GlobalBuildingMap (GBM): the highest accuracy and highest resolution global building map ever created. GBM is derived from nearly 800,000 PlanetScope satellite images, and is distributed in the form of a binary raster (building and non-building) at a resolution of 3 meters.
Visual comparison of building footprints from different data sources in Cairo, Egypt. The three building footprint layers from GBM (purple), Google (cyan) and OSM (yellow) are overlaid with high-resolution aerial image. Two selected areas, i.e., dense area/informal settlement (orange) and non-dense area (green) are zoomed in. Each area has three subfigures, which show the corresponding high-resolution aerial image as reference (left), GBM overlaid with satellite image (mid) and Google overlaid with satellite image (right). Background images © Google Maps.
While the PlanetScope imagery required to reproduce this effort is not publicly available due to licensing restrictions, a list of all 790,101 images used in this work can be found in the assets/downloaded_items.txt file. A GeoJSON file containing the bounding boxes of all processed images can also be found in assets/merged_roi.geojson. Note that Planet data requires a license to download.
The predicted building masks are available on mediaTUM at https://doi.org/10.14459/2024MP1764505.002 under a CC-BY-4.0 license. The easiest way to download the dataset is with rsync:
export RSYNC_PASSWORD=m1764505.002
rsync -av rsync://m1764505.002@dataserv.ub.tum.de/m1764505.002/ .
All Python libraries needed to use this code can be installed using:
pip install -r requirements.txt
Please define data directory, checkpoint directory and log directory before running following command:
python planet_training_demo.py
Please define satellite image directory, prediction directory and prediction files' name before running following command:
python planet_proc_inferDemo.py
Global predictions for all continents can be downloaded from: https://doi.org/10.14459/2024MP1764505.002.