satellite
wmo-oscar-satellites
WMO OSCAR Satellite Database
Part of the Orbital Mechanics Datasets collection on Hugging Face.
The most comprehensive international database of Earth observation satellites and instruments, maintained by the World Meteorological Organization (WMO) through their
OSCAR/Space portal (Observing Systems Capability Analysis and Review Tool).
Currently 1,025 satellites and 1,230 instruments from 81 space agencies worldwide.
Unlike catalogs that focus on a single agency (e.g., NASA, ESA)… See the full description on the dataset page: https://huggingface.co/datasets/juliensimon/wmo-oscar-satellites.GOCE-satellite-telemtryUtilisation of this data is subject to European Space Agency's Earth Observation Terms and Conditions. Read T&C here
This is Dataset Version 3 - Updates may be done following feedback from the machine learning community.
Dataset Description
This dataset contains 327 time series corresponding to the temporal values of 327 telemetry parameters over the life of the real GOCE satellite (from March 2009 to October 2013). It consists both the raw data and Machine-Learning ready-to-use… See the full description on the dataset page: https://huggingface.co/datasets/patrickfleith/GOCE-satellite-telemtry.GEO_satellite_maneuvers
Simulated GEO Satellite Maneuver Dataset
Dataset Summary
This dataset contains simulated GEO satellite trajectories for station-keeping scenarios.Each sample is exported as a pair of files:
State vectors: state_vectors/*_state_vectors.parquet
Metadata: metadata/*_metadata.parquet
Files share the same <timestamp>_<pid> prefix and belong together. The dataset is organized into two subfolders: state_vectors/ and metadata/.
Simulation Tool
Dataset generated… See the full description on the dataset page: https://huggingface.co/datasets/FraDra/GEO_satellite_maneuvers.LEVIR-CDsatellite-disruption-triage-aux-v2-1
Satellite Disruption Triage Aux v2.1
Self-contained real-image repair of ChrisRPL/satellite-disruption-triage-aux-v2.
This version keeps only resolvable BRIGHT real-image rows in VLM SFT files. Synthetic reasoning rows are separated, SEN12MSCR is excluded because the license is unknown, and xBD-Ukraine rows from v2 are excluded because their image references are not resolvable in the stated source repo.
Files
train_flat.jsonl / train_sft.jsonl: real-image train rows… See the full description on the dataset page: https://huggingface.co/datasets/ChrisRPL/satellite-disruption-triage-aux-v2-1.satellite-building-segmentation
Dataset Labels
['building']
Number of Images
{'train': 6764, 'valid': 1934, 'test': 967}
How to Use
Install datasets:
pip install datasets
Load the dataset:
from datasets import load_dataset
ds = load_dataset("keremberke/satellite-building-segmentation", name="full")
example = ds['train'][0]
Roboflow Dataset Page
https://universe.roboflow.com/roboflow-universe-projects/buildings-instance-segmentation/dataset/1
Citation… See the full description on the dataset page: https://huggingface.co/datasets/keremberke/satellite-building-segmentation.