Deutschland is kind of a big deal when it comes to big data, but that doesn’t mean that it’s easy to work with. Until now.

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39 million buildings, and counting.

State of the nation

In Germany, the accumulation and monitoring of geodata is the duty of the sixteen federal states. The states maintain all the sources and have an agreement among each other about available formats and data interoperability. Sounds great, right?

Sadly, this doesn’t necessarily mean it’s a piece of cake to import all this geodata at once. As usual, the devil is in the detail.

Looking at the data, we could see straight away that each federal state feels distinctly unique and individual — and that’s not a good thing. It’s a similar story in some big corporations: One hand doesn’t know what the other is doing. …


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Big news for Down Under: Microsoft’s Open Data department have just released a new dataset for Australia. Machine learning algorithms were used to detect 11 Million building footprints in the country.

Before diving right in and adding the data to our database, we ran our usual stringent QA checks to make sure that the data passes muster. Without giving too much away, we used various geometry checks for the task, including self-intersection testing, and checking to see whether any polygon rings are touching one another.

Then we ran manual visualization checks on the new source. This is necessary because we’ve found strange artefacts in Microsoft building data in the past, and we want to make sure we only have good stuff in our database. With this clean and comprehensive Antipodean dataset, we’re well on the way to our goal of 600 million buildings at your fingertips. …


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Last time, we brought you Estonia. Today we’re happy to announce the fruits of our latest labours: The Grand Duchy of Luxembourg. Also known as: Luxembourg.

Here’s where we made a difference:

  • Total building count for the country has increased to 292k.
  • More than 33% of buildings now have height information (up from 1.2%).
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before (OSM) — after (3db)

To experiment with the 3dbuildings map, head to the website and use the search field to find the area that you need for your project.

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At 3dbuildings we’re always working to bring you the global datasets necessary for your project. Today we’re rolling out expanded coverage for (drum roll): Estonia.

The stats that matter:

  • Total building count for the country has increased to 920,000.
  • Type attribute is now available for 86% of buildings.
  • More than 20% of buildings now have height information (up from 1.5%).

To experiment with the 3dbuildings map, head to the website and use the search field to find the area that you need for your project.

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Collecting data from open sources, cleaning, fixing and mixing it is easy. You just need to practice for 10,000 hours.

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Sao Paulo (OSM Buildings)

Our biggest source of building data is OpenStreetMap. OSM has a number of unique selling points:

  • Strong global coverage
  • Highest number of common attributes per building
  • Good accuracy due to ground truth mapping, or mapping from high-res imagery
  • Updated every minute

OSM’s 400 million buildings (as of July 2020) create a strong base for the subsequent processing work that we do.

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Fixing AI geometry (Tanzania, Microsoft)

Our next biggest source of data is Microsoft US Buildings (2018). It’s our first source that involves AI. As is typical for this technology, false positives and invalid polygons are prevalent. …


We found something intriguing on Twitter the other day…

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TL;DR — You won’t.

This was a a neat Twitter find promising the holy grail, the elixir of eternal life (in 3d mapping communities anyway): a smart building created in under 20 minutes.

Let’s just think about what you’ll need to to make this happen. You’re going to need a proper internet connection to make this work with cloud-based computing platforms. You’ll then need a security setup that has the required firewall settings or even a VPN setup.

Next you’ll need a digital floor plan, or even better a BIM (Building Information Modeling) model. …


When it comes to level of detail, there are no wrong answers — only different use cases.

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LOD–TU Delft

Level of detail (LOD) defines the amount that we abstract real world objects, from raw footprints up to sophisticated 3d models. To help you understand which LOD might be appropriate when you come to download data for your project, here’s our short primer on understanding the essentials.

Level of Detail: 0

This is a building footprint. No height attached, no building parts visible. The vast majority of buildings in OpenStreetMap and open data city models are just that: flat polygons.

These work best for plain maps or 2d analysis. …

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3DBuildings

Clean and comprehensive worldwide building data.

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