Published June 8, 2021 | Version 1.0.0

Maximum Independent Set Satellite Scheduling World Cities Data Set

  • 1. ROR icon Stanford University

Description

Satellite Scheduling World Cities Data Set

The Satellite Scheduling World Cities Data Set is the a set of cities treated as point locations used to simulate a set of image collection tasking requests for AIAA paper "A Maximum Independent Set Method for Scheduling Earth-Observing Satellite Constellations". It provides an open reference and benchmark for the satellite task scheduling problem. This could also be considered as a sparse Maximum Independent Set problem for a generic graph. The requests represent point collects, from which we can compute multiple distinct collection opportunities. The tasking problem is then to select a subset of these collects that it is possible for the spacecraft to feasibly collect in a given time period, subject to constraints on the spacecraft's agility and constraints on only collecting a single collect per request (no duplication of effort).

The data set is hosted on both Github and Zenodo. The Github repository contains the original source data, the associated requests generated from the source data, and scripts to reproduce the scenario files. Zenodo (DOI 10.5281/zenodo) hosts copies of the output Metis graph files and collect data files. Due to the large size of produced files these are not included in the Github repository.

Notes

Notes

Please note that while the source data and generation methods are identical to the satellite task planning paper it was created for. The specific generated problems do not exactly reproduce the scenario in the paper. Since the original reproduction, updates in upstream software dependencies have changed the output of the generation process (specifically, Earth orientaiton parameter handling libraries). This can be determined by considering the cardinality of the generated collect set. However, these differences are generally small and since the constriant rate is similar, the results should be comparable.

Spacecraft Count Orignial Publication Collect Count Reproduction Collect Count
4 59356 59624
6 90777 91204
12 180008 180939
24 359170 361519


This repository also adds additional scenarios for 1, 2, and 36 satellites. Note, the provided scenarios represent the largest 10,000 request data set. Should a smaller request set be desired, the requests should be filtered to the top `x` request based on city population and any collects not associated with those requests should be discarded.

Note the Zenodo repository excludes the collect and graph files for the 1 and 2 satellite scenarios to avoid the file limits. These can still be reproduced from the Github source code.

Acknolwedgement

If this data set is used in your research, please cite the following paper

A Maximum Independent Set Method for Scheduling Earth-Observing Satellite Constellations

@article{eddy2021maximum,
  title={A Maximum Independent Set Method for Scheduling Earth-Observing Satellite Constellations},
  author={Eddy, Duncan and Kochenderfer, Mykel J},
  journal={Journal of Spacecraft and Rockets},
  volume={58},
  number={5},
  pages={1416--1429},
  year={2021},
  publisher={American Institute of Aeronautics and Astronautics}
}

Licensing

The source of the world cities data is from the simplemaps.com website,
licensed under the Creative Commons Attribution 4.0 International License with the specific license found at `./data/worldcities_license.txt`.

Files

requirements.txt

Files (8.3 GB)

Name Size
md5:51dc7213c90fa9dd80e61661781ebcfa
1.1 kB Download
md5:eebb6abf1e4291b1968c296273ac8bb7
82 Bytes Preview Download
md5:15b1464d202cddedac969243da735fc1
658 Bytes Preview Download
md5:b38626e1ea4a23bfbcc6afbfee0f8f8e
7.9 kB Preview Download
md5:394aa72917661b572d1aa08785e95b9d
1.3 kB Preview Download
md5:b52a47e06b135c2c49a7e1dbab1834d3
15.8 kB Preview Download
md5:a7c57f85b3f4cfd8f1051cc1a4938608
23.7 kB Preview Download
md5:4744eb0952bb57aafe1b831eff3c8af4
2.6 kB Preview Download
md5:76b25a2970f79495c40b1502e6018213
3.9 kB Preview Download
md5:597fd031eba04624361f9761ab93bb97
1.7 MB Preview Download
md5:6a276d9ba431d4ece2f795ca02c2b518
11.3 MB Preview Download
md5:eb77fb10d7dc2f0a891c61a8015c364f
45.6 MB Preview Download
md5:078a8a8c5a9ba4163991df1ec3fb6acd
43.3 MB Preview Download
md5:90030e0895795aaf91265fdf71dfad0d
43.2 MB Preview Download
md5:e1fb329c9f5119235eb51b39ab27c602
43.4 MB Preview Download
md5:c9fdf11cae54a170e0a9f2b9c4c530dc
42.8 MB Preview Download
md5:6eb0293bbab4843225588424186dcf98
42.2 MB Preview Download
md5:60632c2e8d625ba03bbfb6bbaefec1e8
43.0 MB Preview Download
md5:c690e01fd42a57f58cfc06eea88e6f24
44.6 MB Preview Download
md5:b7839edff7b7cedf3845fa887b7d8902
41.4 MB Preview Download
md5:34926b86d62b9635f6dfedcc016bf6d8
41.7 MB Preview Download
md5:af3a5a87b8bd473fba1fcb015c069bf2
46.3 MB Preview Download
md5:501a58957c70e3aa5dc6cda8987a82c6
42.7 MB Preview Download
md5:17f5ec2827a491c5c957ba3ff7b19b3f
647.9 MB Download
md5:0cf06b6254bfc5fdafc39860d0d3cb6e
45.6 MB Preview Download
md5:f87161305d418f72d11041d5825b4d22
43.1 MB Preview Download
md5:044d8c895565a4e4005d05c6f8b9bcf9
44.5 MB Preview Download
md5:74dd500358f852a4b338632db87b3adb
41.6 MB Preview Download
md5:a8ba8ecaef75f8536ecebd19cd80e175
41.7 MB Preview Download
md5:3ad9db4b05b19fb1200b815f761d00ea
46.4 MB Preview Download
md5:c6ae90f4df8d1d52e8bc1ea52018008d
42.7 MB Preview Download
md5:637b97374da9fabcfefea95a7938c52c
43.3 MB Preview Download
md5:c1418771bbc66c665bf7ffeee7984318
43.8 MB Preview Download
md5:3a8e6f2516c75cbd7612e639579a5208
42.8 MB Preview Download
md5:ee9dd3e378b7602a8f868507f9221f64
43.3 MB Preview Download
md5:99319046fd78495a24a11a37483785ea
42.8 MB Preview Download
md5:315eb35df5d81e784f38c90688fbeae1
43.2 MB Preview Download
md5:31047a351d711088c9567fcb2ea68dcf
43.4 MB Preview Download
md5:af1d6f3adc84cb8610cf590ccd4ef44e
43.5 MB Preview Download
md5:04d9e33bdbfc5928092801dc25ae4414
42.9 MB Preview Download
md5:111434da5618a0f895efd17ca15ba25e
42.8 MB Preview Download
md5:36fe380f5acf1b0cc7af5af88ab254f3
42.2 MB Preview Download
md5:587900cb82fdec0edde43d582a390ba9
44.6 MB Preview Download
md5:c148360f8e835454ca31d1a83e0ab2a7
44.0 MB Preview Download
md5:e23190d43ab0390e0f3ef976f502e470
41.1 MB Preview Download
md5:03be73809366663878f975c07ee2fd3d
43.0 MB Preview Download
md5:f8d32c13b1ce4d529da88cc73cb949a4
44.6 MB Preview Download
md5:f4761b3573aebe4f8942e96771cbf5bf
41.4 MB Preview Download
md5:1df430be9d90259327dafd4a1e30206d
1.4 GB Download
md5:00be5b804118f46b131b4378c2b173d1
45.6 MB Preview Download
md5:8bce8541985a3ddef78537775c62a2b0
43.0 MB Preview Download
md5:3c9129e68019fc399d26426d2e5dc40c
44.6 MB Preview Download
md5:e3585db84eeecbaac2a25305377483a2
41.5 MB Preview Download
md5:00b8f722b4a39d9e6b4483d478d4af6e
46.2 MB Preview Download
md5:da88275efbe5a7895ab719002cb6f9ad
41.5 MB Preview Download
md5:bc2619f807a54852dc32c5a15d556799
41.7 MB Preview Download
md5:c4ecf24cff7ea527bece01c1d8669402
43.0 MB Preview Download
md5:d258ca54e427a12c88ee8f25c3308c7b
42.8 MB Preview Download
md5:d715b482a77f1cfd745581bf491b0672
44.0 MB Preview Download
md5:f35c7e3a0af39f7859ffc33a787ef8b4
41.7 MB Preview Download
md5:bc9729476f6b14dad8b27e223895718b
42.8 MB Preview Download
md5:834aba6dab0ae2cadcb28157ecd414ee
46.4 MB Preview Download
md5:a5d3f3aac07058a4aaa0a4bdd9881dfd
42.7 MB Preview Download
md5:68b16d1887da222555f07f847a116244
43.8 MB Preview Download
md5:ac2c3f7b66f5062bdd510bdb4f0e71f7
46.2 MB Preview Download
md5:7c8a74f073c4ba598ab6ba2682267c68
40.9 MB Preview Download
md5:b8e578196b91472edf46035235f988e9
43.7 MB Preview Download
md5:1ddd24fe3533dec017416d4e17aa9b28
43.0 MB Preview Download
md5:6222f9714a81f32ecbddbadae2e9817b
42.7 MB Preview Download
md5:38784a2ac7e287181e88c746b6cc2feb
43.3 MB Preview Download
md5:f35febfc5eb26563d92586e9ef16247f
43.2 MB Preview Download
md5:b5bacb5d662de1bb4956b47e8c5a53aa
42.2 MB Preview Download
md5:9a22033ed4f1272e708ec7c6024698ad
43.4 MB Preview Download
md5:e531c406e8f5dc9a7bb58707df70e2dd
41.3 MB Preview Download
md5:cef21ecdce852a12ad4fb874baee78c0
44.8 MB Preview Download
md5:8d042112e25d08d18616572087be12c9
43.2 MB Preview Download
md5:d7e649e7bfe6a5a1bbe0012fc3a91e53
43.2 MB Preview Download
md5:d38cb97d187ffdac88cf883c90179faa
44.4 MB Preview Download
md5:643d82cbc971a6c2945a8551bc5bf190
41.4 MB Preview Download
md5:b5eb6c0e5a5affacd3dbdd4a58af8845
47.8 MB Preview Download
md5:304030982bfcee65fd3e6bf987cb254c
42.0 MB Preview Download
md5:a1d3c9b9e8df5ea4170990b97776124b
41.6 MB Preview Download
md5:f88c965205f4bbd34c9506cb2057d251
41.6 MB Preview Download
md5:f2019d31e5af9c29eda63e2836e6c098
42.9 MB Preview Download
md5:ce7b16c7424f9f100655332977d0601a
43.9 MB Preview Download
md5:193e5f82569494d98a9da24ab5389e8c
2.2 GB Download
md5:3763abcb20aa0632a4799b65d8630320
45.6 MB Preview Download
md5:bdfb4d7ea62162b18f3cbdf34573a9d4
43.0 MB Preview Download
md5:253e185680e9a8d0b74208f1bcb28847
41.7 MB Preview Download
md5:33b6502cc9bf24443ff4437bf8b3a62d
43.3 MB Preview Download
md5:af167dfcdcc063528ef462566cfe95fb
184.3 MB Download
md5:54005a5ba9a3a61aebcab507d6cb6608
45.6 MB Preview Download
md5:177ec15fd93cc7ed9913626b20a2fc95
42.8 MB Preview Download
md5:4aa9754b5f199b26559346150e9334e3
42.2 MB Preview Download
md5:6eb35bfe73900ca8e60d76068d5489c6
41.7 MB Preview Download
md5:2d021f258fbd9f9345a889add4024500
46.3 MB Preview Download
md5:b797c38d6fe07b952f463bbb7b4a279e
42.7 MB Preview Download
md5:a1d3e7478a13c66d19ac81789df7fffe
302.5 MB Download
md5:a8e7bdb82ee57d9d60717c5530714bc4
4.7 kB Preview Download

Additional details

Dates

Available
2024-04-06
Data set published on Zenodo
Available
2021-06-08

Software

Repository URL
https://github.com/duncaneddy/aiaa-mis-satellite-scheduling-dataset
Programming language
Python
Development Status
Inactive