Construction & infrastructure

This dataset contains important data for each building in the Netherlands, including building height and ground level height, building type, number of stories, and usable floor area. You can use this dataset for analyses in which building height or building type are important factors, such as in the search for locations for transmitter masts, for instance. Looking to install pressure booster systems or solar panels? Link the objects to addresses and conduct market analyses. Can also be used as input for 3D models This data set is available in various formats. You can choose between information about the Netherlands, a particular province, or a given municipality.

Quickly and easily find critical locations and black spots in the kilometers of cables and pipes under the root zones of trees? The Tree registry will let you do just that. Based on the combination of tree crown circumference, tree height and road paving, you can easily track down dangerous points. In case of a Klic report, we also pass on the location of tree roots that are near cables or pipes to diggers.

Not all construction vehicles can reach every small street or pass through any viaduct. We have carefully mapped the infrastructure for all vehicles to always show your drivers the best and fastest way.

If your target audience is hard to fit into fixed borders, you can make use of this dataset with different administrative layouts, such as municipalities, zip code areas, districts, or Bundesländer. Naturally, the sets contain accompanying statistical characteristics.

Do you want to find out more about the local characteristics of the area in which you’re going to develop new homes? Our Spatial Queries service lets you request specific household characteristics from a selected area. You can easily filter the data based on location, route or a selected area, and with the export function, you can easily process the information in reports or a spreadsheet application later.

In our distance matrix, you’ll find all travel times and distances to and from all zip codes in the Netherlands. The standard version is available for cars at the zip code 4 and zip code 5 level, but custom tables are also possible for other modes of transportation or other countries, for instance. Ideal for use in HRM systems to determine travel expenses, or to determine travel times and distances between different areas in the logistics sector.

Do you always want the most up-to-date version of the zip code map? At all levels: from 2 to 6-position zip codes? Geodan’s zip code maps let you do just that. You can use these in Geographic Information Systems (GIS), BI systems, or in your own (web) application to make geographic analyses a lot simpler. From displaying your customer turnover by zip code area and visualizing your service area to mapping out districts. You can choose from a basic version or more complete variants, custom-made for your organization.

Our routing networks form the basis for the most realistic and efficient route calculation. Looking for a route from A to B or one passing several locations? We send your co-workers and/or suppliers on the most optimal route, along with reliable travel times. To make your planning even more accurate, combine these services with our Building Properties dataset.

Looking for more information about the demographic characteristics of a certain area or neighborhood? Simply link your own zip-code-level data to neighborhoods and districts known to Statistics Netherlands. We’ll get you all the characteristics that are available at that level and provide all data in a single, handy overview.

Geodan offers a standard map library with data for GeodanMaps customers, including administrative layouts, such as zip code and municipal boundaries, as well as all addresses and buildings, building types, energy data, and demographic data at the zip-code level. Aside from that, it’s easy to add your own data for a handy, complete overview.

GeodanMaps lets you code your own geodata using an Excel file. From zip codes and addresses to coordinates, neighborhoods, and areas; they are all converted into separate map layers, allowing you to visualize your own data on a map and gain new insights. This information is also easy to share with others.