Environmental Engineering Reference
In-Depth Information
2 General Work
ow from Data to Modern
(State-of-the-Art) Visualization
fl
This section describes the general workflow that transforms data to visualization
(Fig. 1 ). While examples mainly draw on water-related problems and variables, the
focus is on basic principles, applicable to any visualization of environmental data.
Basis of any visualization is the availability of data, which should be collected
according to a de
ned sampling design. Data can be ground based (traditional
sampling) or quasi-continuous based on various technologies. Data sampling design
and data collection approaches (traditional and quasi-continuous) presented here are
applicable to data-rich (Sect. 2.1.1 ) as well as to data-poor (Sect. 2.1.2 ) environments.
2.1 Data Availability
On a global view, regions can be grouped according to the availability of data into
data-rich and data-poor environments. The data availability of a certain region is
related to the
country
'
s history,
climatic
conditions, geographic
location
and development stage, which includes infrastructure,
financial as well as socio-
economic background. As a measure for general data availability might serve the
Research Question / Concern / Area of application interest
e.g. Drought risk analysis, erosion vulnerability
Defines
Sampling Strategy (where and what to sample)
Available Data
(maps, historical
information, data
bases, ...)
Evaluation
Is the visualization
appropriate to answer the
target question?
Data collection
Point
Field
Regional - (Global)
Local
samples
(soil, water,
chemicals)
Upscaling of local
measurements (near-
surface geophysics, models,
remote sensing)
Upscaling (regional
to global models,
remote sensing)
INPUT
OUTPUT
INPUT
Visualization
Georeferenced
Maps with point
information
2D, 3D maps, time-series of
environmental changes,
simulation models
2D, 3D maps, time-series of
environmental changes,
simulation models
(paper format, digital format, web-based, interactive tools, VGE)
Interactive Interface & Scenarios
(e.g. decision malers, public)
Monitoring
(repeated measurement and/or analysis of target area preferable applying existing models (e.g.
software models, remote sensing, Pedo-Transfer-Models, Proxies)
Fig. 1 General workflow from the research question via data up to visualization
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