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"Digital city models are much better known than digital rural models. While buildings and infrastructure are likely to be modeled within cities, land and associated land operations and environmental parameters are more likely candidates for modeling the digital pathways stretching across rural and remote areas.  They are not two disconnected parts though. They interface each other and are complimentary to each other. In fact, the effectiveness of each requires an understanding and appreciation of both to enable regional, national and international planning."

PerspectivesWebHeader
 

Digital city models are much better known than digital rural models.
While buildings and infrastructure are likely to be modeled within
cities, land and associated land operations and environmental
parameters are more likely candidates for modeling the digital pathways
stretching across rural and remote areas.  They are not two
disconnected parts though. They interface each other and are
complimentary to each other. In fact, the effectiveness of each
requires an understanding and appreciation of both to enable regional,
national and international planning.

The city and the country
Cities are distinctly different than rural areas. These differences are
the basis for modeling each of them differently. For rural and remote
areas, it is the land and water areas that are of greatest interest,
along with the operations connected to them – given small towns and
villages could effectively employ digital city modeling tools.

The idea behind a digital rural model is to develop a model that
realistically represents land management practices – operations
together with water body phenomena. This includes land division and
ownership, physical inventory and description, land operations
including agriculture and forestry as well as climatic and atmospheric
factors.

Sensors and monitoring
While city models may involve sensor technologies and monitoring, rural
digital models would be highly oriented toward sensor use and land
areas would be continuously monitored through a number of different
technologies including remote sensing, laser, GPS and GIS. At more
localised scales we might even consider that variable rate farming
(precision farming) are part of a wider digital rural model. In fact,
the practice of variable rate farming may operate through the
aggregation of numerous participants and indpendent producers, often
using similar data for smaller regions.

Similarly, forestry operations could also be viewed in the wider
context of digital rural models. Why? Consider hydrology for small
rural towns, avalanche hazards, flooding and disease related issues.
Each of these can transcend local operations and are dependent upon
those operations. The monitoring of climate variables also falls within
the context of a digital rural model since land based operations can
result, for example, in enhanced vulnerability to flooding and so on.

Environmental monitoring of rural operations is growing. Legislation
is increasing in the area of monitoring animal operations and the
applications of chemicals to land. These operations are required to be
documented.  In the case of mining and other land change operations,
attention must be paid to water bodies and nearby streams. In these
cases the monitoring of water bodies is continuously provided through
networks of sensors.

Rural – urban energy
Recent interest in solar, wind, geothermal and other renewable energy
production, together with already existing oil & gas, mining and
other operations is resulting in the development of regional energy
plans. These proposals, such as the one introduced for the city of
Berlin, Germany, consider the energy produced from lands around the
city and its management within the context of the city – utilisation.

For such applications the weaving together of city and rural digital
models makes effective sense because it ties regional climate,
operations and land use into a wider energy framework.  It is hoped
that increased management of overall resources within a holistic manner
will be possible through the combined integration of digital modeling.

Rural energy systems, including those which include biofuels and the
management of waste for the production of energy are likely to grow.
These applications are more than likely to be located in rural areas,
but their produced energy is likely to be transferred to cities.

Spatial data infrastucture development (SDI)
The development of SDI have traditionally sought to integrate spatial
information from regions of different scale into one combined seamless
system. However, this has not usually been articulated as the combining
of two (or more) different modeling efforts. Instead, it has often been
expressed with the idea that one expanding system can effectively
represent all operations within a whole district or bioregion, for
example. But is it accurate to consider cities and rural areas in the
same way?  Or, is it more appropriate to consider them as distinct
areas in need of distinct modeling and design efforts? Interoperability
ought to be able to integrate such distinction.

Geospatial software and hardware
Technologies like GIS, CAD, remote sensing and GPS have major roles to
play in both urban and rural modeling. A higher need to integrate
spatial data will be necessary. But these are not the only technologies
that need to be considered in the integration of rural and city model
integration. The aggregation of sensors into networks, monitoring of
biological processes in rural energy systems, transport and
distribution from rural energy networks,  are all poised to become much
more in demand.

A unique feature of these technologies is their ability to perform
continuously and through the seasons. Many of the applications will not
only be oriented toward indoor applications, but will capture and
process spatial data in harsh environments with environmental extremes.

The common denominator to digital city and digital rural models is
the fact that they are spatial – in time and space – but while one is
highly 3D, building and infrastructure functional, the other is more
land and water based, sensor oriented and monitoring in nature.
Combined their effectiveness is dependent upon high levels of digital
interoperability.

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Note: This column alternates weekly between Vector1 Media editors.
Jeff Thurston is editor Europe, MIddle East, Africa and Russia V1 Magazine and V1 Energy magazine.

Additional Reading:

3D Rural Community Nutritional Models.
Where Does a Digital City Model Get Implemented?
“Will digital city models become one über model or separate models for specific domains?
Digital City Announced – agit 2008 / Geoinformatics Forum Salzburg
3D City Model Berlin Wants to Live and Breathe
The Classification of 3D City Models.
“How will technology evolve so that city models become the new base map?”
What is the role of the digital terrain model (DTM) today?  

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