license: cc-by-nc-4.0
pretty_name: KoSim-GL
tags:
- uav
- geo-localization
- cross-view-retrieval
- simulation
KoSim-GL
KoSim-GL is a benchmark for matching simulated UAV views to satellite imagery in urban areas of Daejeon, Republic of Korea. The UAV images were generated with an AirSim and ROS flight simulator. The satellite imagery was collected through the Google Maps Tile API. See the project repository and paper for the collection method and benchmark protocol.
Dataset contents
| Split | Locations | UAV images | Satellite images |
|---|---|---|---|
| Train | 255 | 2,188,425 | 1,530 |
| Test | 29 | 261,890 | 174 |
| Train + test | 284 | 2,450,315 | 1,704 |
The archive also contains a subset_eval directory with 162 query UAV images
and 162 gallery satellite images. These 324 additional image entries are not
included in the train and test totals above. The archive also contains six
text metadata files and one Python counting script.
The full dataset is a 394,614,137,420-byte ZIP, distributed as ten consecutive binary parts. It contains the train and test splits in a University-1652-compatible layout. UAV views cover six altitude levels from 100 to 600 m and five camera views (one nadir and four oblique).
Download and reconstruction
Download all ten files named 20261013_multi_sinsungdong_data_v2.zip.part01
through 20261013_multi_sinsungdong_data_v2.zip.part10 from
Files and versions
into one directory. Each part is 39,461,413,742 bytes. Use only the v2
parts and keep their names unchanged. Run this Python code from that directory
to restore the original ZIP:
from pathlib import Path
import hashlib
base = "20261013_multi_sinsungdong_data_v2.zip"
digest = hashlib.sha256()
with Path("multi_sinsungdong_data.zip").open("xb") as output:
for number in range(1, 11):
with Path(f"{base}.part{number:02d}").open("rb") as source:
while block := source.read(16 * 1024 * 1024):
output.write(block)
digest.update(block)
assert digest.hexdigest() == "c6a51312f03f001210cb58e675d050514bfbe596890ff6f66f1f128194d85840"
The SHA-256 above is for the original unsplit ZIP. Individual part checksums are in the machine-readable manifest. Reconstruction needs approximately 395 GB of free space in addition to the downloaded parts.
Intended use
Research and evaluation of cross-view image retrieval and UAV geo-localization. The project repository lists the dataset license as Creative Commons Attribution-NonCommercial 4.0.
Citation
Ahn, H., Lee, C., Lee, S., Wi, H., Jang, I., and Choi, D.-G. "KoSim-GL: A Large-Scale Simulation-Based Dataset for UAV Cross-View Geo-Localization in Korean Urban Environments." Electronics 15(12), 2720 (2026). https://doi.org/10.3390/electronics15122720
Contact
For dataset questions, open an issue in the project repository.