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1.
Sensors (Basel) ; 21(3)2021 Feb 01.
Artigo em Inglês | MEDLINE | ID: mdl-33535463

RESUMO

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.


Assuntos
Imagens de Satélites , Baleias , Animais , Reprodutibilidade dos Testes
2.
Ann Rev Mar Sci ; 2024 Aug 19.
Artigo em Inglês | MEDLINE | ID: mdl-39159203

RESUMO

Advancements in space-based ocean observation and computational data processing techniques have demonstrated transformative value for managing living resources, biodiversity, and ecosystems of the ocean. We synthesize advancements in leveraging satellite-derived insights to better understand and manage fishing, an emerging revolution of marine industrialization, ocean hazards, sea surface dynamics, benthic ecosystems, wildlife via electronic tracking, and direct observations of ocean megafauna. We consider how diverse space-based data sources can be better coupled to modernize and improve ocean management. We also highlight examples of how data from space can be developed into tools that can aid marine decision-makers managing subjects from whales to algae. Thoughtful and prospective engagement with such technologies from those inside and outside the marine remote sensing community is, however, essential to ensure that these tools meet their full potential to strengthen the effectiveness of ocean management.

3.
Sci Data ; 9(1): 245, 2022 05 27.
Artigo em Inglês | MEDLINE | ID: mdl-35624202

RESUMO

Monitoring whales in remote areas is important for their conservation; however, using traditional survey platforms (boat and plane) in such regions is logistically difficult. The use of very high-resolution satellite imagery to survey whales, particularly in remote locations, is gaining interest and momentum. However, the development of this emerging technology relies on accurate automated systems to detect whales, which are currently lacking. Such detection systems require access to an open source library containing examples of whales annotated in satellite images to train and test automatic detection systems. Here we present a dataset of 633 annotated whale objects, created by surveying 6,300 km2 of satellite imagery captured by various very high-resolution satellites (i.e. WorldView-3, WorldView-2, GeoEye-1 and Quickbird-2) in various regions across the globe (e.g. Argentina, New Zealand, South Africa, United States, Mexico). The dataset covers four different species: southern right whale (Eubalaena glacialis), humpback whale (Megaptera novaeangliae), fin whale (Balaenoptera physalus), and grey whale (Eschrichtius robustus).


Assuntos
Baleia Comum , Jubarte , Animais , Cetáceos , Aprendizado de Máquina , Imagens de Satélites , Estados Unidos
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