British Antarctic Survey, High Cross, Madingley Road, Cambridge, CB3 0ET, UK.
Scott Polar Research Institute, University of Cambridge, Lensfield Road, Cambridge, CB2 1ER, UK.
Sci Data. 2022 May 27;9(1):245. doi: 10.1038/s41597-022-01377-4.
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).
监测偏远地区的鲸鱼对于它们的保护非常重要；然而，在这些地区使用传统的调查平台（船只和飞机）在后勤上是困难的。利用超高分辨率卫星图像来调查鲸鱼，特别是在偏远地区，正越来越受到关注和重视。然而，这项新兴技术的发展依赖于能够准确自动检测鲸鱼的系统，而目前这种系统还很缺乏。这些检测系统需要访问一个包含卫星图像中标注的鲸鱼示例的开源库，以便对自动检测系统进行训练和测试。在这里，我们提出了一个包含 633 个标注鲸鱼对象的数据集，该数据集是通过对全球不同地区（如阿根廷、新西兰、南非、美国、墨西哥）的各种超高分辨率卫星（即 WorldView-3、WorldView-2、GeoEye-1 和 Quickbird-2）拍摄的 6300 平方公里的卫星图像进行调查而创建的。该数据集涵盖了四个不同的物种：南方露脊鲸（Eubalaena glacialis）、座头鲸（Megaptera novaeangliae）、长须鲸（Balaenoptera physalus）和灰鲸（Eschrichtius robustus）。
