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

Ventura, Daniele; Bonifazi, Andrea; Gravina, Maria Flavia; Belluscio, Andrea; Ardizzone, Giandomenico

doi:10.3390/rs10091331

Submit to this Journal Review for this Journal Edit a Special Issue

Article Menu

...

Open AccessArticle

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

^1,*

²,

²,

¹ and

Giandomenico Ardizzone

Department of Environmental Biology, University of Rome “La Sapienza”, V. le dell’Università 32, 00185 Rome, Italy

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

(This article belongs to the Special Issue Remote Sensing in Coastal Zone Monitoring and Management—How Can Remote Sensing Challenge the Broad Spectrum of Temporal and Spatial Scales in Coastal Zone Dynamic?)

View Full-Text Download PDF

Browse Figures

Citation Export

Abstract

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

▼ Show Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Supplementary Material

Supplementary File 1:
Supplementary (ZIP, 1842 KiB)

Share and Cite

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

Find Other Styles

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Metrics

Abstract views Pdf views Html views

Article Menu

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

Abstract

Supplementary Material

Share and Cite

Article Metrics

Article Access Statistics

Article Access Map by Country/Region

Further Information

Guidelines

MDPI Initiatives

Follow MDPI