Whales from space dataset, an annotated satellite image dataset of whales for training machine learning models.

Whales from space dataset, an annotated satellite image dataset of whales for training machine learning models.
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DOI:
10.1038/s41597-022-01377-4
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发表时间:
2022-05-27
期刊:
影响因子:
9.8
通讯作者:
Fretwell, Peter T.
Fretwell, Peter T.
中科院分区:
综合性期刊2区
文献类型:
--
作者:
Cubaynes, Hannah C.;Fretwell, Peter T.

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在偏远地区监测鲸鱼对保护鲸鱼很重要;然而,在这些地区使用传统的调查平台(船和飞机)在后勤上很困难。利用高分辨率卫星图像调查鲸鱼,特别是在偏远地区,这种做法越来越受到关注,势头也越来越强劲。然而,这项新兴技术的发展依赖于精确的自动化系统来检测鲸鱼,而这是目前所缺乏的。这种检测系统需要访问一个开源库,其中包含卫星图像中注释的鲸鱼示例,以训练和测试自动检测系统。在这里,我们提出了一个数据集的633注释鲸鱼对象,创建的测量6,300平方公里的卫星图像捕获的各种非常高分辨率的卫星(即世界观-3,世界观-2,GeoEye-1和Quickbird-2)在不同地区的地球仪(如阿根廷,新西兰,南非,美国,墨西哥)。该数据集涵盖了四个不同的物种:南露脊鲸(Eubalaena australis)、座头鲸(Megaptera novaeangliae)、长须鲸(Balaenoptera physalus)和灰鲸(Balrichtius robustus)。
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 australis), humpback whale (Megaptera novaeangliae), fin whale (Balaenoptera physalus), and grey whale (Eschrichtius robustus).
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影响因子: 3.7
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发表时间: 2021-02-01
期刊: Sensors (Basel, Switzerland)
影响因子: --
作者:
Höschle C;Cubaynes HC;Clarke PJ;Humphries G;Borowicz A
通讯作者: Borowicz A
DOI: 10.1371/journal.pone.0254380
发表时间: 2021
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影响因子: 3.7
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