Literature DB >> 33535463

The Potential of Satellite Imagery for Surveying Whales.

Caroline Höschle1, Hannah C Cubaynes2,3, Penny J Clarke2,4, Grant Humphries5, Alex Borowicz6.   

Abstract

The emergence of very high-resolution (VHR) satellite imagery (less than 1 m spatial resolution) is creating new opportunities within the fields of ecology and conservation biology. The advancement of sub-meter resolution imagery has provided greater confidence in the detection and identification of features on the ground, broadening the realm of possible research questions. To date, VHR imagery studies have largely focused on terrestrial environments; however, there has been incremental progress in the last two decades for using this technology to detect cetaceans. With advances in computational power and sensor resolution, the feasibility of broad-scale VHR ocean surveys using VHR satellite imagery with automated detection and classification processes has increased. Initial attempts at automated surveys are showing promising results, but further development is necessary to ensure reliability. Here we discuss the future directions in which VHR satellite imagery might be used to address urgent questions in whale conservation. We highlight the current challenges to automated detection and to extending the use of this technology to all oceans and various whale species. To achieve basin-scale marine surveys, currently not feasible with any traditional surveying methods (including boat-based and aerial surveys), future research requires a collaborative effort between biology, computation science, and engineering to overcome the present challenges to this platform's use.

Entities:  

Keywords:  great whale species; remote sensing; very high-resolution (VHR) satellite imagery

Mesh:

Year:  2021        PMID: 33535463      PMCID: PMC7867100          DOI: 10.3390/s21030963

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  12 in total

1.  Feasibility of using high-resolution satellite imagery to assess vertebrate wildlife populations.

Authors:  Michelle A LaRue; Seth Stapleton; Morgan Anderson
Journal:  Conserv Biol       Date:  2016-10-26       Impact factor: 6.560

2.  An unexpectedly large count of trees in the West African Sahara and Sahel.

Authors:  Martin Brandt; Compton J Tucker; Ankit Kariryaa; Kjeld Rasmussen; Christin Abel; Jennifer Small; Jerome Chave; Laura Vang Rasmussen; Pierre Hiernaux; Abdoul Aziz Diouf; Laurent Kergoat; Ole Mertz; Christian Igel; Fabian Gieseke; Johannes Schöning; Sizhuo Li; Katherine Melocik; Jesse Meyer; Scott Sinno; Eric Romero; Erin Glennie; Amandine Montagu; Morgane Dendoncker; Rasmus Fensholt
Journal:  Nature       Date:  2020-10-14       Impact factor: 49.962

3.  Current and future patterns of global marine mammal biodiversity.

Authors:  Kristin Kaschner; Derek P Tittensor; Jonathan Ready; Tim Gerrodette; Boris Worm
Journal:  PLoS One       Date:  2011-05-23       Impact factor: 3.240

4.  Spotting East African mammals in open savannah from space.

Authors:  Zheng Yang; Tiejun Wang; Andrew K Skidmore; Jan de Leeuw; Mohammed Y Said; Jim Freer
Journal:  PLoS One       Date:  2014-12-31       Impact factor: 3.240

5.  Extrapolating cetacean densities to quantitatively assess human impacts on populations in the high seas.

Authors:  Laura Mannocci; Jason J Roberts; David L Miller; Patrick N Halpin
Journal:  Conserv Biol       Date:  2017-04-28       Impact factor: 6.560

6.  Google Haul Out: Earth Observation Imagery and Digital Aerial Surveys in Coastal Wildlife Management and Abundance Estimation.

Authors:  Jerry H Moxley; Andrea Bogomolni; Mike O Hammill; Kathleen M T Moore; Michael J Polito; Lisa Sette; W Brian Sharp; Gordon T Waring; James R Gilbert; Patrick N Halpin; David W Johnston
Journal:  Bioscience       Date:  2017-06-14       Impact factor: 8.589

7.  Aerial-trained deep learning networks for surveying cetaceans from satellite imagery.

Authors:  Alex Borowicz; Hieu Le; Grant Humphries; Georg Nehls; Caroline Höschle; Vladislav Kosarev; Heather J Lynch
Journal:  PLoS One       Date:  2019-10-01       Impact factor: 3.240

8.  Global coverage of cetacean line-transect surveys: status quo, data gaps and future challenges.

Authors:  Kristin Kaschner; Nicola J Quick; Rebecca Jewell; Rob Williams; Catriona M Harris
Journal:  PLoS One       Date:  2012-09-12       Impact factor: 3.240

9.  Whale counting in satellite and aerial images with deep learning.

Authors:  Emilio Guirado; Siham Tabik; Marga L Rivas; Domingo Alcaraz-Segura; Francisco Herrera
Journal:  Sci Rep       Date:  2019-10-03       Impact factor: 4.379

10.  A comparison of baleen whale density estimates derived from overlapping satellite imagery and a shipborne survey.

Authors:  C C G Bamford; N Kelly; L Dalla Rosa; D E Cade; P T Fretwell; P N Trathan; H C Cubaynes; A F C Mesquita; L Gerrish; A S Friedlaender; J A Jackson
Journal:  Sci Rep       Date:  2020-07-31       Impact factor: 4.379

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  3 in total

1.  Whales from space dataset, an annotated satellite image dataset of whales for training machine learning models.

Authors:  Hannah C Cubaynes; Peter T Fretwell
Journal:  Sci Data       Date:  2022-05-27       Impact factor: 8.501

2.  Remote sensing techniques for automated marine mammals detection: a review of methods and current challenges.

Authors:  Esteban N Rodofili; Vincent Lecours; Michelle LaRue
Journal:  PeerJ       Date:  2022-06-20       Impact factor: 3.061

3.  Mapping Arctic cetaceans from space: A case study for beluga and narwhal.

Authors:  Bertrand Charry; Emily Tissier; John Iacozza; Marianne Marcoux; Cortney A Watt
Journal:  PLoS One       Date:  2021-08-04       Impact factor: 3.240

  3 in total

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