亚得里亚海东岸水藻生境测绘声学测量方法的优化

Lovro Klarić, A. Dapo, B. Pribicevic
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引用次数: 0

摘要

本研究为优化亚得里亚海东岸海洋波西多尼亚藻类生境绘制过程提供了一种新的方法。迄今为止,亚得里亚海水下和沿海栖息地的制图主要采用直接方法(潜水、下拉相机等)和间接建模相结合的方法,这在大多数情况下会导致数据的异质性。上述方法已被证明是不可靠的、昂贵的,而且只能提供信息。现代间接遥感方法能够分析整个水柱中返回声信号的色散,从而更详细和有效地绘制栖息地地图。侧面扫描回声测深成像由于其良好的海底覆盖范围,已广泛用于栖息地测绘。然而,它仍然被证明有一些局限性(例如,需要与其他仪器结合来收集精确的水深数据)。多波束回声测深仪可以实现对海底的全面覆盖,精确的水深数据和后向散射数据可以进行更详细的分析。另一方面,同时使用侧扫和多波束回声测深仪进行水文测量,可以获得更好的图像,更好的海底覆盖范围,以及大量不同的数据集。这种方法需要优化声学仪器来收集详细的数据,这可以在以后更成功地分类Posidonia oceanica水下栖息地。事实证明,这种方法更省时、更精确,而且对未来绘制大面积海域具有成本效益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
OPTIMIZATION OF ACOUSTIC SURVEY METHODS FOR HABITAT MAPPING OF THE POSIDONIA OCEANICA ALGAE ON THE EASTERN COAST OF THE ADRIATIC
This study presents a new approach to optimize the habitat mapping process of the Posidonia oceanica algae on the east coast of the Adriatic Sea. Mapping of underwater and coastal habitats in the Adriatic Sea, until now, was conducted by direct methods (diving, drop-down camera, etc.) in combination with indirect modelling, which in the majority of cases results in data heterogeneity. The mentioned approach has proven unreliable, expensive, and only informative. Modern indirect, remote sensing methods enable an analysis of the dispersion of the return acoustic signal in the entire water column, leading to more detailed and effective habitat mapping. Side-scan echo sounder imagery has been extensively used for habitat mapping due to its good seafloor coverage. However, it still has proven to have some limitations (e.g. need for combining with other instruments to collect precise bathymetric data). Multibeam echo sounder enables full coverage of the seafloor, precise bathymetric data, and backscatter data allowing more detailed analysis. On the other hand, a simultaneous hydrographic survey with side-scan and multibeam echo sounder results in superior imagery, better seafloor coverage, and vast and various data sets. This approach requires optimization of the acoustic instruments for collecting detailed data, which can later result in a more successful classification of the Posidonia oceanica underwater habitat. Such methodology has proven to be less time-consuming, more precise, and cost-benefit for future mapping of large sea areas.
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