A new method for ecological surveying of the abyss using autonomous underwater vehicle photography
A new method for ecological surveying of the abyss using autonomous underwater vehicle photography
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DOI：
10.4319/lom.2014.12.795
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发表时间：
2014-11-01
影响因子：
2.7
通讯作者：
Ruhl, Henry A.
中科院分区：
文献类型：
--
作者：
Morris, Kirsty J.;Bett, Brian J.;Ruhl, Henry A.
随着技术进步，特别是利用自主水下航行器的光学成像，海洋环境测绘的范围和速度正在迅速增加。本文介绍了一种新的深海数码静止照相机系统，该系统可拍摄高频（> 1赫兹）海底彩色照片，适用于详细的生物和生境评估，并介绍了有效处理这种海量图像的手段，以便能够对从单个巨型底栖生物到景观尺度（> 100公里（2））的各种空间尺度进行评估。作为深渊自主生态勘测项目的一部分，AUV Autosub 6000获得了超过150，000张海底图像（类似于160公里的总样带长度），以调查豪猪深海平原（4，850米;大西洋东北部）的巨型动物分布。开发了图像处理的自动化工作流程，纠正了不均匀的照明和颜色，地理参考了照片，并产生了10个图像的马赛克（“瓷砖”，每个代表15-20米（2）的海底连续带），删除了连续图像之间的重叠。然后手动注释这些图块以生成生物数据。与其他技术相比，这种方法非常有利，大大提高了图像采集速度，与拖网相比，准确性提高了10-50倍。该方法还提供了比其他技术更精确的密度和生物多样性估计[变异系数（CV）< 10%]，与WASP拖曳相机系统相比，密度估计精度提高了2倍。最终，这个新系统有望为了解人类在深海的影响做出宝贵贡献。
The extent and speed of marine environmental mapping is increasing quickly with technological advances, particularly with optical imaging from autonomous underwater vehicles (AUVs). This contribution describes a new deep-sea digital still camera system that takes high-frequency (> 1 Hz) color photographs of the seafloor, suitable for detailed biological and habitat assessment, and the means of efficient processing of this mass imagery, to allow assessment across a wide range of spatial scales from that of individual megabenthic organisms to landscape scales (> 100 km(2)). As part of the Autonomous Ecological Surveying of the Abyss (AESA) project, the AUV Autosub6000 obtained > 150,000 seafloor images (similar to 160 km total transect length) to investigate the distribution of megafauna on the Porcupine Abyssal Plain (4850 m; NE Atlantic). An automated workflow for image processing was developed that corrected nonuniform illumination and color, geo-referenced the photographs, and produced 10-image mosaics ('tiles,' each representing a continuous strip of 15-20 m(2) of seafloor), with overlap between consecutive images removed. These tiles were then manually annotated to generate biological data. This method was highly advantageous compared with alternative techniques, greatly increasing the rate of image acquisition and providing a 10-50 fold increase in accuracy in comparison to trawling. The method also offers more precise density and biodiversity estimates [Coefficient of variation (CV) < 10%] than alternative techniques, with a 2-fold improvement in density estimate precision compared with the WASP towed camera system. Ultimately, this novel system is expected to make valuable contributions to understanding human impact in the deep ocean.