Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
7.9
5.0
Journals
Remote Sensing
Special Issues
Remote Sensing Applications in Marine Mammal Research
remotesensing-logo
Submit to Remote Sensing Review for Remote Sensing Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Remote Sensing Applications in Marine Mammal Research

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Ocean Remote Sensing".

Deadline for manuscript submissions: closed (31 October 2021) | Viewed by 14366

Special Issue Editors

Dr. Barbara Bollard

E-Mail Website
Guest Editor
Drone Lab, Auckland University of Technology, 55 Wellesley Street East, Auckland CBD, Auckland 1010, New Zealand
Interests: conservation planning; unmanned aerial vehicles; multi and hyperspectral imaging; marine mammal; habitat modelling; object recognition; spatial ecology; multitemporal remote sensing
Special Issues, Collections and Topics in MDPI journals
Dr. Lorenzo Fiori

E-Mail
Guest Editor
Scientific & Technical Director, Terra Azul Ltd – Marina de Vila Franca do Campo, Loja 4, 4680-187 Vila Franca do Campo, São Miguel Island, Azores, Portugal
Interests: behavioral ecology; cetaceans; unmanned aerial vehicles; drones; swim-with-whales; tourism impact

Special Issue Information

Dear Colleagues,

Remote sensing from the air and space has greatly advanced our understanding of the biotic and abiotic marine environment. This Special Issue will address recent advances in remote sensing applications in marine mammal research. Submissions that describe new insights into unresolved problems that are enabled by observations at novel scales of space and time are particularly encouraged, as are submissions that demonstrate observations in novel environments. Manuscripts are welcome from unmanned aerial systems as well as spaceborne observations on a range of topics such as:

  • Tracking applications to gain non-invasive insights into animal movements;
  • Novel sensors and sensor networks;
  • Behavioral and physiological responses to the changes in the environment;
  • Multitemporal remote sensing;
  • Characterization of marine habitats in relation to marine mammal distribution;

Targeted acquisitions to take advantage of natural experiments such as natural disasters or changing sea level.

Dr. Barbara Bollard
Dr. Lorenzo Fiori
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • marine mammals
  • tracking
  • sensors
  • animal behavior and ecology
  • multitemporal remote sensing
  • satellite and drone remote sensing

Published Papers (3 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

17 pages, 2188 KiB  
Article
Weakly Supervised Detection of Marine Animals in High Resolution Aerial Images
by Paul Berg, Deise Santana Maia, Minh-Tan Pham and Sébastien Lefèvre
Remote Sens. 2022, 14(2), 339; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14020339 - 12 Jan 2022
Cited by 11 | Viewed by 4171
Abstract
Human activities in the sea, such as intensive fishing and exploitation of offshore wind farms, may impact negatively on the marine mega fauna. As an attempt to control such impacts, surveying, and tracking of marine animals are often performed on the sites where [...] Read more.
Human activities in the sea, such as intensive fishing and exploitation of offshore wind farms, may impact negatively on the marine mega fauna. As an attempt to control such impacts, surveying, and tracking of marine animals are often performed on the sites where those activities take place. Nowadays, thank to high resolution cameras and to the development of machine learning techniques, tracking of wild animals can be performed remotely and the analysis of the acquired images can be automatized using state-of-the-art object detection models. However, most state-of-the-art detection methods require lots of annotated data to provide satisfactory results. Since analyzing thousands of images acquired during a flight survey can be a cumbersome and time consuming task, we focus in this article on the weakly supervised detection of marine animals. We propose a modification of the patch distribution modeling method (PaDiM), which is currently one of the state-of-the-art approaches for anomaly detection and localization for visual industrial inspection. In order to show its effectiveness and suitability for marine animal detection, we conduct a comparative evaluation of the proposed method against the original version, as well as other state-of-the-art approaches on two high-resolution marine animal image datasets. On both tested datasets, the proposed method yielded better F1 and recall scores (75% recall/41% precision, and 57% recall/60% precision, respectively) when trained on images known to contain no object of interest. This shows a great potential of the proposed approach to speed up the marine animal discovery in new flight surveys. Additionally, such a method could be adopted for bounding box proposals to perform faster and cheaper annotation within a fully-supervised detection framework. Full article
(This article belongs to the Special Issue Remote Sensing Applications in Marine Mammal Research)
►▼ Show Figures

Graphical abstract

18 pages, 3204 KiB  
Article
Feasibility of Using Small UAVs to Derive Morphometric Measurements of Australian Snubfin (Orcaella heinsohni) and Humpback (Sousa sahulensis) Dolphins
by Anna I. Christie, Andrew P. Colefax and Daniele Cagnazzi
Remote Sens. 2022, 14(1), 21; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14010021 - 22 Dec 2021
Cited by 8 | Viewed by 3479
Abstract
Analysis of animal morphometrics can provide vital information regarding population dynamics, structure, and body condition of cetaceans. Unmanned aerial vehicles (UAVs) have become the primary tool to collect morphometric measurements on whales, whereas on free ranging small dolphins, have not yet been applied. [...] Read more.
Analysis of animal morphometrics can provide vital information regarding population dynamics, structure, and body condition of cetaceans. Unmanned aerial vehicles (UAVs) have become the primary tool to collect morphometric measurements on whales, whereas on free ranging small dolphins, have not yet been applied. This study assesses the feasibility of obtaining reliable body morphometrics from Australian snubfin (Orcaella heinsohni) and humpback dolphins (Sousa sahulensis) using images collected from UAVs. Specifically, using a dolphin replica of known size, we tested the effect of the altitude of the UAV and the position of the animal within the image frame on the accuracy of length estimates. Using linear mixed models, we further assessed the precision of the total length estimates of humpback and snubfin dolphins. The precision of length estimates on the replica increased by ~2% when images were sampled at 45–60 m compared with 15–30 m. However, the precision of total length estimates on dolphins was significantly influenced only by the degree of arch and edge certainty. Overall, we obtained total length estimates with a precision of ~3% and consistent with published data. This study demonstrates the reliability of using UAV based images to obtain morphometrics of small dolphin species, such as snubfin and humpback dolphins. Full article
(This article belongs to the Special Issue Remote Sensing Applications in Marine Mammal Research)
►▼ Show Figures

Figure 1

18 pages, 5753 KiB  
Article
Evaluation of Satellite Imagery for Monitoring Pacific Walruses at a Large Coastal Haulout
by Anthony S. Fischbach and David C. Douglas
Remote Sens. 2021, 13(21), 4266; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13214266 - 23 Oct 2021
Cited by 6 | Viewed by 5352
Abstract
Pacific walruses (Odobenus rosmarus divergens) are using coastal haulouts in the Chukchi Sea more often and in larger numbers to rest between foraging bouts in late summer and autumn in recent years, because climate warming has reduced availability of sea ice [...] Read more.
Pacific walruses (Odobenus rosmarus divergens) are using coastal haulouts in the Chukchi Sea more often and in larger numbers to rest between foraging bouts in late summer and autumn in recent years, because climate warming has reduced availability of sea ice that historically had provided resting platforms near their preferred benthic feeding grounds. With greater numbers of walruses hauling out in large aggregations, new opportunities are presented for monitoring the population. Here we evaluate different types of satellite imagery for detecting and delineating the peripheries of walrus aggregations at a commonly used haulout near Point Lay, Alaska, in 2018–2020. We evaluated optical and radar imagery ranging in pixel resolutions from 40 m to ~1 m: specifically, optical imagery from Landsat, Sentinel-2, Planet Labs, and DigitalGlobe, and synthetic aperture radar (SAR) imagery from Sentinel-1 and TerraSAR-X. Three observers independently examined satellite images to detect walrus aggregations and digitized their peripheries using visual interpretation. We compared interpretations between observers and to high-resolution (~2 cm) ortho-corrected imagery collected by a small unoccupied aerial system (UAS). Roughly two-thirds of the time, clouds precluded clear optical views of the study area from satellite. SAR was unaffected by clouds (and darkness) and provided unambiguous signatures of walrus aggregations at the Point Lay haulout. Among imagery types with 4–10 m resolution, observers unanimously agreed on all detections of walruses, and attained an average 65% overlap (sd 12.0, n 100) in their delineations of aggregation boundaries. For imagery with ~1 m resolution, overlap agreement was higher (mean 85%, sd 3.0, n 11). We found that optical satellite sensors with moderate resolution and high revisitation rates, such as PlanetScope and Sentinel-2, demonstrated robust and repeatable qualities for monitoring walrus haulouts, but temporal gaps between observations due to clouds were common. SAR imagery also demonstrated robust capabilities for monitoring the Point Lay haulout, but more research is needed to evaluate SAR at haulouts with more complex local terrain and beach substrates. Full article
(This article belongs to the Special Issue Remote Sensing Applications in Marine Mammal Research)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-3
Back to TopTop