The Potential of Satellite Imagery for Surveying Whales.
The Potential of Satellite Imagery for Surveying Whales.
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DOI：
10.3390/s21030963
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发表时间：
2021-02-01
期刊：
影响因子：
--
通讯作者：
Borowicz A
中科院分区：
文献类型：
--
作者：
Höschle C;Cubaynes HC;Clarke PJ;Humphries G;Borowicz A
高分辨率（VHR）卫星图像（空间分辨率小于1米）的出现为生态学和保护生物学领域创造了新的机会。亚米分辨率图像的进步为地面特征的检测和识别提供了更大的信心，扩大了可能研究问题的领域。迄今为止，VHR图像研究主要集中在陆地环境；然而，在过去的二十年里，这项技术在探测鲸类动物方面取得了渐进式的进展。随着计算能力和传感器分辨率的提高，利用具有自动检测和分类过程的VHR卫星图像进行大尺度VHR海洋调查的可行性增加了。自动调查的初步尝试显示出有希望的结果，但需要进一步发展以确保可靠性。在这里，我们讨论了未来的方向，其中VHR卫星图像可能用于解决鲸鱼保护的紧迫问题。我们强调了目前在自动检测和将这项技术推广到所有海洋和各种鲸鱼物种方面所面临的挑战。为了实现盆地尺度的海洋调查，目前任何传统的测量方法（包括船载和航空测量）都是不可行的，未来的研究需要生物学、计算科学和工程学之间的合作努力，以克服目前对该平台使用的挑战。
The emergence of very high-resolution (VHR) satellite imagery (less than 1 m spatial resolution) is creating new opportunities within the fields of ecology and conservation biology. The advancement of sub-meter resolution imagery has provided greater confidence in the detection and identification of features on the ground, broadening the realm of possible research questions. To date, VHR imagery studies have largely focused on terrestrial environments; however, there has been incremental progress in the last two decades for using this technology to detect cetaceans. With advances in computational power and sensor resolution, the feasibility of broad-scale VHR ocean surveys using VHR satellite imagery with automated detection and classification processes has increased. Initial attempts at automated surveys are showing promising results, but further development is necessary to ensure reliability. Here we discuss the future directions in which VHR satellite imagery might be used to address urgent questions in whale conservation. We highlight the current challenges to automated detection and to extending the use of this technology to all oceans and various whale species. To achieve basin-scale marine surveys, currently not feasible with any traditional surveying methods (including boat-based and aerial surveys), future research requires a collaborative effort between biology, computation science, and engineering to overcome the present challenges to this platform’s use.
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影响因子：
10.1
作者：
Moxley JH;Bogomolni A;Hammill MO;Moore KMT;Polito MJ;Sette L;Sharp WB;Waring GT;Gilbert JR;Halpin PN;Johnston DW
通讯作者：
Johnston DW
影响因子：
3.7
作者：
Fretwell PT;Staniland IJ;Forcada J
通讯作者：
Forcada J
影响因子：
4.6
作者：
Bamford, C. C. G.;Kelly, N.;Jackson, J. A.
通讯作者：
Jackson, J. A.
影响因子：
4.6
作者：
Guirado, Emilio;Tabik, Siham;Herrera, Francisco
通讯作者：
Herrera, Francisco
影响因子：
3.7
作者：
Kaschner, Kristin;Quick, Nicola J.;Harris, Catriona M.
通讯作者：
Harris, Catriona M.