Environmental Engineering Reference
In-Depth Information
value. Another example is the creation of a soil map that is based on measurements
with electromagnetics (EMI). Different homogeneous soil units are assigned to
several point soil samples and soil pro
le descriptions that then represent each of
the electromagnetic soil units. The degree of spatial resolution depends in this case
on the number of homogenous soil units and number of soil point samples. This
upscaling approach should additionally be supported by experts and further
knowledge of the investigation area.
Nowadays, paper maps are still in use due to their handiness, independence from
technology and comprehensibility. Today
s maps come as interactive, web-based
high-resolution tools such as Google Earth, GeoCommons (geocommons.org) or
OpenStreetMap (openstreetmap.org) whose content can freely be extended through
community input. These maps are based on remote sensing images in RGB (pho-
tography) visualization. Topographic or land cover type information is represented
by natural colour shadings (e.g. forest corresponds to dark green areas) as we know
from ordinary photography. However, natural colour shading is equivocal where, for
example a dark green area might correspond to forests or grasslands. These digital
interactive maps are only partly usable for decision-makers, unless earth surface
features are explicitly indicated and interpreted by cartographic symbols. The sym-
bols are applied to highlight speci
'
c earth surface features such as urban areas,
forests, water bodies or soil types using speci
c colour shadings, symbols, or text
features and corresponding map legend. The identification of cartographical features
is based on image classi
cation of land use or soil type) with
expert knowledge and supplementary information (e.g. paper maps, ground truthing).
In a fast changing world with complex global interactions and an increase in
environmental and social influential factors (e.g. development of chemicals, tech-
nologies, cross-bordering land and resource uses) it is challenging to understand
fully these developments and their interactions. Coping with those challenges
requires more sophisticated visualization tools. The visualization tools need to be
more flexible and extendible to make it possible to understand the interconnec-
tedness (nexus) of global change processes as well as their feedback mechanisms.
Kwakkel et al. (
2014
) give a good overview of selected software tools for geo-
spatial data and networks visualization. In the next sections, we will briefly present
various software tools that can partly be found in Kwakkel et al. (
2014
).
cations (e.g. classi
2D Visualization
Geoinformation systems (GIS) are used to collect systematically and visualize data
interactively from various sources linking them not only with a geographic refer-
ence system, but also with additional
information (e.g. soil
type, water type)
'
(O
Looney
2001
). In general, map information is coded by symbols and/or colours.
For example topographic maps generally colour flat areas in green and mountainous
areas in brownish shades, whereas line features might represent streets or rivers.
The digital character of the map allows overlying several user-de
ned adjustable
data layers, where the user can seamlessly zoom in and out. The quality and degree
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