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A low-cost drone based application for identifying and mapping of coastal fish nursery grounds

机译：一种低成本的无人机应用程序，用于识别和制图沿海鱼类苗圃场

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摘要

Acquiring seabed, landform or other topographic data in the field of marine ecology has a pivotal role in defining and mapping key marine habitats. However, accessibility for this kind of data with a high level of detail for very shallow and inaccessible marine habitats has been often challenging, time consuming. Spatial and temporal coverage often has to be compromised to make more cost effective the monitoring routine. Nowadays, emerging technologies, can overcome many of these constraints. Here we describe a recent development in remote sensing based on a small unmanned drone (UAVs) that produce very fine scale maps of fish nursery areas. This technology is simple to use, inexpensive, and timely in producing aerial photographs of marine areas. Both technical details regarding aerial photos acquisition (drone and camera settings) and post processing workflow (3D model generation with Structure From Motion algorithm and photo-stitching) are given. Finally by applying modern algorithm of semi-automatic image analysis and classification (Maximum Likelihood, ECHO and Object-based Image Analysis) we compared the results of three thematic maps of nursery area for juvenile sparid fishes, highlighting the potential of this method in mapping and monitoring coastal marine habitats. (C) 2016 Elsevier Ltd. All rights reserved.
机译：在海洋生态学领域中获取海床，地形或其他地形数据对于定义和绘制重要的海洋生境具有举足轻重的作用。但是，对于非常浅和无法访问的海洋栖息地，具有高细节水平的此类数据的可访问性通常是挑战性的，耗时的。通常必须牺牲空间和时间范围，以使监视例程更具成本效益。如今，新兴技术可以克服许多这些限制。在这里，我们描述了一种基于小型无人无人机（UAV）的遥感技术的最新发展，该无人机可产生非常精细的鱼类育苗区地图。该技术使用简单，价格便宜，并且可以及时生成海洋区域的航拍照片。同时给出了有关航空照片采集（无人机和相机设置）的技术细节以及后期处理工作流程（使用从运动中构造算法和照片拼接的3D模型生成）。最后，通过应用现代的半自动图像分析和分类算法（最大似然，ECHO和基于对象的图像分析），我们比较了三个幼稚鱼苗圃区域专题图的结果，突出了该方法在制图和分类中的潜力。监测沿海海洋栖息地。 （C）2016 Elsevier Ltd.保留所有权利。

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