Visualization of Water Services in Africa: Data Applications for Nexus Governance - Governing the Nexus: Water, Soil and Waste Resources Considering Global Change - page 194

it is important to identify the boundary conditions in terms of which data are needed,
which data are available and what we can do with it. This allows us to select
appropriate methods and highlight where new data needs to be assessed.
In data-poor environments, large amounts of data should be gathered from
proxies and transfer functions that rely on fast and cost-effective data assessment
methods, such as remote sensing. This data can be analysed and interpreted by
scientists and governmental bodies. Therefore, remote sensing image availability
should be supported by the government, external institutions or image suppliers.
Another option might be

near-surface geophysics such as spectroscopy and
EMI. The EMI instrument is light and carried above the earth surface, which gives
insights into the soil

' rapid '

s physical and chemical composition (e.g. used for farming).
However, data from remote sensing or geophysics require some kind of ground
truthing. Therefore, a sampling design is required that cost-effectively allows for the
extraction of required ground-based point information. The assessment of land-use
changes, for instance, requires an image classi

'

cation where each class represents a
different land use. Each land use possesses a speci creflectance that is used for the

classi cation. Expert knowledge or ground-based information is needed to allocate

each class to a speci

c land-use.
Since those instruments and many methods are relatively cheap, but may still be

dif cult to afford in developing countries, it might be advantageous to implement a

sharing system for instruments, laboratory facilities, expert knowledge and dat-
abases, which could be supported by capacity development. Sharing of knowledge,
tools and recommendations about standardized methods could be done via internet.
Direct face-to-face consultations will be important, however, and cannot be
replaced by online tools. The public should be included in all steps, since it is
another valuable source for data collection (e.g. mobile phone). In addition, deci-
sions from decision-makers might be more acceptable and understood if public
involvement is considered from the outset. Modelling as a means of process
understanding, managing and prediction should be supported by experts/organi-
zations through capacity development. Software tools that are applicable and easy
to use in data-poor environments should be provided together with adequate
documentation.

2.6 Making Use of Data: Data Integration and Visualization
for Decision-Making

Data that was assessed (see Sect. 2.3 ) need to be statistically prepared, investigated
as well as analyzed using some form of visualization technique. Visualization
makes data accessible and understandable to any stakeholder (e.g. researchers,
decision-maker or the public). The importance of data visualization for decision-
makers that allows for understanding of complex data and relationships from
diverse sources/disciplines is well known (Kwakkel et al. 2014 ).