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1
Geovisualisation
Mike J Smith
1
, John Hillier
2
, Jan-Christoph Otto
3
and Martin Geilhausen
3
1
School of Geography, Geology and the Environment, Kingston University, Penrhyn Road, Kingston upon Thames, Surrey, KT1 2EE,
UK. Tel: +442070992817, Fax: +44870 063 3061, michael.smith@kingston.ac.uk.
2
Department of Geography, Loughborough University, Loughborough, Leicestershire, LE11 3TU, UK. Tel: +441509 223727
J.Hillier@lboro.ac.uk.
3
Department of Geography and Geology, University of Salzburg, Hellbrunnerstr. 34 A - 5020 Salzburg, Austria. Tel: +43 66280445291
Jan-Christoph.Otto@sbg.ac.at, Martin.Geilhausen@sbg.ac.at.
Keywords (10-15 alphabetically sorted): cartography, DEM, filter, globe, kernel, legend, map,
symbol, terrain, visualisation
Synopsis (50-100 words)
Geovisualisation, the depiction of spatial data, is key to facilitating the generation of observational
datasets through which Earth surface and solid Earth processes may be understood. This chapter
focuses upon the visualisation of terrain morphology using satellite imagery and DEMs, where
manual interpretation remains prevalent in the study of geomorphic processes. Techniques to
enhance satellite images and DEMs in order to improve landform identification as part of the
manual mapping process are presented. Visual interaction with spatial data is an important part of
exploring and understanding geomorphological datasets and a variety of methods ranging from
simple overlay, panning and zooming are discussed, along with 2.5D, 3D and temporal analyses.
Visualisation outputs are outlined in the final section, which focuses on static and interactive
methods of dissemination. Geomorphological mapping legends and the cartographic principles for
map design are introduced, followed by details of dynamic webmap systems that allow a greater
immersive use by end users, as well as the dissemination of data.
1 Introduction
Geoscientists aim to develop an understanding of the processes that create landforms, and in
order to study landforms must be able to visually perceive them. So accurate, detailed and reliable
visualisation is arguably of primary importance to the geomorphological study of processes
shaping the Earth and other planetary landscapes. In geomorphology, the shape of the land is
fundamental so, whilst other complementary data exist, elevation data are central to
geovisualisation. Geovisualisation relates to topics covered in other chapters in this volume
particularly remote sensing (XR: 3.1), digital terrain modelling (XR: 3.9), geomorphometry (XR:
3.10) and spatial analysis/geocomputation (XR: 3.14). Extensive and complex image processing
techniques are applied in these areas, but many of these do not relate to visual display, which is
the focus of this chapter. For simplicity, although geovisualisation is used more widely, terrain is
used to illustrate geovisualisation.
The scope of this chapter includes focusing upon visual processing, visual interaction and visual
outputs, all of which form part of the visual “depiction” of terrain. Much of this focus is related to
geomorphological mapping, often a formal outcome of geovisualisation. Section 2 provides
background context in terms of a historical perspective, formal definitions of geovisualisation, and
an outline of emergent technologies and applications. Section 3 explicitly deals with Visual
Processing and the optimisation of imagery for landform visualisation. Section 4 introduces the
mechanics of various methods by which a user can interact with data once they have been
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prepared for viewing. Finally, Section 5 discusses the dissemination of data in both traditional
paper and electronic formats, highlighting various visualisation products. Terminology concerning
geomorphology and elevation data are explained within the text and also collected together in a
glossary. More detailed definitions are provided by Pike et al (2008).
This introduction starts by placing geovisualisation into its historical context, then focuses on
visualisation for geomorphology where recent work is driven by the availability of digital datasets.
The relationship of geomorphology to geovisualisation through geospatial analysis is then
discussed and the term geovisualisation defined, leading onto an outline description of the uses of
geovisualisation and a framework within which they can be categorised. Finally, the scope of the
chapter is stated.
2 Background
2.1 Historical Context
The visual interpretation of data and conceptual ideas has been a key aspect of human
understanding (e.g. Kraak and Ormeling, 2010). For spatial data, those where location is of
importance, maps have been commonly created to assist in interpretation. Figure 1a illustrates the
utility of creating maps for the investigation of geomorphic processes by displaying the distribution
of glacial landforms and their composition (indicated by the symbol fill colour), something that is
difficult to convey using vertical (Figure 1b) or oblique (Figure 1c) aerial photos. Alongside maps,
alternative portrayals of spatial data have been routinely used (e.g. Kraak and Ormeling, 2010;
Bonham-Carter, 1994): these include field sketches (Figure 2) and conceptual diagrams (Figure 3),
vertical/oblique aerial photos (Figure 1b/c), satellite imagery, digital elevation models and
augmented reality (e.g. Reitmayr et al, 2005).
Early geomorphological maps were often produced for military and engineering purposes and
designed for use in the field (Klimaszewski, 1982). With the onset of a morphological view of
landscapes and the description of their physiography at the turn of the 20
th
century, landform
analysis and morphological description became new purposes for geomorphological maps (e.g.
Passarge, 1912; Passarge, 1914). From this standpoint maps were more than just a medium for
visualisation but represented a research tool for landscape analysis providing a generalised
inventory of landforms, surface structures, geomorphological processes, surface and subsurface
materials, and genetic information. The applications of geomorphological maps range from simple
descriptions of a field site, for example accompanying a journal publication or construction site
report, to land system analyses (Bennett et al., 2010), land surveys, land management or natural
hazard assessment (Brunsden et al., 1975, Seijmonsbergen & de Graaff, 2006)
Maps remained the fundamental geomorphological output through to the 1980s as they provided
both 2D visualisation and an effective data storage paradigm for spatial data. Geomorphological
mapping subsequently declined due to a preoccupation with cartographic symbolisation and a
move to field scale experimentation. Since the 1990s widely available remotely sensed data,
progress in computing power, and the improvement of information systems (e.g. Wessel & Smith,
1998; ESRI, 2003) have permitted the combination of field scale and regional approaches, causing
a resurgence in mapping. In particular the emergence of the GIS (Geographic Information System)
through the wider field of geomatics has provided a digital tool through which disparate datasets
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can be stored, manipulated, analysed and communicated. This provides a powerful methodology
to combine diverse data such as total stations, GPS, satellite imagery, postcodes and historic
sources. Specifically, GIS can be used to prevent data overload, facilitating the clear, carefully
constructed presentation required for interpretation, analysis and higher-level use of the data
Historically geovisualisation has been a paper-based analogue technique, however it is now the
routine collection and widespread availability of large digital datasets that is driving much analytical
work facilitated by computer-based geovisualisation. Such large datasets are most often generated
by remote sensing of various kinds; Smith and Pain (2009) review currently available datasets. In
terms of data volume, satellite imagery remains the single most important product, although the
balance between spectral resolution, spatial resolution, and temporal resolution can be
problematic. However, in terms of impact upon geomorphology, the generation of digital elevation
models (DEMs) (see XR: 3.9) has arguably had the largest effect. This is profound because a
variety of elevation data can be synthesised into a DEM and, once in raster format, image
processing methodologies, common in geovisualisation, can be applied. Contemporary mapping is
therefore computer based, reliant upon the input of digital datasets, with analysis and output
performed using GIS.
2.2 Geomorphology and Geovisualisation
Geovisualisation is much utilized in geomorphology for the exploration and analysis of spatio-
temproal data. Whilst a spatial framework is not a requirement for geomorphological study (e.g.
Smith and McClung, 1997), it is natural in many studies to use “space” as the organising paradigm
(e.g. Benetti et al, 2010). A better understanding of many geomorphic phenomena can therefore be
gained through the recording (i.e. ‘mapping’) and analysis of their spatial distribution. In the past
the observed distribution and form (i.e. morphology) would typically have been communicated
using a geomorphological map (e.g. Rose and Smith, 2008).
The term “geovisualisation” is a contraction of geographic visualisation. This was first mooted by
MacEachren et al (2004), who defined geovisualisation as a “process for leveraging … data
resources to meet scientific and societal needs and a research field that develops visual methods
and tools to support a wide array of geospatial data applications.” This definition extends
geovisualisation beyond simply communication using the presentation of an image or images. The
definition proposes that the term “visualisation” include four primary functions (Figure 4): i)
‘exploration’ of datasets e.g. in order to find landforms ii) ‘analysis’ e.g. of patterns and
relationships between the landforms iii) ‘synthesis’ e.g. generating an overview and understanding
of the origin of the landforms and iv) ‘presentation’ of the findings. Within this definition,
geovisualisation incorporates a wide gamut of activities and capabilities. In contrast, Kraak (2008)
suggested that “geovisualisation” was seeing inflation as a term: namely, that geovisualisation was
being used increasingly widely and indiscriminately, becoming equated with “mapping”, and
therefore increasingly less useful as a term. So, he favours the use of the term “geovisual
analytics” (Thomas & Cook, 2005; Andrienko et al 2007) for the range of activities in and around
the geovisualisation cube, implicitly retaining a more focused definition of “geovisualisation”.
Discussion exists about the terminology surrounding geographic visualisation, yet, at its simplest,
geovisualisation is simply a synthesis of the long-developed visual communication of cartography
with current digital analytical technologies, principally GIS. Indeed, it could be argued that in the
past cartography was geovisualisation; that is, cartography embodied the sum of geovisual
techniques that were possible before practical, pervasive desktop computing. The introduction of
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computer technologies in the 1960s, however, saw a split in the discipline of geographic
visualisation with users either focused principally upon i) design and communication or ii) data
handling. The former we now think of as cartography, whilst the latter became geographic
information science. The meaning of the term geovisualisation is therefore debated, but in its
widest, intuitive, sense it is ‘the visual depiction of spatial data’. It is a convenient term to employ
within geomorphology, and is used here with this latter broad meaning.
2.3 Applications and Emergent Technologies
Some applications of geovisualisation are depicted in Figure 4, with the axes of the cube
illustrating the task being performed, the user doing the task, and the degree of interaction with the
data being visualised. Within this, MacEachren et al’s (2004) four functions (Section 2.2) move
sequentially from highly interactive exploration of the data by specialists in order to generate basic
observational knowledge, to presenting synthesised information to the public involving little
interaction with the data. “Knowledge construction” at the start of this sequence requires a
specialist user with a high degree of interaction and can be considered a research-intensive
application. At the opposite end of the spectrum, “information sharing” generally requires lower
levels of interaction by non-specialists and is an application for the public and decision makers.
This latter area is now an important aspect of research as funding bodies are aware of their
accountability and therefore desire further downstream application, as well as interaction with the
general public or, more generally, “public relations”.
Two trends not well represented by the four functions proposed within the geovisualisation cube
are the growth in both public interaction with data and data distribution to the widest possible
audience. The latter facilitates the former, and with both specialists and the public exploring data,
the face of the cube representing high levels of interaction is becoming increasingly occupied.
Specifically, there are 3 requirements for this occupation to be achieved:
• freely or easily available data
• non-proprietary or ‘open’ formats for geospatial data
• free or easily available software or simple tools to download, visualise and analyse data
The public release of data is not new (e.g. SYNBAPS: VanWykhouse, 1973), but there has been
an increasing political pressure to do so. In the USA the National Geophysical Data Center
(http://www.ngdc.noaa.gov/) makes data publically available and it is a requirement of funding that
data be released. The UK government has released significant quantities of data
(http://data.gov.uk), and UK research councils also require scientists to place their data in
repositories. Data sharing and archival requires a move away from proprietary data formats and
this has been achieved through the development of industry standard, open, formats (e.g. KML)
and openly specified proprietary formats (e.g. the shapefile format; ESRI, 2003).
The ability to select base data and easily overlay specialist datasets is fundamental across a
spectrum of activities, ranging from the development to the use of applications. For example,
Generic Mapping Tools (Wessel & Smith, 1998), GRASS and QGIS allow scripting to enable
advanced users to create wider dynamic access to data. The Seamount Catalog
(http://earthref.org/SBN/; Koppers et al, 2010) exemplifies a scripted front end to geospatial data.
For both technical and non-specialist users, GeoMapApp (http://www.geomapapp.org/; Carbotte et
al, 2004) is a free, easy to use software package that contains datasets, displays (e.g. maps and
profiles) and overlays data and allows users to import new data. GoogleEarth performs similar