Lesson10：Geovisualization

Part1 Beautiful Visualization

1.Why do we create visualizations?

• To expose ideas/relationships

• To make an argument

• To observe trends

• Summarize/aggregate data

• Archiving

• Trust

• Advertise ideas

• Exploratory data analysis

• Answer questions

• Make decisions

• See data in context

• Expand memory

• Support graphical calculation

• Find patterns

• Present argument

• Tell a story

• Inspire

2. Three functions of Visualizations

• Record information – Photographs, blueprints, …

• Support reasoning about information (analyze)

– Process and calculate

– Reason about data

– Feedback and interaction

• Convey information to others (present)

– Share and persuade

– Collaborate and revise

– Emphasize important aspects of data

3. What Is Beauty?

What do we mean when we say a visual is beautiful? Is it an aesthetic judgment, in the traditional

sense of the word? It can be, but when we’re discussing visuals in this context, beauty can be

considered to have four key elements, of which aesthetic judgment is only one. For a visual to

qualify as beautiful, it must be aesthetically pleasing, yes, but it must also be novel, informative,

and efficient.

Part2 Geovisualization

M. J. Kraak. Inlamational Institute of Goo-lnlormation Science and Earth Observation. EThe

NETHERLANDS@ 2009 Elservier Ltd.

1. Glossary

Cartography The art. science, and technology of making and using maps.

Geovisualization A loosely bounded domain that addresses the visual exploration,

analysis, synthesis, presentation of geospatial data by integrating approaches from various

disciplines including cartography with those from scientific visualization, image analysis,

information visualization, exploratory data analysis, visual analytics, and GI Science.

Map A symbolized representation of a geographical reality, representing selected features and

characteristics, resulting from the creative effort of its author’s execution of choices, and is

designed for use when spatial relationships are of primary relevance.

Visual Thinking The thinking process that results from interacting with graphic

representations such as maps and diagrams.

2. Introduction

Maps are familiar to all of us. Everyday decisions are made based on maps and the geographic

information they represent. This varies from simple route-finding from A to B, to locating an

event from the news, or studying a weather map. In a professional environment the examples are

more complex and might include planning a new railroad, assisting during an earthquake disaster,

or understanding the global spread of the bird flu. Maps offer us insight in our geoenvironment,

because they have the ability to present, synthesize, analyze, and explore the real world. Maps do

this well because they only present a selection of the complexity of reality and visualize it in an

abstract way. The cartographic discipline has developed a whole set of design guidelines to

realize the most suitable map that offers insight in spatial patterns and relations. In general,

professional geographers don’t have to be convinced of the unique qualities of maps to express

their ideas, to make a point, to obtain new knowledge, communicate with colleagues, and of

course to orientate and navigate. Maps are also appreciated outside the professional community.

Maps have been used throughout history and across alt cultures in day-to-day activities.

Recent technological and societal developments have acted as a positive stimulus for map

creation and use, both for professional and for nonprofessional users. The recent success of

products like Google Maps and Google Earth has demonstrated this. Both products combine an

intuitive interface with a good map design, a wide availability of data., and the possibility of

linking your own data to the maps and satellite imagery. It has resulted in a tremendous increase

in the number of maps produced and disseminated, and allows the wider public to participate in

the mapping process. In addition, maps that used to be complicated to produce can now be

created to present many alternative views by the single click of the mouse.

However, this last aspect is not always realized because the view on maps is often limited to

its presentation function. Even the professional geographer might not be fully aware of the

possibilities. Although it has to be realized that the traditional role of a map to 'present' is still

very much valid, today’s challenge is to see the map as a flexible interface to geospatial data,

since it offers interaction with the data behind the visual representation. The interactive and

dynamic environments in which maps are used, often in combination with other graphic

representations, encourage exploration. As such they are used to stimulate (visual) thinking about

geospatial patterns, relationships, and trends. The contexts where maps like this operate have led

to an extended view on cartography, and can be deemed the world of geovisualization. This can

be described as a bounded domain that addresses the visual exploration, analysis, synthesis, and

presentation of geospatial data by integrating approaches from disciplines including cartography

with those from scientific visualization, analysis, information visualization, exploratory data

analysis, visual analytics, and GI Science.

3. Nature of Geovisualization

The above developments in the integration of and techniques used by different disciplines is a

logical step, especially because many challenges being faced in the natural and social sciences

have an inherent complexity and interdisciplinary nature. Examples include: how to assess the

vulnerability of regions and their human populations to global environmental change ;how to

measure and sustain biodiversity; how to predict an cope with changing disease incidence

patterns ; and how to manage the increasing traffic flows of cities more effectively. For each of

these problems, georeferencing provides a fundamental mechanism for linking the diverse

forms of data needed to attack these problems. Currently no fully developed, integrated models

of complex human and environmental systems exist. The international research community tries

to come to solutions from different perspectives. The geovisualization perspective has the

potential to provide 'windows' into the complexity of phenomena and processes involved,

through innovative scene construction, virtual environments, and collaboration, thus prompting

insight into the structures and relationships contained within these complex, linked data sets.

The nature of geovisualization research is wide-ranging and in the research agenda established

by the international cartographic community, particular areas have been identified. These focus

areas are closely interrelated and should be seen in connection with each other. They include

representation, visualization-computation integration, interfaces, and cognitive/usability issues.

3.1 Representation

In the past, cartography had a more or less fixed set of options available for a correct graphic

representation of any type of geographic data. Today technology offers many new

extensive opportunities for which the application of existing methods are less certain.

Examples are animation, hyperlinking, immersive environments, and multimodal

interfaces. Despite these advanced technology-driven options, the available software does not

cater for all possible map types available, because these require typical human creativity to create.

Interaction and dynamics are today a default component of the representation tool box. In

addition, the amount and complexity of the data to represent is increasing. Large multivariate

spatiotemporal data set, including the third dimension as well as time,are available and have to

be understood. Based on these observations, there is a need to consider conceptual and

technological issues:

to develop a theory for georepresentation and formalizing representation methods,

to develop new forms of representation that support the understanding of geospatial

phenomena and space-time processes,

to adapt representation methods to meet the changing nature of data to be represented,

to adapt representation methods to the increasing range in kinds of tasks that visual

geosparial representations must support, and

to take advantage of recent (and anticipated) technological advances in both hardware and

data formats.

3.2 Interaction Forms and Interface Design

In a visual environment the interface is most important, should intuitively be able to execute

the tasks they have in mind. This is not trivial, because the geovisualization environments are

often composed of multiple coordinated views, each of which give a different view will result in

cooresponding changes in other views. Next to the use of the large screens that support these of

mobile devices can be witnessed as well. To make it all work one has to

extend our understanding of interface design to take advantage of the potential of virtual

environments,

develop and assess formalizations for specifying interface operations appropriate to

geovisualization environment,

develop a comprehensive user-centered design approach to geovisualization usability,

develop the understanding and mechanisms for capitalizing on the potential of

geovisualization to prompt creative thinking,

extend our undestanding of metaphor for geovisualization, and

investigate interfaces to support the digital earth and the concept of digital earth as an

interface.

3.3 Integration of Visualization and Geocomputation

Although a visual approach to problem-solving is very strong, it cannot do without

computational support. Most graphic actions that are initiated require computational support, and

again graphics are needed to get an insight in computational results. What needs to be done is to

address the engineering problems of bringing together disparate technologies,

explicitly incorporate the location and time components of multivariate data within visual

and analytical methods,

represent geographic knowledge,

incorporate geographic meaning within visualization environments,

develop visual approaches to geospatial data ming,and

integrate visual and computational tools that enable humans and machines to collaborate in

knowledge construction.

3.4 Cognition and Usability issues

It is good to see how new tools can be used in one's discipline, but it is even better to know if

those tools work - in other words, to consider th implications of new forms of representation and

interaction. Usability studies have to developed to see when and why the tools do work and for

whom. Here the geovisualitzion community can draw upon experiences in the field of human

computer interaction. This requires:

development of cognitive theory to support and assess geovisualization methods in VE &

dynamic display,

development of an intergrated understanding of metaphors and knowledge schemata for

geovisualization interface design,

understanding individual and group differences related to use and usability of

geovisualization,

extending our perspective on cognitive and usability issues associated with geovisualization

to contexts involving group work,

determining contexts in which geovisualization is successful, and

developing methods and tools that will enable the kinds of cognitive and usability research

called for.

The four focus areas are interdependent, and are all related to integrated technologies that cake

advantage of the potential offered by increasingly experiential representation technologies

(multimodal maps), to the methods and tools that enable understanding of and insight into the

increasingly larger and more complex geospatial data sets, and to a new generation of

geovisualization methods and tools that support group work, and human- centered approaches to

geovisualization.

4. Alternative Visual Representations

In a geovisualization environment, maps are used to stimulate (visual) chinking about

geospatial patterns, relationships, and trends. One important approach here is to view geospatial

data sets in a number of alternative ways, for example, using multiple representations without

constraints set by traditional techniques or rules. This should avoid the trap that most researchers

tend to rely on, that is, well-worn procedures and paradigms. Instead they should realize that

creative discoveries, in both art and science, often occur in unusual situations, where one is

forced to think unconventionally. In these circumstances it is better to remove mental roadblocks

and create some distance from the discipline in order to reduce the effects of traditional

constraints. One can choose from many different alternative mapping methods. However, it is not

just maps one can use. Other interactive graphics like diagrams and georeferenced imagery

should be considered, especially because of the large data set one has to deal with.

Many alternative mapping methods are familiar to frequent map users. When it comes to

traveling, most of us ase public transport maps. Their cask is to guide us from A to B，and since

one does not have to worry about driving, lots of (traffic) information can be omitted. This can

lead to interestingly alternative map designs. The best-known example is the map of the London

Underground originally created by Beck in the early 1930s. The concept of this map has been

copied by many other cities, although not always successfully. While designing the map, Beck

decided to schematize the route network,as the map image of the city center became too cluttered.

The traveler would, according to his opinion hindered by this approach since it was dark

underground anyway. The London Underground website has examples, and one can in website

allows one to interact with the network and request the real-time situation regarding delays, plan

a tour, and buy tickets.

Travelers to mountainous areas will be familiar with the panorama map. Most tourist areas can

no longer do without them. Often a summer and winter version of the map, each highlighting the

characteristics of the respective seasons, is available. The winter version highlights the

magnificent sky slopes while the summer version concentrates on the fine overall view.. These

maps are highly appreciated, and despite the fact that the images are geometrically distorted, they

give most visitors a better impression of the area than topographic maps would. Google Earth

can be considered an interesting alternative, since it allows one to combine different graphics

representations on top of the satellite imagery draped over the terrain. This might help in the

interpretation of the landscape.

5. Revealing Patterns: Understanding History

To illustrate the geovisualization approach, concentrating on representational aspects, Charles

Minard's well-known map of Napoleon's 1812 campaign into Russia (see Figure 1) will be

discussed. The map portrays the dramatic losses of Napoleon's army during his Russian

campaign. The authors purpose of both maps was to stress the senselessness of war. This section

illustrates the argument that if one is able to look at the data from different perspectives, for

instance via alternative map views, sometimes in combination with other graphics such as

diagrams, graphs, or even photographs and videos, one will better appreciate the nature of the

data at hand. The map is rather well known and has been mentioned by many researchers earlier.

It has been claimed that“it may well be the best statistical graphic ever drawn,” and “a narrative

graphic of time and space which illustrates how multivariate complexity can be subtly

integrated ... so gentle and unobtrusively that viewers are hardly aware that they are looking into

world of four or five dimensions."

The Minard map shows several 'variables'. As with any map, there is location. Next to the

major paths, some minor ones are depicted as well. Linked to the retreat path (the black solid

band) is a diagram indicating temperature .Additionally, the map shows the size of the army by

numbers and by the width of the advance and retreat bands. Names indicate major battles and

important geographic features. Time is inherent in the map (it shows a clear distinction between

the advance (going east) and retreat path (going west)), but absolute indications are given only in

the temperature diagram.

Traditionally, cartographers have three options to display geospatial data with a temporal

component. These are a single (static) map, in which specific graphic variables and symbols are

used to show change and represent events. Minard’s map is a good example of this category. The

second option is a series of (static) maps, sometimes called a small multiple (Figure 2a). The

single maps represent snapshots in time, and together the maps make up an event. Change is

perceived by the succession of the individual maps depicting the event in successive snapshots. It

could be said that the temporal sequence is represented by spatial sequence, which the user has to

follow, in order to perceive temporal variation. Finally, one can create an animated map. Here

change is perceived to happen in a single image by displaying several snapshots one after the

other. The difference with the animation from the static series of maps is that the variations

introduced to represent an event do not have to be deduced from a spatial sequence, but from real

movement on the map itself (Figure 2b).

Obviously, Minard’s map includes a temporal component; however, if one were to ask “what is

the situation on August 24th", the answer is not straightforward. Even if one could locate that

moment in time, all other campaign details remain visible and many cause confusion.

Alternatively, adding a slider to the map would introduce time more explicitly, and allow the user

to define the progress of the campaign. However, in this process there is no link between world

time and display time Also, moving the Slider with regular intervals would not result in a

regularpassing of time because Napoleon remained at certain places for a longer period. For

instance, in Moscow he paused for more than a

month - that is, information that cannot be derived

from the original static map. Some of the

animations have similar problems because (or a

small exist only for the moment in rime that the

change is registered. The use of a series of maps (or

a small multiple), each representing a particular

moment in time could be the alternative. In Figure

3, two alternatives are given, each showing a

different (traditional) cartographic solution. The maps depict the position of individual French troops on July

24 and August 24. The viewer is not distracted by previous or future moments in time.

Additionally, it provides (just as in the original map) an overview of die whole campaign. The

path of the campaign passed up to the particular date has been highlighted.

Interesting alternative visualizations have been produced by other researchers. They used

Minard's map to demonstrate the capabilities of a scientific and information visualization

software. Their products are examples of visualizations not influenced by traditional cartographic

rules. Figure 4 presents two snapshots of the visualization produced by the SAGE software. In

the snapshots the map is linked to diagrams, a principle Minard also followed in 1861.

The maps in both snapshots are oriented north, with the longitude indication along the

horizontal axis. In both diagrams the horizontal axis represents time. In the upper snapshot of the

diagram, the vertical axis represents longitude, and in the lower snapshot it represents the

number of troops. These combinations reveal some interesting facts when compared with the

original map in Figure 1. The diagram in the upper snapshot reveals two battles took place at

Pollock (located at the northern path in the map and circled in the diagram) instead of one. The

gap in the diagrams in both snapshots shows that Napoleon stayed for a month in Moscow before

returning west, information not found in the original map. These examples show that alternative

views can be revealing and clarifying.

What if another dimension is added? Figure 5 presents a 3D view in which the height of the

columns of the path segments represents the number of troops. The crossing of the River

Berezina is highlighted. Napoleon lost half of his remaining troops during this crossing. This

information is also found in the original map, but the 3D view presents this much more

dramatically. Other variables such as temperature can be represented in 3D view as well. The

columns can be colored depending on the temperature, applying color schemes with blue for cold

and red for warm. Links with diagrams such as shown in Figure 4 are also possible, including the

interaction options presented. The ability to manipulate the 3D scene in space to change the

perspective view is a prerequisite, since many interesting facts might be hidden behind objects. If

one would have looked at the River Berezina crossing from the north, it would have been hidden

by the troops-columns representing the advance. Additional layers with other information can be

stacked below or even above the campaign information.

Based on terrain heights, a fly-through can be generated demonstrating the impact of the

terrain on the campaign. In this particular case, it does not result in a spectacular view since the

landscape Napoleon passed by is relatively flat. Google Earth would be an apt program to use in

this case. Of course, one has to realize that landuse patterns would have changed considerably in

some places over the last 200 years. Figure 6 displays the path some of Napoleon's troops took,

projected on today’s satellite imagery.

Alternatively, software exists which allows one

to dress the landscape randomly and apply light

conditions, based on season and time of the day.

Even a snow cover can be simulated. One has to

realize the application of the rules of nature

results in a fictional world, even if real

topographic data has been used. Application can

be found in virtual reality environments. For ex-

ample, in a two-dimensional animation one can change the background of the landscape

depending on the temperature from blue in winter to green in summer. Figure 7 shows how the

background color of the map has been used to

indicate the temperature during the campaign.

The third dimension can be applied from a completely different perspective. Figure

8 presents a socalled space-time cube in which the x and y axes represent the

geography and the z axis represents time. Again, this solution would benefit greatly

from interactive options to manipulate the viewer's perspective of the cube. An

additional option could be slider planes along each of the cube's axes. The user can

move them through the cube and as such can highlight a time period or location. One

could, of course, also change the type of data represented along the axes and, for

instance, create temperature versus troops versus time.

6. Revealing Patterns: Predicting the Future

For the study of dynamic phenomena, such as the weather, and specifically cloud

developments, satellite images are the main source. These image repositories are be-

coming the fastest growing archives of spatiotemporal information and the users are

confronted with this flow of data that need to be explored. Here visual exploratory

tools are also useful. To predict storms and severe weather conditions, images are

searched to look for convective clouds. How are the dynamics of cloud development

displayed? An immediate response might be interactive animation. However, despite

being interactive, animations have some drawbacks and can easily lead to information

overload, limiting their exploratory usage. An additional alternative view that allows

the user to reduce the information load and focus attention, could enhance

understanding.

Next to the animation the visualizations of clouds can be presented in an abstract

way, based on quantitative data, enable essential attributes to be mapped, and have

dedicated interactivity. The visual exploration is improved by coupling computational

methods - here used to detect and track clouds - with abstract and selective

visualizations of the tracked information in a single environment (Figure 9). Tracking

reduces the complexity of time-series data sets: each cloud feature is described in

terms of its attributes (position, size, image intensity, etc.) and its lifetime. This offers

quantitative, abstract, and richer graphical representations of each cloud’s evolution.

In particular, the proposed multiple views in combination with the traced cloud paths

can show the essence of the object evolution and history. Abstract representations help

the user to search for objects of interest (clouds with negative temperature gradients

are most likely to be convective and selective interactivity assists the user in focusing

the attention on the particular clouds). With the presented functionality, the

lower-level visual task of detecting and tracking dynamic clouds is performed

computationally. Vision can now be completely devoted to a higher-level visual task.

So, the meteorological scientists can pay more attention to exploration of convective

clouds and generating hypotheses about their dynamics and evolution.

7. Challenges

The examples in the previous section demonstrate that visual support in any phase

of the geospatial data handling process can be realized and is helpful. However they

are mostly individual solutions.

For a better integration, mechanisms must be provided that can visualize the

connections between the Various stages of analysis and show how concepts relate to

data, how models relate to concepts, and so forth. Today, one cannot find a single

program to execute all the visualization operations discussed. Such functionality is

needed, but what is debatable is if we really require this in a single package. With

geodata infrastructure approach in the future and its distributed geoservices, it’s more

important that one has access to (visualization) functions and data to create the

representations required. An important precondition is, of course, interoperability，for

example, so that the smooth exchange of data and functions is possible. Currently,

these requirements are not yet fulfilled. Standardization initiatives from the Open

Geospatial Consortium and work executed following the principles of open source

software development will bring these requirements closer to realization. Reaching

this goal will facilitate collaboration in solving geoproblems. This approach has

become more common in academia； however, many interesting and advanced ex-

ploratory geovisualiz3tion tools are found in experimental lab environments. These

solutions are often open for others to access and apply, bur interested researchers as

well as other geoprofessionals might find they aren't always easily adopted. What are

the future concerns to be addressed?

7.1 Stabilization

It is needed to incorporate the new methods and techniques in

existing(cartographic) theories. This process is always far behind and problematic.

Those active at the frontier will make use of new trends and the gap between

established practices might widen, while technological progress is faster as ever.

Examples are efforts focused around portable and wearable PDAs and other com-

munication devices that draw upon real-time personal global positioning. Such

exciting developments are likely to continue to attract significant attention in the near

future. This location-based personalization re-emphasizes one of the original defining

themes of visualization as a form of map use the map devoted to particular needs and

designed based upon these requirements. Advances in communication technologies

mean that users of such maps can now be loosely connected through phone and

wireless networks providing universal access to customizable, map-based interfaces to

geospatiai information that may be location- and context-sensitive. It is interesting to

conjecture if geovisualizarion developments are motivated by known requirements

and the need for solutions, or developing possibilities and the desire to explore and

apply them. This can be considered a cause of concern between approaches that are

initiated by user needs and technological opportunities respectively and draws

attention to geovisualizacion research initiated by ‘demand' as opposed to supply.

7.2 Outreach

Next to an orientation toward 'technology-oriented disciplines' one has to strive to

apply the geovisualization knowledge in application fields. A useful example is

disaster management, where people might benefit from the tools during their activities

before, during, and after disaster management. In other words, geovisualization tools

must be used by people solving the large geoproblems. User expectations also rise,

and not only by ‘Google-Earth-type，of developments. This widespread adoption of

techniques initially used to further scientific advancement to meet the information

needs of a far wider range of map users, means that the design process must consider

and cater for a far more extensive and heterogeneous user group than the 'maps for

experts’， typical of early geovisualization efforts. It is interesting to note chat

geovisualization techniques are also applied by other disciplines to nongeographic

data. The resulting graphics are called spatialization. In these situations the map is

used as metaphor to get insight in the data.

7.3 Incorporation

The geodata infrastructure plays a more prominent role in offering data and

services. How about specific visualization services where the user could select

representation to execute a process as displayed in Figure 9? In addition, one can

witness real-time data collection and processing of large volumes of data via remote

sensing or sensor web- enabled collecting devices in the field. These can generate new

and fresh ideas about the role of the map. In this light the incorporation of new

technology in geovisualization remains important; incorporation of geovisualizarion

in the geodata infrastrucrure is important as well. With the trend of geovisualization

moving from the realm of experts well into the public domain, it has progressed from

a focus on the individual (user, tool, data set) to support collaborative and distributed

geovisualization which is facilitated by geoservices available via the geodata

infrastrucuture. With distributed geovisualization, the inputs can come from many

sources; geovisualization resources can be built from distributed components; and

multiple individuals can collaborate with and through the resulting geovisualization

tools. Geocollaboration faces some pragmatic problems. Collaboration could be in the

same place at the same time or at the same place at different times. However, it is also

possible to work at different places at the same time or at different places at different

times. This will put specific constraints on the software, and data and version man-

agement. Problems like which of the collaborators is charge, and how to deal with

access right to the data etc. might surface.

Figure 7 The temperature during the campaign: (a) a green map background indicating relatively

warm weather; (b) the map with a white background suggesting very low temperatures.

Figure 4 The campaign data in multiple linked views, (a) Linking the map with a longitude-time diagram, and (b)

linking the map with an attribute-time diagram. (Based on Roth S. F_, Chuah, M. C.. Kerpedjiev, S.,

Kolojejchick, J. A. and Lucas, P. (1997). Towards an information visualization workspace: Combining multiple

means of expression. Human-Computer Interaction Journal 12(1&2), 131-185.)

Figure 5 Three-dimensional view of the size of Napoleon's troops during his Russian

campaign in 1812.

Figure 6 Napoleon’s campaign mapped on Google Earth imagery.

Figure 7 The temperature during the campaign: (a) a green map background indicating relatively

warm weather; (b) the map with a white background suggesting very low temperatures.

7.4 Collaboration

This topic follows the current policy of the Commission on Visualization and

Virtual Enviromnents to import and export ideas from other disciplines. In the new

field of visual analytics, one is trying to improve insights inherent in large volumes of

data, which might sound familiar in geovisualization. The research agenda of this

field is stimulating analytical reasoning, the creation of new visual representations and

Figure 8 A space-time cube of Napoleon's march in Russia: (a) the path; (b)

the path and number of troops.

interaction techniques, as well as new data representations and transformations,

production, presentation, and dissemination techniques. As in information

visualization, the data at hand is nor necessarily geographic in nature, but methods

and techniques can be exchanged. Geovisualization, which see the maps as an

instrument of visual thinking, can contribute the geographical component in this field

of visual analytics.

8. Conclusions

The geovisualization approach offers a fresh look on geographic data, because it

allows maps and other geographics to operate in an interactive and dynamic

environment.

Maps retain their traditional roles such as presenting geographic facts, but they

should also be seen as flexible interfaces to geospatiai data； they do offer interaction

with the data behind the representation. This makes them instruments that encourage

exploration and are used to stimulate (visual) thinking about geospatial patterns,

relationships, and trends.

Further Reading

Andrienko, N. and Andrienko, G. (2006) Exploration analysis of spatial and temporal data -

A systematic approach: Springer Verlag.

Dykes,J., MacEachren, A. M. and Kraak, M J. (eds.) (2005). Exploring geovisualization.

Amsterdam :Elsevier.

Hearmshaw, H. M. and Unwin, D. J (eds) (1994). Visualization in geographical

information systems. London :John Wiley and Sons.

Kraak, M. J. (2003). Geovisualization illustrated. ISPRS. Journal of Photogrammetry and

Remote Sensing .

Kraak, M. J. and OrmelMig, F. J. (2003). Cartography, visualization of geospatial data,

MacEachren, A. M (1994). How maps work: Representation, visualization ,and design.

MacEachren, A. M. and Kraak, M. J.(2001).Research challenges in geovisualization..

Cartography and Geographic Information Systems 28(1), 3-12.

MacEachron, A. M. and raylor, D. R F. (eds.) (1994). Visualization in modem

cartography .London:

Peuquet, D. J. (2002) Representations of space and time.

Spence, R. (2001). Information visualization. ACM Press Books.

Tufte, E. R. (1997). Visual explanations.

Ware, C. (2004). Information visualization: Perception for design.