A low-cost drone based application for identifying and mapping of coastal fish nursery grounds. (20th March 2016)

• Record Type: Journal Article
• Authors: Ventura, Daniele; Bruno, Michele; Jona Lasinio, Giovanna; Belluscio, Andrea; Ardizzone, Giandomenico
• Is Part Of: Estuarine, coastal and shelf science. Volume 171(2016)
• Page Start: 85
• Page End: 98
• Publication Date: 2016-03-20
• Subjects: Drone -- Nursery -- Mapping -- Image classification -- Aerial imagery -- Mediterranean Sea -- Central Tyrrhenian Sea -- Giglio Island; Estuarine oceanography -- Periodicals; Coasts -- Periodicals; Estuarine biology -- Periodicals; Seashore biology -- Periodicals; Coasts; Estuarine biology; Estuarine oceanography; Seashore biology; Periodicals; 551.461805
• DOI: 10.1016/j.ecss.2016.01.030
• Languages: English
• ISSNs: 0272-7714

Abstract

Abstract: 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. Highlights: A new application of a small unmanned aerial platform is proposed. The methodology used for aerial acquisition of ultra-high imagery of a nursery area is described. We examine three different methods of image analysis and automatic classification of seabed. A cost-effective and time-saving method may become a key tool in sensitive coastal habitats monitoring.