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Global Building Atlas

📖5 min read

Introduction​

The Global Building Atlas is a comprehensive 3D dataset containing over 2.75 billion buildings. Developed by the Technical University of Munich (TUM), it provides coverage for areas often missing from standard digital maps, including rural regions and parts of the Global South.

Unlike standard OpenStreetMap data, this dataset includes estimated heights (Level of Detail 1 or LoD1) derived from satellite imagery and machine learning. This guide covers how to stream this massive dataset directly into QGIS using a Web Feature Service (WFS).

Global Coverage

Access 2.75 billion building footprints worldwide.

3D Ready

Includes height data for immediate 3D extrusion.

WFS Stream

Stream data directly without downloading massive files.

Reliability & Limitations​

It is excellent for coverage (quantity) but mediocre for precision (quality). Good for reference. If you need accurate heights, it is not reliable.

Reliability Breakdown​

1. Coverage: High Reliability

  • The Good: The dataset covers "areas historically missing," such as rural Africa and South America. This is its biggest strength. It likely has buildings that Google Maps or OpenStreetMap completely miss.
  • The Bad: Because it is auto-generated from satellite images, it may hallucinate buildings.

2. Height Data: Low Reliability

  • The Red Flag: The dataset uses "Monocular height estimation".
  • What this means: The AI is guessing the height of a building based on a single flat photo (looking at shadows, etc.). It is not using accurate laser scanning (LiDAR).
  • The Result: Expect heights to be "guesstimates." A 10 meter high building might be listed as 8 or 12 meters. The error margin in these datasets is typically ±3 to 9 meters (approx. 1–3 floors).

3. Shape Accuracy: "Square"

  • **LoD1 (Level of Detail 1): As stated, these are "extruded blocks." They do not have slanted roofs, domes, spires or other details
  • **Polygonization: The algorithms (fuse_bf) often smooth out complex shapes. A jagged, complex apartment complex might appear as a simple rectangle.

Step 1: Set Up the Connection​

To access the data, you need to connect QGIS to the TUM server.

  1. Open QGIS.
  2. Navigate to Layer > Add Layer > Add WFS/OGC API - Features Layer...
  3. Click New under the Server Connections section.
  4. Enter the connection details:
    • Name: Global Building Atlas
    • URL: https://tubvsig-so2sat-vm1.srv.mwn.de/geoserver/ows?
  5. Click OK.

Step 2: Locate and Add Data​

Handle with Care

This dataset covers the entire world. Attempting to load the full dataset at once may freeze QGIS. You should filter by your current view.

  1. In the Data Source Manager, ensure Global Building Atlas is selected.
  2. Click Connect.
  3. Locate the layer named global3D:lod1_global.
  4. Prepare your view: Close the manager temporarily and zoom the map canvas to your specific area of interest (e.g., a specific neighborhood).
  5. Re-open the WFS window (Layer > Add Layer > Add WFS...).
  6. Select global3D:lod1_global.
  7. Important: Check the box "Only request features overlapping the view extent". This limits the download to what you currently see.
  8. Click Add.

Step 3: Verify Coordinate System​

The native data is often in EPSG:3857 (Web Mercator). QGIS usually handles reprojection automatically, but it is useful to verify.

  • Check the bottom right corner of the QGIS window.
  • Ensure your Project CRS is set to EPSG:3857 or a local UTM zone for accurate visualization.

Step 4: Visualize in 3D (LoD1)​

"LoD1" means buildings are simple extruded blocks. You can visualize this directly in QGIS.

  1. Check Attributes: Right-click the layer and open the Attribute Table. Look for the height field (often height, elevation, or h_est).
  2. Open 3D View: Go to View > 3D Map Views > New 3D Map View.
  3. Style the Layer:
    • Right-click the layer > Properties > 3D View.
    • Set "No Symbol" to Single Symbol.
    • Altitude Clamping: Set to "Absolute" (or "Terrain" if you have a DEM).
    • Extrusion: Click the data override icon (ε) next to Extrusion.
    • Select Field type and choose the height field found earlier.
    • Click OK.

Step 5: Export Data​

To use this data in Blender, you can export it as a Shapefile.

  1. Right-click the global3D:lod1_global layer.
  2. Select Export > Save Features As...
  3. Format: Select ESRI Shapefile.
  4. CRS: IMPORTANT: https://easycalculator.org/utm-zone-map, Find the UTM zone for the location, then in QGIS click the globe next to CRS > Search under Universal Transverse Mercator and find the correct UTM zone, there is a preview in the window
  5. Save the file.

Step 6: Import into Blender​

To bring this data into Blender, we rely on the BlenderGIS add-on.

  1. Open Blender.
  2. Navigate to GIS > Import.
  3. Choose Shapefile (.shp).
  4. Elevation Source: important setting: set to none (When we don't want to import the height location of the building, meaning at what level of altitude the building is place, not the actual height of the building). In the import dialog, find the Extrusion from field option. Select the height attribute (e.g., height or h_est). This tells Blender to automatically extrude the flat footprints into 3D volumes.
  5. Separate Objects: Check or Uncheck this to either keep the buildings as a single mesh (improves performance) or to seperate them.
  6. Click OK.

The buildings will appear in your scene, extruded to the height as interpreted by the Global Building Atlas.

Summary​

The Global Building Atlas is a powerful resource for filling in the map where OpenStreetMap data might be sparse. By connecting via WFS and carefully filtering for your area of interest, you can access high-quality building footprints and height data for almost any location on Earth.

Key Takeaways:

  • Use WFS to stream the data; avoid downloading the full dataset.
  • Verify that "Only request features overlapping the view extent" is checked.
  • Use the height attribute to generate 3D block models.

Documentation for Methodology​

How to cite this dataset

Citation​

When using this data in an investigation, you should cite the original research:

Zhu, X. X., Chen, S., Zhang, F., Shi, Y., & Wang, Y. (2025). GlobalBuildingAtlas: An Open Global and Complete Dataset of Building Polygons, Heights and LoD1 3D Models. Technical University of Munich. https://doi.org/10.14459/2025mp1782307

Methodology Example​

"Building footprints and height data were obtained from the Global Building Atlas (Zhu et al., 2025) via WFS connection in QGIS. Data was filtered to the investigation area and exported as GeoJSON for 3D reconstruction."

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Last updated on by blender-visual-investigation