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Open AccessArticle

Mapping and Classification of Ecologically Sensitive Marine Habitats Using Unmanned Aerial Vehicle (UAV) Imagery and Object-Based Image Analysis (OBIA)

1
Department of Environmental Biology, University of Rome “La Sapienza”, V. le dell’Università 32, 00185 Rome, Italy
2
Laboratory of Experimental Ecology and Aquaculture, University of Rome “Tor Vergata”, Via della Ricerca Scientifica, 00133 Rome, Italy
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(9), 1331; https://doi.org/10.3390/rs10091331
Received: 13 June 2018 / Revised: 16 August 2018 / Accepted: 20 August 2018 / Published: 21 August 2018
Nowadays, emerging technologies, such as long-range transmitters, increasingly miniaturized components for positioning, and enhanced imaging sensors, have led to an upsurge in the availability of new ecological applications for remote sensing based on unmanned aerial vehicles (UAVs), sometimes referred to as “drones”. In fact, structure-from-motion (SfM) photogrammetry coupled with imagery acquired by UAVs offers a rapid and inexpensive tool to produce high-resolution orthomosaics, giving ecologists a new way for responsive, timely, and cost-effective monitoring of ecological processes. Here, we adopted a lightweight quadcopter as an aerial survey tool and object-based image analysis (OBIA) workflow to demonstrate the strength of such methods in producing very high spatial resolution maps of sensitive marine habitats. Therefore, three different coastal environments were mapped using the autonomous flight capability of a lightweight UAV equipped with a fully stabilized consumer-grade RGB digital camera. In particular we investigated a Posidonia oceanica seagrass meadow, a rocky coast with nurseries for juvenile fish, and two sandy areas showing biogenic reefs of Sabelleria alveolata. We adopted, for the first time, UAV-based raster thematic maps of these key coastal habitats, produced after OBIA classification, as a new method for fine-scale, low-cost, and time saving characterization of sensitive marine environments which may lead to a more effective and efficient monitoring and management of natural resources. View Full-Text
Keywords: unmanned aerial systems/vehicles (UAS/UAV); marine coastal habitats; mapping; object-based image analysis (OBIA); image classification; structure from Motion (SfM); aerial mapping; Mediterranean Sea unmanned aerial systems/vehicles (UAS/UAV); marine coastal habitats; mapping; object-based image analysis (OBIA); image classification; structure from Motion (SfM); aerial mapping; Mediterranean Sea
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MDPI and ACS Style

Ventura, D.; Bonifazi, A.; Gravina, M.F.; Belluscio, A.; Ardizzone, G. Mapping and Classification of Ecologically Sensitive Marine Habitats Using Unmanned Aerial Vehicle (UAV) Imagery and Object-Based Image Analysis (OBIA). Remote Sens. 2018, 10, 1331. https://doi.org/10.3390/rs10091331

AMA Style

Ventura D, Bonifazi A, Gravina MF, Belluscio A, Ardizzone G. Mapping and Classification of Ecologically Sensitive Marine Habitats Using Unmanned Aerial Vehicle (UAV) Imagery and Object-Based Image Analysis (OBIA). Remote Sensing. 2018; 10(9):1331. https://doi.org/10.3390/rs10091331

Chicago/Turabian Style

Ventura, Daniele; Bonifazi, Andrea; Gravina, Maria F.; Belluscio, Andrea; Ardizzone, Giandomenico. 2018. "Mapping and Classification of Ecologically Sensitive Marine Habitats Using Unmanned Aerial Vehicle (UAV) Imagery and Object-Based Image Analysis (OBIA)" Remote Sens. 10, no. 9: 1331. https://doi.org/10.3390/rs10091331

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