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The Impact of Satellite Trails on Hubble Space Telescope Observations: satellite classifications

The Impact of Satellite Trails on Hubble Space Telescope Observations: satellite classifications
The Impact of Satellite Trails on Hubble Space Telescope Observations: satellite classifications
This repository contains the Hubble Space Telescope (HST) observations with satellite classifications, released in the paper "The Impact of Satellite Trails on Hubble Space Telescope Observations" (DOI: 10.1038/s41550-023-01903-3). This table contains 114 607 individual HST images taken in the last 19 years and publicly released in the eHST archive by 3 October 2021, with satellite trail classifications made with machine learning and citizen science. We processed the individual images by adding the two ACS/WFC (WFC3/UVIS, respectively) apertures side-by-side, without correcting for geometric distortions and without the gap between the two detectors (hence why the satellite trails can appear discontinuous in the images). Note that these are not original images from the eHST archive, and therefore are not meant for other scientific analysis. The dataset contains 3072 HST images with satellites (2.7% of the dataset) and 3228 satellite trails in total. The classifications were visually inspected and vetted by the authors (images are flagged with the 'satellite' flag). The table contains the following columns: observation IDs: both individual exposures (simple_id) and composite images, multiple individual exposures processed and stacked (composite_id); instrument: ACS/WFC or WFC3/UVIS; start time and end time of exposure; exposure duration; right ascension (ra) and declination (dec); 'satellite' flag [empty otherwise]; no_sat: number of satellites in the image; image URL - URL for the individual HST observations used for satellite classification; additional metadata columns, as available in the eHST archive. The satellites were classified by volunteers on the Hubble Asteroid Hunter citizen science project and with a machine learning classifier. Please cite the paper (Kruk et al., https://www.nature.com/articles/s41550-023-01903-3) when using the data in this repository.
Zenodo
Popescu, Marcel
cc7a25bd-bba8-489b-ac93-36d0410dd58d
Dillmann, Steven
40a7975b-8447-4e09-aee4-bd815030736e
Perks, Megan E.
94ad0f72-c3c7-4154-8c5e-a2fc8d1359b7
Lund, Tamina
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Merin, Bruno
270edc10-5b22-4eeb-b47e-6caa4d8086ec
Aussel, Ben
5f943af8-b42d-4725-95d1-6b26b2840834
Thomson, Ross
f20d7a64-6756-4d06-a562-22e9d4dfad7d
Karadag, Samet
2112df64-0bfc-4a2b-a8e3-0cf9f23c1a25
McCaughrean, Mark J.
620ec264-c600-4b53-8ee3-30fa0f19bad8
Kruk, Sandor
595330a5-a5ee-4809-8352-8f67accb5a44
Martin, Pablo Garcia
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Popescu, Marcel
cc7a25bd-bba8-489b-ac93-36d0410dd58d
Dillmann, Steven
40a7975b-8447-4e09-aee4-bd815030736e
Perks, Megan E.
94ad0f72-c3c7-4154-8c5e-a2fc8d1359b7
Lund, Tamina
a935121c-5e5f-438c-99f9-e5c4b7972218
Merin, Bruno
270edc10-5b22-4eeb-b47e-6caa4d8086ec
Aussel, Ben
5f943af8-b42d-4725-95d1-6b26b2840834
Thomson, Ross
f20d7a64-6756-4d06-a562-22e9d4dfad7d
Karadag, Samet
2112df64-0bfc-4a2b-a8e3-0cf9f23c1a25
McCaughrean, Mark J.
620ec264-c600-4b53-8ee3-30fa0f19bad8
Kruk, Sandor
595330a5-a5ee-4809-8352-8f67accb5a44
Martin, Pablo Garcia
d8d21319-1158-4a80-9ce0-5b4a9c62b69c

(2022) The Impact of Satellite Trails on Hubble Space Telescope Observations: satellite classifications. Zenodo doi:10.5281/zenodo.7474191 [Dataset]

Record type: Dataset

Abstract

This repository contains the Hubble Space Telescope (HST) observations with satellite classifications, released in the paper "The Impact of Satellite Trails on Hubble Space Telescope Observations" (DOI: 10.1038/s41550-023-01903-3). This table contains 114 607 individual HST images taken in the last 19 years and publicly released in the eHST archive by 3 October 2021, with satellite trail classifications made with machine learning and citizen science. We processed the individual images by adding the two ACS/WFC (WFC3/UVIS, respectively) apertures side-by-side, without correcting for geometric distortions and without the gap between the two detectors (hence why the satellite trails can appear discontinuous in the images). Note that these are not original images from the eHST archive, and therefore are not meant for other scientific analysis. The dataset contains 3072 HST images with satellites (2.7% of the dataset) and 3228 satellite trails in total. The classifications were visually inspected and vetted by the authors (images are flagged with the 'satellite' flag). The table contains the following columns: observation IDs: both individual exposures (simple_id) and composite images, multiple individual exposures processed and stacked (composite_id); instrument: ACS/WFC or WFC3/UVIS; start time and end time of exposure; exposure duration; right ascension (ra) and declination (dec); 'satellite' flag [empty otherwise]; no_sat: number of satellites in the image; image URL - URL for the individual HST observations used for satellite classification; additional metadata columns, as available in the eHST archive. The satellites were classified by volunteers on the Hubble Asteroid Hunter citizen science project and with a machine learning classifier. Please cite the paper (Kruk et al., https://www.nature.com/articles/s41550-023-01903-3) when using the data in this repository.

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More information

Published date: 22 December 2022

Identifiers

Local EPrints ID: 473804
URI: http://eprints.soton.ac.uk/id/eprint/473804
PURE UUID: a32be867-e854-449f-a653-c43b99181bf8

Catalogue record

Date deposited: 01 Feb 2023 17:31
Last modified: 20 Nov 2023 18:18

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Contributors

Contributor: Marcel Popescu
Contributor: Steven Dillmann
Contributor: Megan E. Perks
Contributor: Tamina Lund
Contributor: Bruno Merin
Contributor: Ben Aussel
Contributor: Ross Thomson
Contributor: Samet Karadag
Contributor: Mark J. McCaughrean
Contributor: Sandor Kruk
Contributor: Pablo Garcia Martin

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