README.md

---
pretty_name: "GS-QA2 Source Data: OSM Vector Layers and ASTER DEM Raster"
license: other
license_name: odbl-and-aster-gdem
license_link: https://opendatacommons.org/licenses/odbl/
language:
- en
tags:
- geospatial
- gis
- openstreetmap
- digital-elevation-model
- aster-gdem
- raster
- vector
- postgis
- benchmark
viewer: false
---

# GS-QA2 Source Data

Reference geospatial data underlying **[GS-QA2](https://huggingface.co/datasets/Zoe/GS-QA2)**, a benchmark for question answering over raster–vector data. This repository contains the raw vector and raster inputs needed to rebuild the reference PostGIS database, execute the benchmark's ground-truth SQL queries, and run the baselines — use it together with the QA pairs in [Zoe/GS-QA2](https://huggingface.co/datasets/Zoe/GS-QA2) and the code in [github.com/ZhuochengShang/QARV](https://github.com/ZhuochengShang/QARV).

## Contents

| Path | Contents | Format |
|---|---|---|
| `osm/osm_extract/{lakes,parks,pois,postal_codes,roads}/` | Raw OSM extracts of the United States (~53 GB, 3,152 files) — the exact input to the benchmark's ingestion scripts | GeoJSON |
| `dem/tiles/*.tif` | 1,182 ASTER GDEM v3 1°×1° GeoTIFF tiles (1 arc-second ≈ 30 m, EPSG:4326) covering the contiguous United States (~18 GB) | GeoTIFF |
| `dem/tile_list.txt` | Listing of all DEM tile filenames | text |
| `dem/needed_dem_tiles.txt` | The tile set required by the benchmark (usable to re-download from NASA Earthdata instead of fetching `dem/tiles/`) | text |

## Rebuilding the reference database

The benchmark's ground-truth SQL expects PostGIS tables `pois`, `roads`, `parks`, `lakes`, `regions` and a raster table `public.dem_us`. Follow `GS-QA/ingestion/` in the [QARV repository](https://github.com/ZhuochengShang/QARV):

1. Set `DATA_ROOT` to the downloaded `osm/` directory (so the layers are at `$DATA_ROOT/osm_extract/{lakes,parks,pois,postal_codes,roads}`) and load the vector tables with `ingest_osm_postgis.sh` (which uses the `*_processor.py` loaders and schema files from `GS-QA/generator/`).
2. Set `DEM_ROOT` to the downloaded `dem/tiles/` directory and load with `ingest_dem_postgis.sh`. The script runs `raster2pgsql` with 256×256 tiling — the 1,182 source GeoTIFFs become the 265,950 in-database raster tiles reported in the paper — and builds a GiST spatial index.

All geometries and rasters use EPSG:4326 (WGS 84).

## Provenance

- The OSM extracts were produced with [osmx](https://bitbucket.org/bdlabucr/osmx/src/master/) from [Geofabrik](https://www.geofabrik.de/data/download.html) United States extracts, by the authors of the original [GS-QA benchmark](https://arxiv.org/abs/2605.22811) (also mirrored at [this Google Drive folder](https://drive.google.com/drive/folders/1pz895-lpGAaNJXz2mzjnB7SAgWwD0Uag?usp=share_link)).
- The DEM tiles are ASTER GDEM Version 3 (ASTGTM v003) granules obtained from [NASA Earthdata / LP DAAC](https://doi.org/10.5067/ASTER/ASTGTM.003); `dem/needed_dem_tiles.txt` identifies the granules so they can equally be re-downloaded from the source.

## Licensing and attribution

- **OSM-derived data (`osm/`):** © [OpenStreetMap](https://www.openstreetmap.org/copyright) contributors, licensed under the [Open Database License (ODbL) 1.0](https://opendatacommons.org/licenses/odbl/). Any derived database must comply with ODbL share-alike terms.
- **DEM tiles (`dem/`):** **ASTER GDEM is a product of METI and NASA.** ASTER GDEM v3 data are freely available and redistributable; retain this attribution. See the [ASTGTM v003 documentation](https://doi.org/10.5067/ASTER/ASTGTM.003).

## Citation

```bibtex
@inproceedings{shang2026gsqa2,
  title     = {GS-QA2: A Benchmark for Question Answering over Raster--Vector Data},
  author    = {Shang, Zhuocheng and Elmahallawy, Shahd and Al Nazi, Zabir and Hristidis, Vagelis and Eldawy, Ahmed},
  year      = {2026},
  note      = {Benchmark and code: https://github.com/ZhuochengShang/QARV}
}

@article{saeedan2026gsqa,
  title   = {GS-QA: A Benchmark for Geospatial Question Answering},
  author  = {Saeedan, Majid and Shihab Rashid, Muhammad and Eldawy, Ahmed and Hristidis, Vagelis},
  journal = {arXiv preprint arXiv:2605.22811},
  year    = {2026}
}
```

## Contact

Zhuocheng Shang — zshan011@ucr.edu — University of California, Riverside