Data contribute to the Netherlands’ new spatial environment
The energy transition is a very complex issue in which local conditions & circumstances have a very important role to play. Location data can support authorities, both local and national, in planning the energy transition, by boosting the usage of existing infrastructure, providing insight into existing natural areas and bundling initiatives. That’s how data support a sustainable spatial environment in our country.
Our country is set to undergo a radical transformation over the next 20 to 30 years, due mainly to the energy transition. We will need a lot of space to harness the power of the wind and the sun and generate sufficient sustainable energy, and it is not without reason that Prime Minister Rutte compared the scope of the change at hand with the reconstruction of the Netherlands after the Second World War. The issue is very complex and is set to have a major impact on how we use our space, which requires smart planning. It is important that we pinpoint the areas that need energy first, as well as identifying which opportunities we have to generate that energy in a sustainable manner. Subsequently, we will have to draw up plans to bring the supply & demand sides as closely together as possible, taking into account local conditions and circumstances, such as the available infrastructure, as well as the wishes of the local people.
Local conditions are key
Wind farms and solar meadows play an important role in generating sustainable energy, and they require suitable locations to work properly. An effective solar meadow, for instance, requires approximately 10 hectares of land to start with. If such a plot of land can be found, the next step is making sure that the local plan allows for a solar meadow. The local electricity grid must also have sufficient capacity to process the solar energy generated by the meadow, and so on. The land, for example, must not be prone to flooding and it must be easily accessible by car to allow for maintenance.
Peter de Graaf
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Please feel free to contact us. Peter de Graaf is our expert in this field.
In order to make effective plans for the energy transition, we will need all sorts of data about local conditions and circumstances, and at Geodan, we know exactly which location data to source. We have analyzed large amounts of data from public spatial records, combining them with our own datasets. Now, we don’t just know the address and perimeter of any given building, but also its surface area, volume, roof type and number of floors. We have made all this information available on our GeodanMaps data platform, which lets us plot data on a map. This tool makes it easier to visualize and understand what data really mean, helping authorities, grid operators, energy suppliers and energy collectives to make well-informed decisions.
From data to policy
The municipalities of Apeldoorn, Deventer, Zutphen and Zwolle use a special viewer when making decisions about the energy transition, which consists of approximately 25 interlinked datasets. By combining information such as the year of construction, land use, and home types, decision-makers can come to a reliable estimate of energy consumption. Data derived from energy labels can then be used to highlight high-potential areas for sustainable development, where F ratings can be boosted to a B, for instance. On top of that, the locations of local heat sources, such as data centers or factories, can be used to design a better heat plan. All the available data can even be used to explore which energy source would be most suitable for a specific neighborhood, such as solar, wind, or geothermal energy. It is important, however, that such decisions be underpinned by specialist calculations, which is why it is wise to involve a party that focus specifically on that aspect of the energy transition.
Finally, the energy transition also has interfaces with other social developments. When making homes more sustainable, for instance, it can also be useful to make modifications that will let elderly citizens remain independent for longer, or to tackle social segregation. Again, data can play an important role in this process, by pinpointing areas with a large elderly population, or areas with high income inequality. These data allow for smart, integrated planning, contributing to the spatial environment of the future.
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Curious about the possibilities of location intelligence? We are happy to tell you all about it!