Geovisualization: Multidimensional Exploration of the Territory

Sidonie Christophe

Paris-Est University, IGN ENSG, LaSTIG, France

Keywords:

Geovisualization, Visual Analysis, Style, Interaction, Immersion.

Abstract:

The purpose of this position paper is to emphasize the remaining challenges for geovisualization in an evo-

lutive context of data, users and spatio-temporal problems to solve in an interdisciplinary approach. Geovi-

sualization is the visualization of spatio-temporal data, phenomena and dynamics on earth, based on the user

interaction with heterogeneous data, and their capacities of perception and cognition. This implies to bring

closer together knowledge, concepts and models from related scientiﬁc visualization domains, for a better un-

derstanding, interpretation and analysis of spatio-temporal phenomena on earth. We currently face and cross

several types of complexities, regarding spaces, data, models and tools. Our position here, based on past and

on-going works, as ﬁrst proofs of concept, is to model a multidimensional exploration of the territory, because

integrating explorations of uses, styles, interaction and immersion capacities, until various ’points of view’ on

the represented spatio-temporal phenomenon.

1 INTRODUCTION

The amount of heterogeneous geospatial data, multi-

sensors, multi-sources, multi-scales, more or less pre-

cise, and more or less massive, motivate the users

to visualize them all together, in addition to textual

archives, iconographic collections and any possible

spatialized information (co-visualization). Addition-

ally, the users expect tools offering ways to navigate

into all those data, through space and time (naviga-

tion). For scientiﬁc purposes, some users need to de-

tect changes, breaks, and artifacts in data, to com-

pare sources and imprecision, to compare measures

in time, simulation, prediction scenarii, or learning

models. For general public purposes, characteris-

tics of a spatial issue on earth have to be explained,

graphically synthesized and should support collabo-

rative mediation. Those typical user needs require to

visualize a spatio-temporal data, phenomenon or dy-

namics from various possible points of view (multi-

dimension). Even if cartographic, geovisualization

or datavisualization tools exist, no visualization sys-

tem is now able to offer ﬂexible multi-dimensional vi-

sualization of spatio-temporal information, based on

the navigation into geospatial ans spatialized data, to

ease the visual reasoning on complex spatio-temporal

dynamics on earth. Geovisualization is the set of

knowledge, methods and tools favoring the visualiza-

https://orcid.org/0000-0002-2980-2803

tion and the visual analysis of geographic spaces and

spatio-temporal phenomena, based on the user inter-

action with geographic or spatial data (MacEachren

and Kraak, 2001; Dykes et al., 2005).

We would like to emphasize that geovisualization

is most of all related to the all methodological ap-

proach and the modeled processes of both graphic

representation and rendering of, and the interaction

with, geospatio-temporal information, enhancing the

knowledge inference on geographic spaces and spa-

tial phenomena. The purpose is to ”see, perceive and

understand”, based on the user exploration of data

and graphic representations, while preserving what

could be meaningful for the users into the represented

geographic spaces and phenomena. Similarly to in-

formation visualization and data visualization, but

geospatial-oriented, geovisualization should facilitate

both the exploration of the geospatial data and the

ﬁrst steps of visuo-spatial interpretation. Geovisu-

alization is not only about designing new technolo-

gies for co-localized geospatial data visualization, but

also about addressing the complexity to visualize a

spatio-temporal phenomenon interacting with the re-

lated geographic spaces. Through years, the context

has evolved from challenges already existing but that

have become more pronounced over time. More het-

erogeneous, imprecise and massive spatial and non-

spatial data are available to be combined and hy-

bridized for visualization; a diversity of users expects

to visualize complex spatio-temporal phenomena in

Christophe, S.

Geovisualization: Multidimensional Exploration of the Territory.

DOI: 10.5220/0009355703250332

In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 3: IVAPP, pages

325-332

ISBN: 978-989-758-402-2; ISSN: 2184-4321

325

order to see, explain, analyze and understand complex

spatial dynamics and systems; ﬁnally, user interaction

and interfaces allow to investigate innovative modes

to explore data and to virtually or in an augmented

way experience geographic spaces. Geovisualization

is about bringing knowledge, concepts and models

for a better understanding, interpretation and analy-

sis of spatio-temporal phenomena on earth. This is

an interdisciplinary, and even transdisciplinary ﬁeld:

geovisualization aims at specifying and integrating

new models of abstraction, representation, perception

and cognition related to geographic spaces, with the

help of and contributing to geographic information

sciences, HCI, computer graphics and cognitive sci-

ences. In this position paper, we aim at emphasizing

and revisiting essential challenges for geovisualiza-

tion, in specifying how the issue of the visualization

of spatio-temporal data could be addressed as a mul-

tidimensional exploration problem, based on our own

research approach.

2 GEOVISUALIZATION

Geovisualization integrates approaches from ”visu-

alization in scientiﬁc computing, cartography, im-

age analysis, information visualization, exploratory

data analysis, and geographic information systems

to provide theory, methods and tools for visual ex-

ploration, analysis, synthesis, and presentation of

geospatial data” (MacEachren and Kraak, 2001). It

refers both to the science and the techniques to design

and use ”visual geospatial displays to explore data

and through that exploration to generate hypotheses,

develop problem solutions and construct knowledge”

(Kraak, 2003). Since, the main trend is still to iterate

from the users needs, in order to design and to han-

dle effective geovisualization techniques (N

ollenburg,

2007; Lloyd and Dykes, 2011), and to connect peo-

ple, maps and processes to acquire knowledge (Dykes

et al., 2005). The challenge of enhancing spatial anal-

ysis based on visual media is related to geovisual an-

alytics (Andrienko and Andrienko, 2005; Keim et al.,

2008; Andrienko et al., 2014; MacEachren, 2015),

that we consider to be a part and a purpose of our

’geovisualization issue’. This raises issues of inter-

related design and use, for geospatial data explo-

ration, based on but also leading to issues of percep-

tion and cognition. The main challenges for geovi-

sualization designers is to take into account the set of

the following complexities: 1- Geographic spaces and

data to handle; 2- Spatio-temporal phenomena and

models to represent; 3- Visual integration and interac-

tive or even immersive exploration of data, to design.

Geographic Spaces and Data. A geographic space

is characterized by its terrain, landscapes, natural and

artiﬁcial entities, shapes, volumes, structures and ar-

rangements, modeled into heterogeneous, imprecise

and massive spatial data, according to acquisition

methods, sources, scales, data types, etc. The descrip-

tion and analysis of geographic spaces and their in-

teraction with other dynamic systems on earth come

mainly from geography and geosciences. We face an

amount of geospatial data (vector databases, maps,

various imagery, 3D models, numeric models, point

clouds, etc.) but also non-spatial data (texts, stories,

web data, statistic data, photographs, etc.) that can be

spatialized. The handling of the suitable scale to man-

age, while preserving the spatial arrangements of the

territory, as having a proper positioning or controlled

level of uncertainty of the geolocalization of things

are at stake here. Graphically representing these ge-

ographic spaces and phenomena requires to preserve

spatial coherence of the information, related to their

geometry, topology and semantic, while preserving

their structure and their meaning. Visual perception

and spatial cognition play a great role there to drive

representation choices. Massive geospatial data bring

us also to go closer to image rendering performance,

for real time purposes, visualization of simulated data

or Lidar data, or 3D streaming. In geovisualization,

we sometimes face a kind of dichotomy between the

abstraction paradigm, coming from map design and

vectorial spatial data handling, and the photo-realism

paradigm, coming from image processing and com-

puter vision based on the acquisitions of 3D+T laser

or images on earth. This dichotomy exists also into

the various sets of knowledge and methods, coming

from map design, image processing and computer vi-

sion, to represent spatio-temporal information.

Spatio-temporal Phenomena and Models. Ad-

vances in modeling and simulation of physical, so-

cial, historical of spatio-temporal phenomena and dy-

namics need more and more visualization support, for

visuo-spatial analysis purposes. How could visualiza-

tion effectively help to support perception and inter-

pretation of data and related phenomena? Knowing

that a phenomenon could be represented by raw, pre-

dicted, simulated, learned data, another complexity

comes from acquisition sensors and input models, and

their related imprecision to be (visually) propagated.

Approaches to handle time and dynamics have been

deeply investigated through years, in order to support

visual analytics, visual reasoning, and change detec-

tion, based on innovative space-time cube (Andrienko

and Andrienko, 2005) and leading to researches in the

spatio-temporal analysis of movement, and in partic-

ular trajectories and human-based activities. 3D per-

IVAPP 2020 - 11th International Conference on Information Visualization Theory and Applications

326

spectives or simpliﬁed graphs (Hurter et al., 2009)

such as generalized space-time cubes have been pro-

posed (Bach et al., 2017) in order to explore data.

In parallel, uncertainties of data (positional and se-

mantic accuracy, logical consistency and complete-

ness), models and phenomena remain difﬁcult to con-

vey and is still a major issue for geovisualization: vi-

sual variables have been explored and experimented

(MacEachren, 2015; Bevis et al., 2017). Color

palettes for geo-physics phenomena are still in ques-

tion to improve scientiﬁc analysis and sharing (Spekat

and Kreienkamp, 2007; Thyng et al., 2016), but also

remain questionable. The issue of quality regarding

scientiﬁc visualization, balanced with aesthetic issues

is also discussed (Hanson, 2014). Spatio-temporal

representations and animations are more and more

used, in order to serve continuous animated visualiza-

tions of long-time data, for instance on earthquakes

evolutions

, such as remarkable data visualizations.

Nevertheless, even if animations are very useful to

improve the global perception of a spatio-temporal

phenomenon and its general patterns, it remains difﬁ-

cult to detect and analyze changes, at any scales. In

addition, the beautiful and so efﬁcient graphic repre-

sentation of warming stripes for climate data visual-

ization is particularly relevant and has a strong public

impact: nevertheless it is quite not adapted to com-

plex visual analysis of climate change, regarding dy-

namic geographic spaces and other dynamic geophys-

ical systems, even some parameters may be used to

compare, show and extract time periods and identify

some effects (Hawkins, 2018).

Visual Integration, Interaction and Immersion.

Co-visualizing data, i.e. visualizing them together

in a single visual display, implies difﬁculties caused

by the potential number but also the potential hetero-

geneity in source, scale, content, precision, dimen-

sion and temporality. This visual integration requires

to ﬁgure out graphic representation aspects to pre-

serve legibility when combining heterogeneous data

and sometimes numerous ones. Visual complexity

is a major stake and innovative measures and anal-

ysis have been propose to drive better geovisualiza-

tion techniques (Schnur et al., 2010; Da Silva et al.,

2011; J

egou and Deblonde, 2012). Because the im-

age processing approach here is not suitable to cap-

ture semiologic and cognitive complexities of geo-

visualizations, or local complexities (Touya et al.,

2016). Geovisualization strengthens and revisits the

map design process, i.e. a series of choices regarding

conceptual, semantic, geometric, graphic abstractions

of geospatial reality. Abstraction and schematization

have been addressed by information visualization for

https://volcano.si.axismaps.io/

cartography (Isenberg, 2013; Kim et al., 2013) until

sketchiness techniques evaluation (Boukhelifa et al.,

2012; Limberger et al., 2016). We claim here for a

closer methodological approach between the ’abstrac-

tion’ paradigm and the ’photo-realism’ paradigm, in

order to take advantages from both for the visual in-

tegration of data. Various research works propose

managing continuous transitions in a same visual-

ization, for instance between levels of abstraction,

according to the distance from the image center or

some rendered objects, to the scene depth, in ren-

dering styles or through scales (Semmo et al., 2012;

Trapp et al., 2015; Dumont et al., 2017). Multi-

plexing tools have been investigated, in order to fo-

cus on some parts of the visualization or some ob-

jects in the visualization (Pietriga et al., 2010; Pindat

et al., 2012) opening a main lead for the visualiza-

tion of several data types. Interaction is meant to fa-

vor exploration and perception of represented scenes,

leading to immersion into virtual scenes, augmenting

the real environment: numerous applications of aug-

mented and virtual reality have been investigated for

many use cases (Milgram and Kishino, 1994; Schmal-

stieg and Reitmayr, 2007; Normand et al., 2012).

Augmented and mixed realities are opportunities, for

urban design and dynamics comprehension such as

non-visual perceptions, to experiment spatial percep-

tion, interaction and cognition, supporting analysis or

enriching a multi-sensorial experience. These new

devices require adaptation for geovisualization and

visuo-spatial analysis, probably inspired by 3D geo-

visualization (Devaux et al., 2018), not to be only

gaming-oriented or movie scenarii, but use-oriented

(Jacquinod and Bonaccorsi, 2019), and targeting the

Immersive Analytics (Chandler et al., 2015).

3 MULTI-D EXPLORATION

The multidimensional characteristic of data and phe-

nomena implies to be able to go from one represen-

tation to another, from a dimension to another, from

a point of view to another, while: 1- facilitating the

exploration, 2-without loosing visual landmarks and

attention. We tackle the ’geovisualization issue’ as a

multidimensional exploration of the territory. We aim

at conceiving an interactive system, allowing to de-

sign and use visualizations, based on the exploration

of possible heterogeneous data and styles, through

space and time, supporting to observe, analyze and in-

terpret possible spatio-temporal phenomena on earth.

This ideal system should favor some responsiveness,

in order to co-design with the users, provide guidance

to ﬁnd the most suitable visualization for a use con-

Geovisualization: Multidimensional Exploration of the Territory

327

text, and provide ways to explore and design possible

visualizations. These requirements need to orches-

trate the main components of this exploration, based

on the knowledge of the sets of parameters, operators

and constraints. This purpose can only be fed by the

identiﬁcation of the main categories of problems to

solve, in order to formalize and integrate them into

a semi-automatic system of geovisualization, such as

the following ones: 1- the capacities to respond to

various uses; 2- the navigation into graphic represen-

tations through style exploration; 3- the exploration

of data interaction and immersion possibilities; 4- the

exploration of points of view, from the user location

to their intentions. We think that they should be ad-

dressed further and deeper, with the help of a cross-

disciplinary approach, from other visualization do-

mains.

3.1 Use Exploration

As input knowledge for geovisualization, geographic

approaches or direct observations help to identify the

users needs, such as many user studies on preferences

and task performance help to assess the efﬁciency and

the usability (Fabrikant and Lobben, 2009; Slocum

et al., 2001). Use contexts have to be investigated, in

order to explicit meaningful entities and structures of

geographic spaces and the phenomenon in issue (Grif-

ﬁn et al., 2017).

Retrieving Users Needs. To make the users express

what is relevant for them, is difﬁcult to drive on the

ﬁeld, and is actually done through geographic ap-

proaches, but still remains difﬁcult to approach semi-

automatically. For scientiﬁc purposes, if researchers

want to visually analyze the results of a simulation,

prediction or learning model, it will be relevant to

identify with them what is meaningful to actually ob-

serve, according to their use context. For general pub-

lic, it would be useful to better explain phenomena

and their underlying uncertainties. For a ﬂash ﬂood,

some could investigate a precise maximal extent in

time related to possible submersions, affected build-

ings during a water ﬂood, or various prospective sce-

nari of rising water levels, with the help of the same

geovisualization system (Fig.1). Visualization could

help to show and compare realistic simulations or sce-

narios, interpret results from simulation, prediction or

learning models, or the gap between predicted and ob-

served data on earth, in order to reﬁne a model; it

should also support the automatic detection and iden-

tiﬁcation of artifacts, patterns, breaks, changes, out-

liers, weak signals, in input data and initial conﬁgu-

rations of models; but also to explore a phenomenon,

in its various dimensions, spatial, temporal but also

in the initial parameterization and/or measures. The

exploration of the spaces of initial parameters and ob-

servations of the models, to visually compare various

scenarios, and possibly to modify the computation pa-

rameterization in real time.

Improving Models of Perception and Cognition.

Concerning user-centered approaches, a convergence

of Geographic Information sciences with psychology

and cognitive sciences (Davies et al., 2015; Martin,

2008) exists for a long time ago, in order to address

what help people read and think on spaces and their

related representations. Nevertheless, it remains dif-

ﬁcult to go out visual perception issues and to model

properly spatial perception and cognitive dimensions.

A well conducted experimentation requires the def-

inition of low level tasks in a simpliﬁed geographic

space, in order to correctly validate the hypothesis.

But in geovisualization, tasks are complex and made

in a complex geographic space, not facilitating the

speciﬁcation of independent hypothesis, the design of

controlled experimentation and the reproductibility of

those experimentation. This implies to be able to re-

trieve rules and constraints coming from the use con-

texts, and to design models of perception, cognition

and use for visuo-spatial reasoning.

3.2 Style Exploration

The style is simply deﬁned as a ”set of formal and

aesthetic characteristics of something” and ”a man-

ner to practice something, deﬁned by a set of char-

acteristics”, in the dictionnary. Based on the deﬁni-

tion of a pictural style, coming from linguistics and

computer graphics knowledge (Willats and Durand,

2005), we reformulate the style as all what makes

distinguishable and recognizable the way to design a

graphic representation, based on the implicit knowl-

edge of graphic rules and perhaps grammar rules,

required to generate this representation. The style

refers to a typical family of representation choices,

recognizable with the help of a set of visual salient

characteristics. The hypothesis to use styles is to fa-

cilitate the decoding of spatial information, by han-

dling the repeated experience of reading one style, re-

lated to memorization and learning. When reading

a graphic representation, a series of mechanisms of

vision, perception and cognition is triggered, based

on the visual arrangements, related to spatial arrange-

ments in the real scene and typical from representa-

tion choices of an author, an institution, a period of

time, etc. We experiment a reconciliation between

computer vision and map design, with the common

purpose of spatio-temporal analysis and visualization

of geospatial data, while combining knowledge and

IVAPP 2020 - 11th International Conference on Information Visualization Theory and Applications

328

Figure 1: Flood visualizations: animated water rising in 3D (1)(Masse and Christophe, 2015); affected buildings during ﬂash

ﬂoods (2); comparison between prospective scenarii (3) experimented in iTownsResearch

methods to get more a ﬂexible approach of the geo-

visualization methods and tools. Combining abstract

and photo-realist styles, while bringing graphic semi-

ology (Bertin, 1967) into the 3D paradigm, and ren-

dering capacities into (carto)graphic representations,

are the main leads.

Specifying Styles for 2D, 3D, 3D+T or

3D+measure. The speciﬁcation of styles could

allow leveraging the levels of visual, perceptive and

cognitive complexities potentially coming from the

phenomenon to be represented and the related data.

Capacities provided by (carto)graphic abstractions

and expressive renderings methods (Barla et al.,

2007) allowed us to specify several typical carto-

graphic styles targeting expectations to have more

expressiveness, visual effects, some kind of ”relief”

and animation, in ﬂat surfaces and classical linear

provided by GIS systems and related rendering

engine: watercolorization, engraving, old map styles

are speciﬁed and rendered (Christophe et al., 2016).

These expressive methods are transferred to 3D, in

order to provide a set of abstract styles, from a very

simple to more sketchy one, in order to manipulate

abstract buildings, and help the users to focus on their

volume and distribution in empty spaces, and not on

possible details provided by photo-realistic textured

models (Cf. Fig.2). At the contrary, a very realistic

3D geovisualization, based on a high level of detail

will perfectly ﬁt to virtual and/or historical visits

into the past of the city, or to represent realistically a

physical phenomenon. Hybridizing & Optimizing

Styles. Going further than transparency has led us

to mix data and styles and to provide interaction

tools allowing to control the level of hybridization

between photo-realistic and abstract styles: we

initiate a continuous transition between orthoimagery

and vector data, in order to take advantages from

expressivity and efﬁciency of both styles, based on

the interpolation of graphic parameters, that could be

independently controlled by the users, to design and

reﬁne the way to drive each interpolation of parame-

ters (color palette, image textures, generated textures,

abstract patterns) (Hoarau and Christophe, 2017).

The design of optimization methods would offer to

explore the space of possible styles of representa-

https://itownsresearch.github.io/

tion in geovisualization, based on the interpolation

between the sets of graphic parameters of styles,

and related rendering operators. From color and

texture interpolation (Hoarau and Christophe, 2017)

to the optimization of the space of constrained color

palettes (Mellado et al., 2017), we experimented ﬁrst

steps. Extending existing works on style transfer

(Gatys et al., 2016; He et al., 2017; Liao et al., 2017)

to our complex problem would be relevant to follow.

Figure 2: 3D Abstract styles(Brasebin et al., 2016).

3.3 Interaction, Immersion

Covisualization. In the context of Geographic In-

formation Systems (GIS), the ”multi-layer” paradigm

prevails, but only global transparency between layers

does not allow to explore data. Hybridization of data

and styles required data interpolation: we propose a

continuum between cartographic representation and

satellite imagery, based on color and texture inter-

polations, in order to get more photo-realism in the

abstraction, and conversely. This approach has been

pursued in a interdisciplinary approach with human-

computer interaction, about the design and experi-

mentation of multiplexing cartographic tools allow-

ing to improve co-visualization of heterogeneous data

and multi-scale navigation (Lobo et al., 2017).

Augmented Perception. We face the possibility to

enrich the user experience, with the help of 3D inter-

action and an enriched perception, not only visual, of

their environment. Our purpose here is to facilitate

the understanding of 3D models and related spatial

structures and arrangements making the urban mor-

phology. To visually analyze how a physical phe-

nomenon could interact spatially with the urban mor-

phology is at stake there, for a sea level rise or mi-

croclimatic factors, evolving into the city, in all pos-

sible dimensions. Again this issue requires to take

into account what is meaningful in the characteris-

tics of the phenomenon, but also the relevant topo-

graphic data or other data conveying meaning for vi-

Geovisualization: Multidimensional Exploration of the Territory

329

Figure 3: Urban design with augmented reality glasses: removing of and adding a building (Devaux et al., 2018).

sual analysis. In the context of urban design, we pro-

pose an extension of a classical desktop 3D geovisu-

alization into mixed reality, in order to identify the

components of the geovisualization pipeline needing

to be re-adapted or extended (rendering, stylization,

3D interaction), and new components to take into ac-

count more speciﬁcally (pose estimation, occlusions,

inpainting). This kind of application requires not only

the integration of a high quality level of the 3D model,

coming from a photogrammetric acquisition, to get

the scene captured by the augmented reality device,

but also to design intuitive interaction with the aug-

mented data, whatever the resolution of the 3D model

or the visualization scale. Various experimentations

are made – scale modiﬁcation, geometric adaptation

between virtual and real scenes, style matching be-

tween added objects and existing objects in the scene

– allowing the interaction et the hybridization of real

and virtual. For urban design purpose, we design a

use case about the implantation of a new building re-

quiring to remove the previous one, with potential dif-

ferent volume, ground surface, facades textures, with

the help of glasses of mixed reality (Fig.3)(Devaux

et al., 2018). These approaches have to be pursued

and are actually experimented in various use contexts,

based on historical or climate data, to improve the vi-

sualization of urban spaces.

3.4 ’Points of View’

The multidimensional exploration of the territory is

ﬁnally an exploration of various points of view on

the territory. This notion may cover the following as-

pects, but has also to be taken in a more conceptual

way. It could be: 1- the location of the user or the

camera, through a numeric device or not; 2- the var-

ious angles or axes, from which a phenomenon can

be visualized, as elevation (street-level, oblique, ortho

views, for instance), depth, time, etc.; 3- the way to

conceptually and formally represent a phenomenon:

a measure, a probability distribution, a scalar ﬁeld, a

graph, etc.; 4- the intention of the author, and the way

the author may control their message to convey, i.e. an

’intentional’ point of view; This proposition implies

to control, orchestrate the multiple possible explo-

rations, help the users to take beneﬁt from modifying

their point of view, according to their own use con-

texts, and effectively to explore data in a multidimen-

sionnal way. This is this exploration of the diversity of

possible geovisualization designs which will bring us

closer to ﬁt to the diversity of users and uses. To en-

rich perception until immersion, in order to be into the

geographic space, more or less virtually: this issue of

the experience, which could be multi-sensorial, asks

to be experimented in the context of spatio-temporal

phenomena related to geographic spaces.

Beyond Vision? When vision is missing or failing,

we could ask rightly if ’geovisualization’ still has a

meaning there. We argue that the ”to perceive and

to understand” is still relevant and similar challenges

remain to provide a mental representation of the ter-

ritory. This requires a complete revisit of the needed

entities meaningful for mobility, to be represented for

blind people. This extension of ’geovisualization’

motivate us to propose new cognitive model of geo-

graphic space representation, to support this spatial

perception and real mobility tasks. Complex notions

for spatial cognition, such as obstacles, empty spaces,

hazardousness, uncertainty are a huge challenge for

the better understanding of spatio-temporal informa-

tion.

4 CONCLUSION

We claim for a cross-over between domains, in or-

der to model how the visuo-spatial reasoning works,

especially regarding complex tasks, as scientiﬁc and

decision-making purposes, such as explanation and

communication for ﬁnal users. To be able to inter-

face simulation, learning, or prediction models to vi-

sual analysis, will allow to facilitate and enrich the

capacities of interpretation and comparison of mod-

els, simulations and scenarios, in addition to clas-

sical approaches of spatial analysis, in order to de-

tect artifacts and changes, in space and time. We

hope that visualization could facilitate the ﬁrst steps

of decoding, reasoning and learning. In particular, the

issue of the interpretability of spatio-temporal data,

from raw to simulated ones, could help to visually

analyze geophysical, climatical, socio-demographic,

historical phenomena and dynamics on earth. We

assume that challenges are still remaining in order

to reach the ﬁnal goal: how geovisualization could

effectively participate to visuo-spatial reasoning un-

IVAPP 2020 - 11th International Conference on Information Visualization Theory and Applications

330

til the famous decision-making? In particular, un-

certainty and decision-making are still investigated

and experimented (Padilla et al., 2018; K

ubler et al.,

2019) and we hope to be able in the future to use these

experiments to guide graphic representation choices

for a better visualization of spatio-temporal data on

earth.

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