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3.11 Geovisualization

M.J. Smith1, J.K. Hillier, J.-C. Otto, M. Geilhausen 
01 Jan 2013-pp 299-325

AbstractGeovisualization involves the depiction of spatial data in an attempt to facilitate the interpretation of observational and simulated datasets through which Earth's surface and solid Earth processes may be understood. Numerous techniques can be applied to imagery, digital elevation models, and other geographic information system data layers to explore for patterns and depict landscape characteristics. Given the rapid proliferation of remotely sensed data and high-resolution digital elevation models, the focus is on the visualization of satellite imagery and terrain morphology, where manual human interpretation plays a fundamental role in the study of geomorphic processes and the mapping of landforms. A treatment of some techniques is provided that can be used to enhance satellite imagery and the visualization of the topography to improve landform identification as part of geomorphological mapping. Visual interaction with spatial data is an important part of exploring and understanding geomorphological datasets, and a variety of methods exist ranging across simple overlay, panning and zooming, 2.5D, 3D, and temporal analyses. Specific visualization outputs are also covered that focus on static and interactive methods of dissemination. Geomorphological mapping legends and the cartographic principles for map design are discussed, followed by details of dynamic web-based mapping systems that allow for greater immersive use by end users and the effective dissemination of data.

Topics: Geovisualization (64%), Geographic information system (55%), Visualization (54%), Spatial analysis (50%)

Summary (7 min read)

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.
  • 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).
  • 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 prepared for viewing.
  • Finally, the scope of the chapter is stated.

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).
  • 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 can be stored, manipulated, analysed and communicated.
  • Such large datasets are most often generated by remote sensing of various kinds; Smith and Pain (2009) review currently available datasets.
  • In terms of impact upon geomorphology, the generation of digital elevation models (DEMs) (see XR: 3.9) has arguably had the largest effect.

2.2 Geomorphology and Geovisualisation

  • Geovisualisation is much utilized in geomorphology for the exploration and analysis of spatiotemproal 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).
  • The definition proposes that the term “visualisation” include four primary functions : 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.
  • 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 meaning of the term geovisualisation is therefore debated, but in its widest, intuitive, sense it is ‘the visual depiction of spatial data’.

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.
  • 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 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.
  • GoogleEarth performs similar tasks in an accessible way, encouraging map-making by the public at large.

3 Visual Processing

  • Geomorphologists are interested in the geovisualisation of spatial data in order to understand the Earth’s surface.
  • Automated and semi-automated mapping techniques use a variety of algorithmic approaches to identify landforms (e.g. Hillier & Watts, 2004; Van Asselen & Seijmonsbergen, 2006; Seijmonsbergen et al, 2011).
  • On land, passive airborne systems, such as aeromagnetics (detecting subsurface magnetic features), and active systems, such as airborne electromagnetics (3D conductivity), provide subsurface data (Smith and Pain, 2009).
  • The use of automated and semi-automated techniques that integrate a variety of datasets is therefore expected to become increasingly prominent.

3.1 Detection of Landforms

  • Manual mapping requires the visual detection of individual landforms, then recording their morphology on to some kind of basemap.
  • This is dependent upon the data source, image pre-processing and the skill of the interpreter.
  • Angle along the length of elongated landforms (e.g. drumlins), also known as 2. Azimuth Biasing.
  • The minimum resolvable planform size of detectable landforms can only be reduced by increasing the spatial resolution of data (imagery or DEM) being used (Smith et al, 2006).
  • Bias is minimised through the acquisition of imagery with a high illumination elevation (i.e. closer to overhead), however this minimises the landform signal strength so that features are not clearly observable .

3.2 Enhancement of Satellite Imagery

  • With the acquisition of appropriate satellite imagery, it is necessary to process or enhance the imagery to provide the best possible visualisation of landforms.
  • Enhancement is largely based upon a sub-set of the standard image processing techniques, namely those applied in remote sensing (e.g. Lillesand et al, 2008; Mather, 2004) that have proven useful for geomorphological visualisation.
  • Standardised contrast enhancements such as a linear stretch, histogram stretch or standard deviation stretch should be utilised in order to maximise the visible contrast within the image.
  • Inter-drumlin regions in his study contained greater moisture availability which impacted upon land cover, resulting in lower reflectance in VNIR bands, and thereby better differentiating drumlins.
  • Whilst DEMs record elevation rather than reflectance, using the terminology of imagery they may be thought of as a single ‘band’ and therefore any of the techniques described above can be applied to them.

3.3 Enhancement of DEMs

  • DEMs directly record elevation and therefore landscape shape can be inferred from them.
  • DEMs are treated differently from satellite imagery, although some aspects of processing are common.
  • By default most image-processing software display DEMs as a greyscale image with a palette of shades representing height that linearly varies between the maximum and minimum heights in the dataset; a simple ‘panchromatic’ display .
  • In such images small, low amplitude, features are not easily visible against larger-scale higher amplitude features typical in landscapes.
  • It is therefore necessary to focus on the component of the landscape containing features of interest, enhancing the ‘landform signal strength’.

3.3.1 Regional-Residual Separation

  • ‘Regional-Residual Separation’ (RRS) is the act of isolating landforms, ideally completely and uniquely, in to one component so that they may be studied independently.
  • The skill in performing a successful regional-residual separation is always determining a property that makes the features you wish to isolate distinctively different.
  • Widely ranging shapes and sizes within a class of feature (e.g. seamounts, drumlins).

3.3.2 Land Surface Parameters

  • In order to facilitate mapping, parameters derived from elevation as represented in a DEM are commonly calculated.
  • Figure 6 illustrates the problem with a DEM illuminated parallel and orthogonal to the principle landform orientation, and with an animation where the illumination azimuth is rotated through 360º at 5º intervals; for the latter, landforms both appear/disappear and change shape.
  • It is therefore common to utilise relief shaded images generated from multiple azimuths.
  • Roughness, the variability of elevation of a topographic surface at a given scale, has also been used extensively as an LSP for landform characterisation .
  • The parameter is sensitive to changes in local relief, where multi-scalar expressions of openness (i.e. distance) will have an impact.

3.4 Recommendations for Terrain Visualisation

  • A range of techniques designed to best enhance satellite imagery and DEMs for landform detection have been outlined in the previous sections.
  • Simple methods can be effective in highlighting individual landforms of interest, relegating all other aspects of terrain to “noise” (e.g. Hillier & Smith, 2008).
  • The technique of relief shading highlights subtle topographic features well, is widely implemented in software, fast to compute, and very useful when appropriate care is taken to allow for azimuthal bias.
  • This does not correct the problem, however, only making the interpreter aware of it.
  • Openness and roughness also offer illumination-free visualisation methodologies that may be appropriate for certain applications.

4 Visual Interaction

  • Visual Processing, as introduced in the previous section, presented a selection of techniques for the static visualisation of terrain.
  • That is, the outputs are fixed 2D entities, however it is often necessary to combine and interact dynamically with data in order to explore it more in more detail.
  • This section introduces common techniques to dynamically interact with spatial data and then explores increasingly sophisticated methods for interacting with geomorphological data as 2D planes and 2.5D surfaces, before outlining how surface data can complement true 3D volumetric data.

4.1 Display

  • Raster outputs of terrain are usually displayed and inspected upon a video display unit (VDU) using the red, green and blue (RGB) additive model of mixing colours .
  • Given the sensitivity of the human eye limits colour perception to RGB, the colour cube allows the mixing of the three primary colours at different intensities to provide the full gamut of possible viewable colours.
  • The technique is widely used in remote sensing and, within geovisualisation, allows the interactive inspection of multiple terrain datasets.
  • Figure 13 presents an example of how a false colour composite can be used to interpret geomorphology; this combines topographic openness (green; 501x501 m kernel) and slope angle (red; 3x3 m kernel).
  • A watershed (top left/light blue) is clearly depicted with drainage channels running away from it (red); below this are moraine ridges (centre left/light purple), gypsum sink holes (centre/red) beneath till and mass movement (centre/light red/yellow).

4.2 Digitisation and Overlay

  • The main output of visual processing is a raster dataset, or datasets, created using the techniques outlined above.
  • The process is generically known as “digitisation” and can form a body of work for the production of geomorphological maps (e.g. Hughes et al, 2010) or inputs for further quantitative processing (e.g. Smith and Rose, 2009).
  • Layers can be stacked (e.g. overlain) and reordered, allowing the interpreter to interact with different data layers and visually inspect their interaction.
  • The ability to manage large datasets and interact with them, allowing detailed inspection is an important, although simple, feature of a digital workflow.
  • Over larger areas lines and points can also be used to represent some area features.

4.3 2D to 21/2D In Space

  • A simple way to interact with data is through activities such as zooming, panning, rotating, and performing simple contrast enhancements.
  • Google Earth, for example, provides an elegant interface for the navigation of a single set of imagery for anywhere on Earth; this is a remarkable achievement.
  • Whilst somewhat restricted, these “global” measures can be used to explore features of individual datasets.
  • Animations provide a powerful methodology for data visualisation by depicting attribute change to vector or raster data.
  • For DEMs, timestages in a modelled landscape evolution could be similarly displayed.

4.4 3D in Space

  • It is natural to move from 2.5D to full 3D visual interaction with data, either in terms of estimating volumes, or being displayed in conjunction with true 3D volumetric data (e.g. seismic reflection data).
  • As noted above, DEMs do not provide volumetric data, however where it is possible to define a lower boundary through an understanding of a geomorphological basal surface (e.g. Sclater et al, 1975; White, 1993; Wessel, 1998; Hillier & Watts, 2004; Smith et al, 2009), volume can be estimated.
  • Airborne radiometric, magnetic and electromagnetic measurements of the sub-surface, for instance, could be integrated.
  • 3D visualisation packages integrating data such as outcrop sedimentary logs, strikeand-dip measurements, and horizon interpretations with photography draped over a LiDAR DEM have been developed for sub-aerial work (e.g. Fabuel Perez et al, 2010).
  • Through the use of polarised glasses, the human visual system assembles the display in to a 3D image.

4.5 Virtual Globes

  • Virtual globes, or Earth browsers, and online maps have become a central part of the internet since the first release of NASA’s World Wind (http://worldwind.arc.nasa.gov).
  • The geosciences community has embraced the use of virtual globes with emerging applications in many fields: from simple terrain inspection and feature mapping (Sato & Harp, 2009; Welsh & Davies, in press) to data visualisation and facilitated geo-data exchange (http://www.usgs.gov).
  • The National Snow and Ice Data Centre offers information about ICEsat data, NASA’s Ice, Cloud and Land Elevation satellite (http://nsidc.org/data/virtual_globes/glas/anchorage.kml).
  • This may involve graphical outputs for peer-reviewed research papers or direct public consumption.
  • This section summarises static and interactive visualisation products used in geomorphology and introduces some examples of web mapping and WebGIS.

5.1.1 Legend Systems

  • Traditional geomorphological maps differ from other thematic maps in that qualitative information prevails over quantitative or classified data.
  • Most geomorphological maps are compiled using descriptive symbols to represent landforms and processes.
  • Many different symbol sets and mapping systems have evolved during the 20th century in different countries with different thematic emphases and varying usage of symbols and colour .
  • Even though attempts were made to create a general legend for geomorphological maps by the International Geographical Union (IGU) in the 1960s (Demek et al., 1972), no universally applicable legend system has been established.
  • While the former style results in multi-coloured maps with several stacked layers of data that tend to be overloaded with information and may be hard to interpret (e.g. the German system; Barsch & Liedtke, 1980), the latter usually come in black and white and represent a reduction of information for practical purposes (e.g. the British system; Evans, 1990).

5.1.2 Map Design

  • Geomorphological maps are complex thematic maps that place demands on cartographic visualisation techniques in order to provide a comprehensible and readable map.
  • Rock glaciers for example could be represented by a single point symbol on small scale maps, or by the assemblage of line and area symbols that differentiate the step height of the rock glacier front, furrows and ridges and the accumulation of boulders and blocks on top of the rock glacier, if the map scale increases.
  • If colour is used, variation of colour characteristics, hue (colour variation), value and chroma , are the most powerful tools to emphasise certain aspects of the map.
  • In many geomorphological legend systems colours are applied to represent variations in landform genesis (Barsch & Liedtke, 1980), process domains (Gustavsson et al., 2006), or lithology (Pasuto et al., 1999).
  • In order to engage map-users and enable them to develop an understanding of the meaning of the map, a visual sense of the symbols and their attributes that correspond to the intention of the cartographer is required (Robinson et al., 1995).

5.2 Digital Mapping

  • Digital map creation is performed either using vector graphics software (e.g. Adobe Illustrator) or GIS software.
  • The results of GIS analyses are often compiled into maps and consequently GIS software includes mapping facilities and some graphic design capabilities.
  • Special symbol editors are provided to compose and define the symbol set for the map (e.g. in ArcGIS).
  • Generating geomorphological maps using a GIS enables numerous possibilities for the dissemination of research outputs extending beyond simple paper products.
  • These techniques are outlined in the following sections.

5.2.1 Open Standards

  • Data distribution and access in distributed web-based geospatial infrastructures need to be specified to achieve interoperability in a way that different applications (e.g. geodatabases, mapservers or clients) on various platforms (e.g. Linux, Microsoft Windows) can interact and communicate with each other.
  • The specific needs for interoperable geospatial technologies are implemented in specifications or standards describing the basic data models to represent different geographical features.
  • The standards or specifications are the main outcomes of the OGC and appear as technical documents that detail interfaces or encodings.
  • There are currently more than 30 standards defined, the most prominent of which are web services, also known as OpenGIS Web Services (OWS), specifically: i) Web Map Service (WMS) - providing map images, ii) Web Feature Service (WFS) - to retrieve feature descriptions and, iii) Web Coverage Service (WCS) - preparing coverage objects from a requested region.
  • XML is an acronym for Extensible Markup Language which is a set of rules for document encoding, comparable to HTML (Hypertext Markup language).

5.2.2 GeoPDF

  • A GeoPDF, an OGC standard, includes one or multiple map frames within a Portable Document Format (PDF) page associated with a coordinate reference system (Graves & Carl, 2009).
  • It enables the sharing of geospatially referenced maps and data in PDF documents.
  • Multiple, independent map frames with individual spatial reference systems are possible within a GeoPDF for example for map overlays or insets.
  • A GeoPDF enables fundamental GIS functionality outside specialised GIS documents, turning the formerly static PDF maps into interactive, portable, geo-referenced maps.
  • Some geospatial data providers, such as the United States Geological Survey (USGS) or the Australian Hydrographic Service (AHS), have already started publishing interactive maps using the GeoPDF format (http://store.usgs.gov).

5.2.3 Principles of Web mapping and WebGIS

  • Web mapping is a common way of presenting dynamic maps online.
  • The application employs MapServer generating the maps as WMS, the spatial database management system PostgreSQL (http://www.postgresql.org) maintaining the geometries and the web mapping client Mapbender (http://www.mapbender.org).
  • Due to MapServer’s powerful cartographic engine, complex geomorphological symbols can be implemented and displayed.
  • The WebGIS map thus uses the same symbols as the printed map of the same area (Otto & Dikau, 2004).
  • Thus, WebGIS applications are powerful tools to disseminate geospatial information to users from different organisations (e.g. local authorities, environmental agencies).

6 Conclusions

  • Geovisualisation has garnered considerable interest as a term covering a wide swathe of activities ranging from exploration, through to analysis, synthesis and presentation.
  • An intuitive, useful definition is 'the visual depiction of spatial data', and this chapter has focused upon the use of geovisualisation in geomorphology under this definition.
  • Automated and semi-automated techniques also deliver landform parameters, but are beyond the scope of this chapter.
  • This can then be used for the generation of output that is appropriate for the intended end-user, be that a printed map or web-mapping system.
  • Dynamic visualisation techniques, and particularly areas such as temporal and 3D analysis will gradually improve, along with products designed to engage end users such as augmented reality.

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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

2
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

3
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

4
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

Citations
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01 Jan 2016
Abstract: MASSIVE! The year that was, is now slowly coming to an end and with it completion of a big step forward for the Journal of Maps (JoM). It is hard to believe that we enter our third year in partners...

11 citations


Journal ArticleDOI
Abstract: Many communities depend on Lake St. Clair for drinking water and recreational uses. In addition, it is an important transport route for natural resources and manufactured products. The St. Clair River, which flows into the lake from the northeast, is a major source of sediment. The upstream area is known as “chemical valley” due to a large amount of industrial activity located along the river. Sediment sampling surveys were conducted in 1970, 1974, and 2001 by Environment Canada as part of a continuing monitoring program. Two approaches to the representation, analysis, and visualization of lead contamination were used: a two-dimensional Geographic Information System-based approach using kriging and a three-dimensional approach that utilized the interpolated kriging surfaces overlaid on bathymetry data. The results of combining this analytical method with a three-dimensional representation appear to show that Lake St. Clair generally has lower levels of sediment contamination away from the main flow and circulation patterns leading to its Detroit River outlet. Lead levels declined below the threshold effect level in 2001 compared with the higher concentrations seen in 1970 and 1974. In addition, lake-wide spatial distributions are better visualized using the kriging spatial interpolation results when they are overlaid on the bathymetry data. L'emploi d'outils de geovisualisation pour evaluer la contamination par le plomb des sediments dans le lac Sainte-Claire De nombreuses communautes utilisent les eaux du lac Sainte-Claire a des fins d'approvisionnement (eau potable) et recreatives. De meme, il sert d'axe principal pour le transport des ressources naturelles et des produits transformes. La riviere Sainte-Claire, qui se jette dans le lac depuis le nord-est, deverse d'importantes quantites de sediments. La zone situee en amont abonde de produits chimiques en raison des nombreuses activites industrielles en operation de part et d'autre de la riviere. Des echantillons de sediments ont ete preleves par Environnement Canada en 1970, 1974 et 2001 dans le cadre d'un programme de surveillance continue. Deux demarches ont ete mises en œuvre en vue de representer, analyser et visualiser la contamination par le plomb : une premiere s'appuie sur un systeme d'information geographique a deux dimensions utilisant une modelisation par krigeage, et une seconde a trois dimensions utilisant les surfaces d'interpolation obtenue par krigeage superposees aux donnees bathymetriques. Cette methode d'analyse conjuguee avec une representation en trois dimensions permet d'observer une diminution generale du degre de contamination sedimentaire du lac Sainte-Claire en retrait du courant du chenal principal menant a la decharge de la riviere Detroit. En 2001, les concentrations de plomb ont baisse au-dessous du niveau de l'effet de seuil par rapport aux valeurs plus elevees observees en 1970 et 1974. En outre, une meilleure visualisation des repartitions spatiales du plan d'eau est obtenue grâce aux resultats tires de l'interpolation spatiale par krigeage lorsque ceux-ci sont superposes aux donnees bathymetriques.

7 citations


Cites background from "3.11 Geovisualization"

  • ...Geovisualization and mapping of bathymetry is an evolving field (Smith et al. 2013; Alves et al. 2014; Resch et al. 2014)....

    [...]

  • ...…in the literature include Alves et al. (2014) who found that bathymetric features have a profound effect on oil spillmovement in theAegean Sea; Smith et al. (2013) who highlight the use of visual processing, visual interaction, and visual outputs, all of which form part of the…...

    [...]

  • ...Recent examples of the use of geovisualization and/or bathymetry in the literature include Alves et al. (2014) who found that bathymetric features have a profound effect on oil spillmovement in theAegean Sea; Smith et al. (2013) who highlight the use of visual processing, visual interaction, and visual outputs, all of which form part of the geovisualization of terrain; and Resch et al. (2014) who examined the display of bathymetry as a three-dimensional (3D) time series for geovisualization purposes....

    [...]


Journal ArticleDOI
Abstract: MASSIVE! The year that was, is now slowly coming to an end and with it completion of a big step forward for the Journal of Maps (JoM). It is hard to believe that we enter our third year in partners...

6 citations


Journal ArticleDOI
Abstract: Inadequate quantitative methods (QM) training provision for undergraduate social science students in the United Kingdom is a well-known problem. This paper reports on the design, implementation and assessment of an induction module created to test the hypothesis that visualization helps students learn key statistical concepts. The induction module is a twelve-week compulsory unit taught to first year social science students at a UK university, which they complete prior to a more traditional statistical, workshop-based QM module. A component of the induction module focuses on the use of visualization through Geographic Information Systems (GIS), to teach the process of hypothesis generation to students while they also are introduced to the basics of QM research design and univariate and bivariate forms of data analysis. Self-reflexive evaluation indicates that visualization could assist students with more advanced QM statistical skills.

4 citations


Cites methods from "3.11 Geovisualization"

  • ...…to support this approach through the use of aspects of the process of visualization that include the ‘exploration’ of data (MacEachren et al. 2004, Smith et al. 2013); the aims of this being to (i) support students throughout their course, (ii) introduce the key statistical concept of…...

    [...]

  • ...These aspects of visualization have been described in a framework consisting of four functions; from ‘exploration’ and ‘analysis’ of data to the ‘synthesis’ and ‘presentation’ of information (MacEachren et al. 2004, Smith et al. 2013)....

    [...]

  • ...However, the authors of this paper chose to integrate visualization through using mapping technology (MacEachren et al. 2004, Smith et al. 2013), because mapping technology is seen as being increasingly important for employers and social science research in a range of areas, such as poverty,…...

    [...]


Journal ArticleDOI
Abstract: Elsevier’s Modern Cartography Series, edited by Professor DR Fraser Taylor, is a long-running occasional series that currently comprises seven volumes, the first published in 1991. With a hiatus since 2006, Elsevier has injected some new vigour with a title planned for 2017 and this volume, Reflexive Cartography, published in 2015. The book is firmly rooted in cartographic theory and is largely drafted in the style of a monograph. It is not a science-led book, but rather a philosophical approach to understanding the historical development of the subject, its current status and, more particularly, how it can develop in the future. It is worth stating early on that the manuscript was originally written in Italian, utilises extensive Italian academic literature and has been translated into English. The translation is generally good, but stylistically is extremely dense using a technical, verbose, approach and, in the tradition of monographs, overly long! I cannot help but feel that the core message and supporting argument could have been achieved in fewer than 100 pages. The following gives readers a sense of the difficulty in understanding the language (for those not familiar with this style):

1 citations


Cites background from "3.11 Geovisualization"

  • ...When representing landscape more generally, then the subject reduces to one of communication or more specifically geovisualisation (Smith et al., 2013)....

    [...]


References
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TL;DR: GMT allows users to manipulate (x,y,z) data, and generate PostScript illustrations, including simple x-y diagrams, contour maps, color images, and artificially illuminated, perspective, and/or shaded-relief plots using a variety of map projections.
Abstract: Version 31 of the Generic Mapping Tools (GMT) has been released More than 6000 scientists worldwide are currently using this free, public domain collection of UNIX tools that contains programs serving a variety of research functions GMT allows users to manipulate (x,y) and (x,y,z) data, and generate PostScript illustrations, including simple x-y diagrams, contour maps, color images, and artificially illuminated, perspective, and/or shaded-relief plots using a variety of map projections (see Wessel and Smith [1991] and Wessel and Smith [1995], for details) GMT has been installed under UNIX on most types of workstations and both IBM-compatible and Macintosh personal computers

6,358 citations


Journal ArticleDOI
Abstract: Three different least-squares methods for processing time-series of satellite sensor data are presented. The first method uses local polynomial functions and can be classified as an adaptive Savitzky-Golay filter. The other two methods are more clear cut least-squares methods, where data are fit to a basis of harmonic functions and asymmetric Gaussian functions, respectively. The methods incorporate qualitative information on cloud contamination from ancillary datasets. The resulting smooth curves are used for extracting seasonal parameters related to the growing seasons. The methods are implemented in a computer program, TIMESAT, and applied to NASA/NOAA Pathfinder AVHRR Land Normalized Difference Vegetation Index data over Africa, giving spatially coherent images of seasonal parameters such as beginnings and ends of growing seasons, seasonally integrated NDVI and seasonal amplitudes. Based on general principles, the TIMESAT program can be used also for other types of satellite-derived time-series data.

1,455 citations


Journal ArticleDOI
Abstract: Although the Normalized Difference Vegetation Index (NDVI) time-series data, derived from NOAA/AVHRR, SPOT/VEGETATION, TERRA or AQUA/MODIS, has been successfully used in research regarding global environmental change, residual noise in the NDVI time-series data, even after applying strict pre-processing, impedes further analysis and risks generating erroneous results. Based on the assumptions that NDVI time-series follow annual cycles of growth and decline of vegetation, and that clouds or poor atmospheric conditions usually depress NDVI values, we have developed in the present study a simple but robust method based on the Savitzky–Golay filter to smooth out noise in NDVI time-series, specifically that caused primarily by cloud contamination and atmospheric variability. Our method was developed to make data approach the upper NDVI envelope and to reflect the changes in NDVI patterns via an iteration process. From the results obtained by applying the newly developed method to a 10-day MVC SPOT VGT-S product, we provide optimized parameters for the new method and compare this technique with the BISE algorithm and Fourier-based fitting method. Our results indicate that the new method is more effective in obtaining high-quality NDVI time-series.

1,373 citations


Journal ArticleDOI
TL;DR: In general, filters that estimate local surfaces are found to perform best and should be directed towards the usage of additional data sources, segment-based classification, and self-diagnosis of filter algorithms.
Abstract: Over the past years, several filters have been developed to extract bare-Earth points from point clouds. ISPRS Working Group III/3 conducted a test to determine the performance of these filters and the influence of point density thereon, and to identify directions for future research. Twelve selected datasets have been processed by eight participants. In this paper, the test results are presented. The paper describes the characteristics of the provided datasets and the used filter approaches. The filter performance is analysed both qualitatively and quantitatively. All filters perform well in smooth rural landscapes, but all produce errors in complex urban areas and rough terrain with vegetation. In general, filters that estimate local surfaces are found to perform best. The influence of point density could not well be determined in this experiment. Future research should be directed towards the usage of additional data sources, segment-based classification, and self-diagnosis of filter algorithms.

889 citations


Journal ArticleDOI
Abstract: Mathematical proof establishes identity of hypsometric integral and elevation-relief ratio, two quantitative topographic descriptors developed independently of one another for entirely different purposes. Operationally, values of both measures are in excellent agreement for arbitrarily bounded topographic samples, as well as for low-order fluvial watersheds. By using a point-sampling technique rather than planimetry, elevation-relief ratio (defined as mean elevation minus minimum elevation divided by relief) is calculated manually in about a third of the time required for the hypsometric integral.

488 citations


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Q1. What are the contributions in this paper?

Geovisualisation has garnered considerable interest as a term covering a wide swathe of activities ranging from exploration, through to analysis, synthesis and presentation this paper.