

tion in GIS is to project Earth-related dataset onto 2D

display screens using projection methods like Merca-

tor (Grafarend, 1995). However, projecting geospatial

information from the surface of the Earth to 2D maps

creates some issues. Problems such as unwanted dis-

tortion of 2D maps, misinterpretation of the size of the

areas (e.g. countries), and relative positions are just

few of the challenges (Mahdavi-Amiri et al., 2015a;

Zolfagharifard, 2014; Snyder, 1997). In section 4 we

will demonstrate the misinterpretation in visual analy-

sis resulting from the area distortion of Mercator map-

ping (See Figure 16).

In Digital Earth systems (e.g. Google Earth),

geospatial datasets are mapped on a 3D globe which

can conceptually reduce distortions (See Figure 17).

Well-thought interactive interfaces could provide

users with a better understanding of a 3D globe re-

sulting from an exploratory experience. However, to

create the 3D globe, it is necessary to deﬁne a map-

ping (commonly Mercator) from 2D domain to the

surface of the Earth. In addition to perspective distor-

tion, this mapping also creates some kind of distortion

(i.e. area, shape and distance).

One possible solution for reducing the map distor-

tions is to use a 3D physical globe, as a medium for

presenting geospatial datasets (Meng, 2003; Hruby

et al., 2008). The idea of physical visualization

of geospatial datasets has been recently explored in

(Djavaherpour et al., 2017). The physical globe can

prevent some misconceptions and inaccuracies com-

monly found in 2D maps. Unfortunately, in this sce-

nario the data and globe are physically ﬁxed and the

visualization is static; it would be much better if it

was possible to present vividly dynamic and live data

on this physical model. Inspired by spherical dis-

plays (Vega et al., 2014), we introduce a ﬂexible and

scalable method for accurate (i.e. area preserving)

projection of static or dynamic geospatial datasets. In

our method, we use a hierarchical grid system for dis-

Dadkhahfard, S., Etemad, K., Brosz, J. and Samavati, F.

Area Preserving Dynamic Geospatial Visualization on Physical Globe.

DOI: 10.5220/0006627303090318

In Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - Volume 3: IVAPP, pages

309-318

ISBN: 978-989-758-289-9

309

Figure 1: Area-preserving dynamic geospatial visualization on curved display.

Figure 2: The resulting ﬂat cells are then mapped to a sphere/ellipsoid using the inverse of a projection.

cretizing the Earth surface to regular (i.e. size and

shape) cells. We use the geometry of these curved

cells for creating a curved display panel (See Fig-

ure 1). Further, we use multiple projectors to feed

live geospatial data to the curved display. The associ-

ated dataset for each cell is rendered as an image and

carefully projected on the surface of our curved dis-

play. To do this, we developed a projector controller

which takes the geometry of curved cells, the associ-

ated data images and the projector (device’s) param-

eters. Based on this information, the projector con-

troller prepares and adjusts the input data images for

the projector device.

Using curved-displays, we can achieve a better ap-

proximation of the Earth that reduces the area and

shape distortions necessary on standard 2D displays.

To create the curved-display and projector setup, it

is important to deﬁne an accurate correspondence be-

tween regions on the Earth and areas on the curved-

display. For example, to have an accurate analysis

on the global warming issue on a region close to the

north pole, the average and projected temperatures of

that region must be mapped to an area on the curved-

display which has a proportionally right location with

the same area.

To accurately represent data within our model we

rely on a discretization of the surface of the Earth

into cells. The size of cells should be deﬁned accord-

ing to the desired scale and accuracy of the curved-

display. By making use of a hierarchical tessellation

of the Earth, such as a Discrete Global Grid System

(DGGS) method (Mahdavi-Amiri et al., 2015a; Purss

et al., 2016; Sahr et al., 2003; Xie et al., 2013; Randall

et al., 2002), transitions between scales and accuracy

can be easily achieved. In DGGS, the Earth’s surface

is approximated by a convex polyhedron. Depending

on the desired accuracy, each face of the polyhedron is

reﬁned to generate a hierarchy of regular ﬂat cells on

each face. The resulting ﬂat cells are then mapped to

a sphere/ellipsoid using inverse of projections, prefer-

ably area preserving (see Figure 2). The resulting hi-

erarchical cells are indexed and used for addressing

geospatial datasets. There are several active DGGSs

used for creating Digital Earth systems (Mahdavi-

Amiri et al., 2015a). In these systems, large amounts

of live geospatial datasets are assigned to the DGGS

cells. The current version of Google Earth also uses

DGGS, but unfortunately, its projection is not area

preserving.

For this work, we use Pyxis’ (Mahdavi-Amiri

et al., 2015b; Peterson, 2006; Sherlock et al., 2016)

Digital Earth system. The system is based on Aper-

ture 3 hexagonal grid system and the Snyder area pre-

serving projection (Snyder, 1992). For the purposes

of data exchange and transmission, hexagons are ag-

gregated and converted to rhombus cells (see Fig-

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310

ure 2). We use these rhombus cells for constructing

our curved-display.

In our method (see Figure 1), we visualize geospa-

tial DGGS on a piecewise curved-display. The idea is

to use multiple projectors, each of which is dedicated

to one or more rhombus cells. To use the indexed

data on DGGS, we use the same cell structure for con-

structing the curved-display. We have constructed this

piecewise curved-display by 3D printing the DGGS

model’s rhombus cells, and present our technique for

this entire work-ﬂow.

Figure 3: Each panel represents one tenth of the surface of

the globe. Left: resolution zero (coarsest resolution). Right:

resolution one (one level of reﬁnement).

The main contribution of this paper is introducing

a method for accurate (area preserving) visualization

of dynamic geospatial datasets through a framework

for constructing curved-display. Our method is based

on DGGS which provides great ﬂexibility and scala-

bility which is not not available in the spherical dis-

play proposed previously. For example, with our ap-

proach we can have an installation with one or multi-

ple panels at any desired resolution and size, each of

which is associated to a physical place on the Earth.

Using 3D printers, we can easily fabricate a frame for

each panel and then attach them to form curved pan-

els, which are covered by projection paper. Panels

can be used in assembled form or disjointed form, to

compare distant regions of the Earth, side by side (See

Section 4).

The remainder of this paper is structured as fol-

lows. In Section 2, we provide a short review of works

related to visualization of geospatial data and curved-

display projection. Section 3 is dedicated to the

methodology of the introduced framework, which is

organized into three sections: curved-display screen,

setup of the installation, and projection onto the Earth

model. Further, we present some results of the in-

stallation in Section 4. We then discuss the possible

directions that this framework can go as future works

in Section 5.

2 RELATED WORK

In addition to the related papers discussed in the in-

troduction, in this section, some of the related pa-

pers in the the areas of geospatial visualization and

curved/spherical displays are reviewed.

Using 2D maps for geospatial visualization is a

well studied area with a long history (Snyder, 1997).

The main focus of map projection techniques is how

to create a ﬂat instance of the Earth while controlling

and reducing map distortions.

Recently, perhaps due to easier perception, physi-

cal visualization of data has received more attention.

Djavaherpour et.al (Djavaherpour et al., 2017) created

a physical model of Digital Earth and provided sev-

eral printed datasets that can be attached or detached

on top of the physical model to study and for educa-

tional purposes. The main limitation of this work is

how to use it for live and dynamic datasets.

Our work is primarily relevant to the visualization

of Digital Earth datasets, which use a virtual 3D globe

as the medium (Mahdavi-Amiri et al., 2015a). Vega

et.al (Vega et al., 2014) present the main challenges

and beneﬁts of geospatial visualization on a spherical

display. They discussed the beneﬁts of spherical dis-

plays installations including educational applications.

National Oceanic and Atmospheric Administration

”NOAA” (NOAA, 2014) designed a system called

“SOS” or Science On a Sphere (Schollaert Uz et al.,

2014; SOS, 2004), which is a room sized global dis-

play system that projects four high resolution videos

onto a six foot diameter sphere. The set up is designed

to project videos from outside the globe, and the pro-

jection is spherical which may cause misconception

of area and positions. Also, there are other com-

mercialized large spherical displays such as Omin-

isphere (Murphy, 2009) and Hard-Ball (Vega et al.,

2014).

Generally, in these works, spherical mapping is

used to wrap 2D input images/videos on the spherical

displays. However, there is extreme distortion when

we use spherical mapping (particularly near the North

pole and the South pole), and wrap 2D images on 3D

displays. There is a large list of map-projection tech-

niques for reducing or controlling the resulting dis-

tortion (Snyder, 1997). When we map a ﬂat 2D im-

age onto a curved surface, some amount of distortion

(e.g. area, direction, shape) is unavoidable (Snyder,

1997; Gruen, 2012; Sahr et al., 2003; Peterson, 2006).

Depending on the application, the particular mapping

may be used. For example, the famous Mercator map

projection preserves the direction and therefore it is

good when the main purpose of the map is naviga-

tion. However, area is extremely distorted in this type

Area Preserving Dynamic Geospatial Visualization on Physical Globe

311

Figure 4: Various sizes and resolutions of cell-panels. (a) Resolution zero, ﬁnal globe with 1 meter diameter and cell-panel

size around 50×50. (b) Resolution zero, ﬁnal globe with 20 centimetre diameter and cell-panel around 11×11. (c) Resolution

2, ﬁnal globe more than 8 meter diameter and cell-panel size around 60 × 60.

Figure 5: (a) DGGS hexagonal griding model. (b) Imported mesh from DGGS. (c) Designed a frame based on DGGS mesh.

(d) Designing two by two structure inside the frame to enhance curvature. (e) Designing three by three structure inside the

frame to better approximate curvature.

of map, greatly expanding areas near the pole relative

to areas near the equator. Alternatively, map projec-

tions such as Azimuthal area preserving works well

for the purpose of analysis when making comparisons

between sizes of areas on the map.

One approach to reducing distortion is to employ

multiple 2D domains instead of a single domain. For

example, one can better approximate the sphere with

a cube (six ﬂat 2D domains) instead of only one sin-

gle plane. Certainly this can be extended providing

even better approximations if we use a spherical poly-

hedron with more cells than the cube model (Snyder,

1992; Mahdavi-Amiri et al., 2015a). Discrete Grid

Globe Systems use an initial polyhedron for approxi-

mating the Earth’s surface. DGGS are considered as a

“distributed global information system” that provides

an on the ﬂy integration of geospatial datasets (Purss

et al., 2016). HEALPIX (Gorski et al., 2005), SCEN-

ZGrid (SCENZGrid, 2010), HSDS (Goodchild and

Shiren, 1992) and Pyxis’ Digital Earth (Peterson,

2006) are examples of DGGS.

Although, we have used Pyxis system for this

work, our methodology is general and independent

from underlying DGGS.

3 METHODOLOGY

The goal of this paper is to provide the means for pre-

senting dynamic visualization of geospatial data on

a curved-display. We use Pyxis’ DGGS (Peterson,

2006) for discretizing the Earth into several rhom-

bus cells. The cells of Pyxis DGGS are based on

hexagons and higher resolution cells are constructed

through a 1-to-3 reﬁnement (Mahdavi-Amiri et al.,

2015a). The initial polyhedron is a truncated icosa-

hedron (see Figure 2). However, for the purpose

of inter-operability and data transmission a collec-

tion of hexagonal cells are transformed to rhombuses,

using grid conversion (Mahdavi-Amiri et al., 2016).

The resulting rhombuses are also hierarchical. The

ﬁrst resolution (i.e., resolution zero) is constructed

from a spherical icosahedron where each rhombus is

a pair of triangles (see Figure 3 Left). The reﬁne-

ment for creating the multiresolution is a 1-to-9 re-

ﬁnement (Mahdavi-Amiri et al., 2015a) (see Figure 3

Right) (i.e. a 3D mesh).

Using Pyxis DGGS (Peterson, 2006), we can cre-

ate the geometry of the cell and also have access to

geospatial data associated with that cell. Therefore,

if we build our curved-display based on the rhombus

cells, we will have access to a huge amount of data in-

cluding dynamic sets, that can be mapped accurately

to the corresponding rhombus on the display.

3.1 Curved-display Screen

We built our curved-display through 3D printing. We

fabricated a piecewise display where each piece cor-

responds to a DGGS cell at a speciﬁc resolution. We

call these printed pieces cell-panels. For printing

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Figure 6: Different thickness tested when designing the frame of the cell-panels.

Figure 7: When cell-panels are too large, the projection pa-

per is not able to smoothly adapt to the cell’s curvature.

these cell-panels, we need to ﬁrst determine the size

and resolution of the physical globe. The size and

resolution of the globe deﬁnes the display cell-panel

size. For example, if we use the resolution zero, ten

cells will cover the entire globe (See Figure 3, left).

To produce a globe with one meter diameter, the size

of the cell-panels is around 50 × 50 centimetres (Fig-

ure 4-a), whereas for a globe with a 20 centimetre di-

ameter, the size of the cell-panel would be 11 × 11

centimetres (Figure 4-b). For a globe with an eight

meter diameter, the cell size at resolution two (810

cells) is approximately 60×60 centimetres (Figure 4-

c).

For our installation, we chose a one-meter diam-

eter for the entire globe at resolution zero. Conse-

quently, our ﬁnal display made up of cell-panels, each

sized at 50 × 50 centimetres. When fabricating each

cell-panel, we use Pyxis Digital Earth to export the

geometry of the cell as a 3D mesh (Figure 5 a, b). We

only print edges of each cell (Figure 5 c), and in or-

der to make these cell-panels work as screen we will

obtain better image quality if they are covered in a

proper rear-projection screen material. The projection

paper is glued onto the 3D printed frame.

When designing the frame we tested several thick-

nesses as shown in Figure 6. To minimize shadows

and seams in the image, it is optimal to keep these

frames as thin as possible. With our PLA printing

material we found that two millimeters was sufﬁcient

to provide strength and durability with minimal thick-

ness.

As is shown in Figure 7 our cell-panel size of ap-

proximately 50 × 50 centimeters has too much cur-

vature over the surface of the rhombus to be cov-

ered smoothly with the rear projection paper. Con-

sequently we created an internal structure to support

and guide the paper. First, we tested a two by two

internal structure (Figure 5, d) and after covering it

with paper we observed that the problem still exists.

In the next iteration, we tested using three by three el-

ements as the internal structure (Figure 5, e) and the

result was acceptably smooth. Figure 8, (a,c) shows

the ﬁnal result. We also designed and printed clips for

connecting cell-panels as well as stands for stabilizing

and orienting the ﬁnal curved-display (Figure 8 b,d).

For fabricating these cell-panels, we have used

the MakerGear M2 desktop 3D printer. Each internal

structure unit takes around 2 hours to print and uses

less than 2-meters of clear-ﬁlament (USA, 2014).

3.2 Projector Setup

To setup projector devices, we could either use rear or

front projection. The problem with front projection is

the shadows of viewers on the globe. Therefore, we

decided to use rear projection. We have done our ex-

periments with three projector devices available in our

lab. Each projector can feed one, two or more panels.

This panel per projector factor, P can be determined

according to the size of the display and also the pro-

jector specs (i.e. brightness, image size and throw ra-

tio). Our small projector

can easily feed two 50 ×50

display panels. Figure 9 shows different projector se-

tups which we have experimented.

We put each projector in front of its cell-panel in a

way that the center of each projector was perpendicu-

lar to the center of its cell-panel (see Figure 1).

3.3 Projector controller

Naturally, if we point a projector at a piecewise

curved surface, we will have to carefully adjust the

image sent by the projector in order to be sure it is

aligned with the surface and that, particularly because

these surfaces are curved and often not perpendicu-

lar to the projector’s beam (Figure 10). The projector

controller software that accomplishes this was written

in WebGL. The reminder of this section The describes

techniques which this software uses to adjust the im-

age.

Dell: M110 Ultra-Portable Projector HDMI 1280x800

300 ANSI Lumens 10000:1.

Area Preserving Dynamic Geospatial Visualization on Physical Globe

313

Figure 8: (a) Cell-panel with a three by three internal structure, covered with paper (b) Clips for attaching cell-panels (c) Final

curved-display after attaching cell-panels. (d) Final display surface with a stand.

Figure 9: Different projector / panel setups. (a) One projector on one panel covering 10% of the globe. (b) One projector on

two panels covering 20% of the globe. (c) Three projectors on three panels covering 30% of the globe. (d) Two projectors on

four panels covering 40% of the globe.

projector

Figure 10: Projecting onto an angled (a) or curved (b) sur-

face will cause the projected imagery to appear distorted.

To prevent distortion, we use the geometry of

curved cells (i.e. rhombus), as well as measurements

of the projector’s projection to adjust the imagery

(representing the data associated to the cell) before it

is projected. So that it will be positioned correctly on

the model. Sending the image without any wrapping

to compensate the curvature of the display, to the pro-

jector device could create extreme distortion on the

curved display. Therefore, we ﬁrst need to warp the

image to cancel out the curvature of the display. The

geometry of the cell’s 3D model is the main tool for

ﬁnding the warp. To do this, we exactly recreate our

cell’s 3D model as well as the projector’s perspective

projection and the relative positions and orientations

of these two objects in a 3D rendering environment

(in our case, OpenGL). The rendered 2D image will

then, once projected onto the model, display the im-

agery correctly on the surface of the cell’s 3D model.

3.3.1 Modelling the Projection

We start from the assumption that our projector casts

imagery along a frustum. This may not precisely be

the case, particularly when at short distances from

short throw projectors utilizing wide angle lenses, but

in our experience it has been close enough to approx-

imately match the display surface well.

To recreate this frustum within a virtual environ-

ment we need to identify the projector’s projection pa-

rameters. We do this by measuring points on its frus-

tum. Ultimately, given that we work within OpenGL,

we need the following parameters: near plane top n

near plane bottom n

, near plane left n

, near plane

right n

, and the near plane distance D

from the cen-

ter of projection. We assume that the center of the

projection is the origin of our coordinate space.

To ﬁnd these parameters we ﬁrst ensure the pro-

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314

Figure 11: Top-down and side views of measuring a projec-

tor’s projection parameters.

jector is level perpendicular to a ﬂat surface. We mea-

sure the distance from the front of the projector to the

surface D

and the width W

and height H

. The pro-

jectors we used cast their image above the projector

so we also measured the offset between an imaginary

vector perpendicular from the projector to the wall

and the bottom of the image O

(Figure 11). Then we

move the projector further from the wall and measure

these parameters again (D

), D

> D

The main challenge at this point is that we do not

know the distance of each of these two planes from

the center of projection as this distance (let’s label

these d

and d

) will be somewhat different than D

and D

as within the projector neither the lens nor its

light source provide a clear singular, measurable cen-

tral point of projection.

So, we can calculate d

and d

using similar trian-

gles. That is, if we let k = D

− D

= d

− d

(Figure

11) then:

+ k)

and solving for d

yields: d

−W

)

and d

= d

When measuring, we choose D

and D

as rela-

tively large and far from the projector (i.e., 1-2 me-

tres) so our measurements would be as accurate as

possible. However in our virtual setting we want d

be much smaller than D

to avoid potential near clip-

ping in the 3D scene and so we chose a value roughly

. With a value for d

picked then by similar

triangles the near width W

, near height H

, and near

offset O

are:

So the frustum is deﬁned by

) = (−W

/2,W

/2,O

+ H

As we make use of three projectors, one for each

tile, if the projectors are different models, the above

parameters will have to be measured and calculated

separately for each projector.

3.3.2 Aligning the Virtual and Physical Models

The remaining challenge is to place the virtual surface

model in OpenGL to match the alignment of the pro-

jector and the cell-panel in the real world. In our set-

up, to minimize shadows created by the frame within

the Earth surface model we aim to place cell-panel

so that the center of each rhombus is as close as pos-

sible to being orthogonal to the center of projection.

Consequently, our initial alignment in the virtual en-

vironment is orthogonal to the center of projection.

Our software interface provides translation, scal-

ing as well as yaw, pitch, and roll controls to adjust

the virtual environment until a good match is found

with the physical environment.

Our alignment procedure is to place the physical

model and projectors such that the projected image

covers the entire rhombus and that the path between

the projector and cell-panel is not obscured by the

other projectors. Then the virtual model is adjusted;

ﬁrst scale, translation, and roll so that the corners of

the projected imagery roughly align with the corners

of the cell-panel. Then pitch and yaw are modiﬁed

to exactly align the virtual shape with the physical.

Often some ﬁnal ﬁne-tuning of the scale and transla-

tion will be necessary to complete the alignment. This

procedure is independently repeated for each projec-

tor and corresponding rhombus.

4 RESULTS AND DISCUSSION

As proof of concept, we have created several setups,

each with multiple cell-panels. After fabricating each

cell-panel, we set up our curved-display and projec-

tors; for displaying our static and dynamic datasets

on each cell-panel. In each setup, we may need to at-

tach cell-panels (using clips see Figure 8, b). Then,

using the projector controller software, we align the

projected image with each cell panel. This normally

takes less than ﬁve minutes for each conﬁguration

(see Figure 9). Notice that the ﬁrst time setup may

take longer as determining the relative positions of

projectors and cell-panels usually needs some trial

and error.

Our ﬁrst results are from a setup of three pro-

jectors and three panels (see Figure 9, c). Using

this setup we visualize a static dataset of elevation

data shown in Figure 12 a,. Also, a dynamic dataset

(i.e. the global temperature change from 2015 to

2050) (Pyxis, 2017) is presented in Figure 12 b. In

Figure 12 b, we have tried to capture details of the

setup from both outside and inside the curved-display.

This particular dataset is useful in examining potential

Area Preserving Dynamic Geospatial Visualization on Physical Globe

315

Figure 12: Representing various static and dynamic data sets on curved-display. (a) Elevation data. (b) global temperature

from 2015 to 2050.

Figure 13: Animation of dynamic visualization of Global temperature from 2015 to 2050 for Africa.

climate change effects and together with our display

installation allows an analyst (or a group of 3 − 4 an-

alysts) to study this dataset over 30% of the Earth’s

surface.

Figure 14: Data projection on one cell in resolution one,

showing elevation dataset.

Obviously, we can use each individual panel for

display dataset for each rhombus cell which covers

10% of the globe. Figure 13 shows the animation

that presents dynamic visualization of global warm-

ing frame by frame on one panel for Africa. This is

proof of the concept that the introduced framework

is useful for dynamic data visualization on curved-

displays.

Our second setup is two projectors and four cell-

panels (Figure 9, d). With this setup we can project

a dynamic geospatial dataset on 40% of the globe us-

ing two projectors. This setup can be extended to ﬁve

projectors and ten panels and cover the whole globe.

We have used this setup to visualize the global precip-

itation change (see supplementary video).

Further, we have fabricated cell-panels for larger

globe. Figure 14, shows the results of projecting data

on a cell-panel at resolution 2 (see Figure 2). This

cell presents 1/90 of the entire Earth. As it is shown

in this ﬁgure, the panel is more ﬂat than the cells in

resolution zero.

Using our cell-based approach, it is possible to

compare far regions of the globe (e.g. Brazil and

India) side by side (see Figure 15). However, this

comparison is tedious for spherical displays such as

SOS (SOS, 2004).

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316

Figure 15: Using the piecewise nature of our framework,

we can compare India and Brazil side by side.

Figure 16: Visualizing earthquake incidents in Brazil and

Greenland on the world 2D Google map.

As mentioned in the Introduction, one of the

unique features of our method is the use of area pre-

serving projection. Projecting from the surface of the

Earth to 2D maps could create extreme area distor-

tion. Figure 16 shows an example of Mercator maps

used in common map software. In this Figure, Green-

land and Brazil are highlighted. Although in this map

Brazil seems smaller than Greenland, in reality it is

four times larger than this island (see Figure 17).

This area distortion creates misinterpretation and

potentially wrong visual analysis. For example if we

visualize the number and locations of recent earth-

quakes, it seems, that Greenland has a lower risk of

earthquakes, which is not correct. Figure 18 shows

the visualization of earthquake incidents in Greenland

and Brazil projected on one of our setups.

5 CONCLUSION AND FUTURE

WORKS

In this paper we introduced a DIY method for creat-

ing physical globe a a curved-display for projecting

geospatial dataset. Our method is ﬂexible and relies

on off-the-shelf tools with easy installation process.

Figure 17: Visualizing earthquake incidents in Brazil and

Greenland on a digital model of the globe from Pyxis World

View Studio.

Figure 18: projecting Brazil and Greenland on the curved

display with more realistic sizes. Earthquake incidents vi-

sualizations have been.

We employ DGGS (Pyxis) for decomposing the Earth

to the uniformly sized cells. This system is also used

for access many geospatial datasets. Finally, we de-

veloped a projector controller that takes the geometry

and data of cells and adjusts it for the projector.

There are several directions to extend this work.

One natural direction is to create a setup for entire

globe. Also, improving the design of cell-panels such

that the shadow effect could be reduced.

ACKNOWLEDGEMENT

This work was supported in part by the Natural Sci-

ences and Engineering Research Council of Canada

(NSERC) and PYXIS Innovation. Also, we would

like to thank Mark Sherlock for his help in preparing

dynamic datasets for this project.

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