Whales from space dataset, an annotated satellite image dataset of whales for training machine learning models
Monitoring whales in remote areas is important for their conservation; however, using traditional survey platforms (boat and plane) in such regions is logistically difficult. The use of very high-resolution satellite imagery to survey whales, particularly in remote locations, is gaining interest and...
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ftpubmed:oai:pubmedcentral.nih.gov:9142526 2023-05-15T15:36:37+02:00 Whales from space dataset, an annotated satellite image dataset of whales for training machine learning models Cubaynes, Hannah C. Fretwell, Peter T. 2022-05-27 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9142526/ http://www.ncbi.nlm.nih.gov/pubmed/35624202 https://doi.org/10.1038/s41597-022-01377-4 en eng Nature Publishing Group UK http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9142526/ http://www.ncbi.nlm.nih.gov/pubmed/35624202 http://dx.doi.org/10.1038/s41597-022-01377-4 © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . CC-BY Sci Data Data Descriptor Text 2022 ftpubmed https://doi.org/10.1038/s41597-022-01377-4 2022-06-05T00:47:38Z Monitoring whales in remote areas is important for their conservation; however, using traditional survey platforms (boat and plane) in such regions is logistically difficult. The use of very high-resolution satellite imagery to survey whales, particularly in remote locations, is gaining interest and momentum. However, the development of this emerging technology relies on accurate automated systems to detect whales, which are currently lacking. Such detection systems require access to an open source library containing examples of whales annotated in satellite images to train and test automatic detection systems. Here we present a dataset of 633 annotated whale objects, created by surveying 6,300 km2 of satellite imagery captured by various very high-resolution satellites (i.e. WorldView-3, WorldView-2, GeoEye-1 and Quickbird-2) in various regions across the globe (e.g. Argentina, New Zealand, South Africa, United States, Mexico). The dataset covers four different species: southern right whale (Eubalaena glacialis), humpback whale (Megaptera novaeangliae), fin whale (Balaenoptera physalus), and grey whale (Eschrichtius robustus). Text Balaenoptera physalus Eubalaena glacialis Fin whale Humpback Whale Megaptera novaeangliae Southern Right Whale PubMed Central (PMC) Argentina New Zealand Scientific Data 9 1 |
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Data Descriptor Cubaynes, Hannah C. Fretwell, Peter T. Whales from space dataset, an annotated satellite image dataset of whales for training machine learning models |
topic_facet |
Data Descriptor |
description |
Monitoring whales in remote areas is important for their conservation; however, using traditional survey platforms (boat and plane) in such regions is logistically difficult. The use of very high-resolution satellite imagery to survey whales, particularly in remote locations, is gaining interest and momentum. However, the development of this emerging technology relies on accurate automated systems to detect whales, which are currently lacking. Such detection systems require access to an open source library containing examples of whales annotated in satellite images to train and test automatic detection systems. Here we present a dataset of 633 annotated whale objects, created by surveying 6,300 km2 of satellite imagery captured by various very high-resolution satellites (i.e. WorldView-3, WorldView-2, GeoEye-1 and Quickbird-2) in various regions across the globe (e.g. Argentina, New Zealand, South Africa, United States, Mexico). The dataset covers four different species: southern right whale (Eubalaena glacialis), humpback whale (Megaptera novaeangliae), fin whale (Balaenoptera physalus), and grey whale (Eschrichtius robustus). |
format |
Text |
author |
Cubaynes, Hannah C. Fretwell, Peter T. |
author_facet |
Cubaynes, Hannah C. Fretwell, Peter T. |
author_sort |
Cubaynes, Hannah C. |
title |
Whales from space dataset, an annotated satellite image dataset of whales for training machine learning models |
title_short |
Whales from space dataset, an annotated satellite image dataset of whales for training machine learning models |
title_full |
Whales from space dataset, an annotated satellite image dataset of whales for training machine learning models |
title_fullStr |
Whales from space dataset, an annotated satellite image dataset of whales for training machine learning models |
title_full_unstemmed |
Whales from space dataset, an annotated satellite image dataset of whales for training machine learning models |
title_sort |
whales from space dataset, an annotated satellite image dataset of whales for training machine learning models |
publisher |
Nature Publishing Group UK |
publishDate |
2022 |
url |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9142526/ http://www.ncbi.nlm.nih.gov/pubmed/35624202 https://doi.org/10.1038/s41597-022-01377-4 |
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Argentina New Zealand |
geographic_facet |
Argentina New Zealand |
genre |
Balaenoptera physalus Eubalaena glacialis Fin whale Humpback Whale Megaptera novaeangliae Southern Right Whale |
genre_facet |
Balaenoptera physalus Eubalaena glacialis Fin whale Humpback Whale Megaptera novaeangliae Southern Right Whale |
op_source |
Sci Data |
op_relation |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9142526/ http://www.ncbi.nlm.nih.gov/pubmed/35624202 http://dx.doi.org/10.1038/s41597-022-01377-4 |
op_rights |
© The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
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CC-BY |
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https://doi.org/10.1038/s41597-022-01377-4 |
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