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--- |
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license: other |
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language: |
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- en |
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tags: |
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- GeoFM |
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- PlacePulse |
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- SpatialRepresentationLearning |
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- OpenStreetMap |
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- StreetView |
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- Multimodal |
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- Geospatial |
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pretty_name: Place Pulse 2.0 Multimodal |
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size_categories: |
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- 100K<n<1M |
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--- |
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# PP2-M: Place Pulse 2.0 - Multimodal |
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**PP2-M** (Place Pulse 2.0 - Multimodal) is a dataset based on the original Place Pulse 2.0 dataset [1], enriched with additional geospatial modalities for training **multimodal Geo-Foundation Models (GeoFM)**. |
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The dataset includes aligned pairs of the following modalities: |
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- 🌍 **Geographical coordinates** (lat, lon) from Place Pulse 2.0 [1] |
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- 🏙 **Street view images** from Place Pulse 2.0 [1] |
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- 🛰 **Remote sensing images** from Sentinel-2 [2] |
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- 🗺 **Cartographic basemaps** from OpenStreetMap [3] |
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- 📍 **Points of interest (POIs)** from OpenStreetMap [3] |
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--- |
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## 📜 License |
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Due to its multimodality, PP2-M comes with **different licenses per modality**, as described in the folder [`LICENSES`](./LICENSES). |
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--- |
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## 📑 Modalities Description |
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### 📌 Coordinates |
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- **110,988 locations**, each with associated geographic coordinates. |
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### 🏙 Street View Images (SVI) |
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- Obtained from **Google Street View. |
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- Resolution: **400 × 300 pixels**. |
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### 🛰 Remote Sensing Images (Sentinel-2) |
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- Sentinel-2 **Level-2A** images. |
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- Acquisition period: **Jan 1 – Dec 31, 2024**. |
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- Filtered for minimal cloud coverage. |
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- Each patch includes spectral bands: |
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`B01, B02, B03, B04, B05, B06, B07, B08, B08A, B09, B11, B12` |
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- Resolution: **256 × 256 pixels**. |
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### 🗺 Cartographic Basemaps (OSM_basemaps) |
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- Tiles from **OpenStreetMap tile server**. |
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- Zoom levels: **15, 16, 17** → resolutions of **1200 m, 600 m, 300 m**. |
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- Downloaded: **May 2025**. |
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- Rendered at **256 × 256 pixels**. |
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### 📍 Points of Interest (OSM_pois) |
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- Extracted from **OpenStreetMap**. |
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- For each location: up to **15 nearest POIs within 200 m**. |
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- Adaptive search radius ensures coverage in sparse areas. |
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- Retained POIs with tags: |
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`amenity, shop, leisure, tourism, healthcare, theatre, cinema, building=religious, building=transportation, public_transport=station` |
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- **Excluded**: `parking, parking_space, bench, bicycle_parking, motorcycle_parking, post_box, toilets` |
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- Each POI is assigned a **representative category** (priority order: `amenity → leisure → religion → public_transport → shop → tourism`). |
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- Special cases: |
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- `healthcare` if substring matches |
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- `museum` if name contains "museum" |
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- Final POIs are used to construct **textual prompts** describing each POI’s name, category, and distance. |
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--- |
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## 📂 Folder Structure |
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PP2-M/ <br> |
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│<br> |
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├── LICENSES/ → Licenses for all modalities<br> |
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├── Tables_statistics/ → Statistics & tables (based on Place Pulse 2.0)<br> |
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├── SVI/ → Street View Images<br> |
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├── sentinel2/ → Sentinel-2 images<br> |
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├── OSM_basemaps/ → OSM basemaps (zoom 15, 16, 17)<br> |
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├── OSM_pois/ → Raw POIs + generated text prompts<br> |
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└── Precomputed_features/ → Pre-extracted modality-specific features<br> |
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## 🔀 Dataset Splits |
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- **training** – samples used for training. |
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- **validation_in_region** – interpolation evaluation. |
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- **validation_out_region** – extrapolation evaluation (unseen cities). |
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--- |
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## 📊 Precomputed Features |
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In addition to raw data, we provide **pre-extracted features** from each modality using modality-specific models. |
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See details in our paper: [UrbanFusion](https://github.com/DominikM198/UrbanFusion/). |
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--- |
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## 📖 Citation |
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If you use PP2-M, please cite our work: |
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```bibtex |
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@article{muehlematter2025urbanfusion, |
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title = {UrbanFusion: Stochastic Multimodal Fusion for Contrastive Learning of Robust Spatial Representations}, |
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author = {Dominik J. Mühlematter and Lin Che and Ye Hong and Martin Raubal and Nina Wiedemann}, |
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year = {2025}, |
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journal = {arXiv preprint arXiv:2510.13774} |
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} |
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``` |
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--- |
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## 📊 References |
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[1] Dubey, A., Naik, N., Parikh, D., Raskar, R., and Hidalgo, C. A. (2016). Deep learning the city: Quantifying urban perception at a global scale. In ECCV, pp. 196–212.<br> |
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[2] Drusch, M., Del Bello, U., Carlier, S., Colin, O., Fernandez, V., Gascon, F., ... Bargellini, P. (2012). Sentinel-2: ESA’s optical high-resolution mission for GMES operational services. Remote Sensing of Environment, 120:25–36.<br> |
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[3] OpenStreetMap contributors (2017). Planet dump retrieved from https://planet.osm.org<br> |
