As more data on our environment becomes openly available, new ways to use it in design and decision-making emerge. A-Konsultit, a Finnish architectural design firm, and Sipoo, a municipality, set out to use geospatial data in a novel way.
“We got a commission from Sipoo to devise a method for determining development rights in rural areas. The work was part of their district planning process. We already had ideas about how to use geospatial data for locational evaluation, but, now, we had a chance to test it out in practice,” Matti Heikkinen, architect at A-Konsultit, tells.
Developing Rural Areas
Favorably
Planning
what and how much to build in sparsely populated areas follows a convention
that does not take into account socio-environmental factors. If no town plan
exists, Finnish municipalities use a simple formula that outputs the allowed
development rights as a percentage of the real estate area. Its purpose is to
treat land owners fairly.
The problem
with a mechanical calculation is that it fails to develop areas that are most
favorable for a new building – for example, a large estate far away from main
roads, schools, or public utilities can enjoy generous air rights, whereas a
smaller, more favorably located area gets next to nothing.
A-Konsultit
set out to create an assessment system that would take into account various
environmental factors and determine development rights accordingly. The method
they were developing works for any type of location-based evaluation both in
urban environments and sparsely populated areas. They got funding from the
Finnish government’s KIRA-digi project that aims at digitalizing built
environment processes.
Open Geospatial Data as a
Basis
There’s
already a lot of open geospatial data available in a digital format. However,
using it as a basis for environmental analyses is not always easy because of
incompatible data models.
A-Konsultit
was able to collect and combine GIS data on Sipoo properties, infrastructure,
topography, soil, and so on. Fortunately, the data followed national standards,
which made the process straightforward.
As an EU
country, Finland is committed to the Union’s INSPIRE directive. It defines
common, EU-wide standards for 34 spatial data themes. Once fully implemented,
designers and software developers can make use of the huge repositories of
geospatial data across Europe.
Creating an Assessment
Framework
A-Konsultit
had to come up with evaluation criteria to determine the value of various
environmental elements in respect to a location – for example, distance from a bus
route or a sewer. To do that, they created a grid that covered the whole
district. Each rectangular cell of the grid got a certain number of points based
on the criteria. The result looks like a heat map with colors referring to the
point count.
“In
practice, we created several maps, laid them on top of each other, and
calculated the sum of the plusses and minuses of each rectangle. The higher the
score, the better a location is as a building site,” Heikkinen explains. “We
used QGIS for maps and Excel spreadsheets for the calculations.”
Heikkinen
admits that as mathematical, open, and objective as the process looks like, it
has subjective aspects. A team that sets the criteria has a great influence on
the outcome. For land owners, the air rights correlate with the value of the
property. On the other hand, having high development rights in an unfavorable
location does not add much value.
According
to Heikkinen, the Sipoo project is unique because that the geospatial
evaluation leads directly to legally binding decisions. So far, he has not
discovered similar solutions elsewhere. The city of Stockholm has used an
analogous method in district planning, but at a strategic level.
Automating the Design
Process
The
principle demonstrated in Sipoo applies to all kinds of environmental
evaluation scenarios. Depending on the purpose of the analysis, the evaluation
can be augmented with various calculation algorithms and scripts. Apart from
established GIS sources, the data could be collected from mobile devices and
other real-time sources.
Heikkinen envisions
advanced applications of the technology. An algorithmic design app could use
geospatial data to generate optimized 3D city models. The app could analyze the
results from various points of view – for example, windiness or noise. If the
user is not be satisfied, they can restart the process by adjusting certain
parameters to get different results. It’s easy to imagine that machine learning
would also come into play at some point in the process.
“In an
environment that is becoming more complex every day, politicians and designers
should take a huge number of variables into account,” says Heikkinen. “For
humans, that’s becoming impossible. Machines can manage the flow of information
and help in reaching a balanced design solution.”
If you want
to learn more about the experiment, contact Matti Heikkinen at
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