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Winterl A, Richter S, Houstin A, Barracho T, Boureau M, Cornec C, Couet D, Cristofari R, Eiselt C, Fabry B, Krellenstein A, Mark C, Mainka A, Ménard D, Morinay J, Pottier S, Schloesing E, Le Bohec C, Zitterbart DP. Remote sensing of emperor penguin abundance and breeding success. Nat Commun 2024; 15:4419. [PMID: 38811565 PMCID: PMC11137044 DOI: 10.1038/s41467-024-48239-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 04/25/2024] [Indexed: 05/31/2024] Open
Abstract
Emperor penguins (Aptenodytes forsteri) are under increasing environmental pressure. Monitoring colony size and population trends of this Antarctic seabird relies primarily on satellite imagery recorded near the end of the breeding season, when light conditions levels are sufficient to capture images, but colony occupancy is highly variable. To correct population estimates for this variability, we develop a phenological model that can predict the number of breeding pairs and fledging chicks, as well as key phenological events such as arrival, hatching and foraging times, from as few as six data points from a single season. The ability to extrapolate occupancy from sparse data makes the model particularly useful for monitoring remotely sensed animal colonies where ground-based population estimates are rare or unavailable.
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Affiliation(s)
- Alexander Winterl
- Department of Physics, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany.
| | - Sebastian Richter
- Department of Physics, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Aymeric Houstin
- Department of Physics, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
- Department of Applied Ocean Physics and Engineering, Woods Hole Oceanographic Institution, Woods Hole, USA
- Université de Strasbourg, CNRS, IPHC UMR 7178, F-67000, Strasbourg, France
| | - Téo Barracho
- Université de Strasbourg, CNRS, IPHC UMR 7178, F-67000, Strasbourg, France
- CEFE, Université de Montpellier, CNRS, EPHE, IRD, Montpellier, France
- University of Moncton, Canada Research Chair in Polar and Boreal Ecology and Centre d'Études Nordiques, Department of Biology, Moncton, New Brunswick, Canada
| | - Matthieu Boureau
- Université de Strasbourg, CNRS, IPHC UMR 7178, F-67000, Strasbourg, France
| | - Clément Cornec
- Université de Strasbourg, CNRS, IPHC UMR 7178, F-67000, Strasbourg, France
- ENES Bioacoustics Research Laboratory, CRNL, CNRS, Inserm, University of Saint-Etienne, Saint-Etienne, France
| | - Douglas Couet
- Université de Strasbourg, CNRS, IPHC UMR 7178, F-67000, Strasbourg, France
| | - Robin Cristofari
- Université de Strasbourg, CNRS, IPHC UMR 7178, F-67000, Strasbourg, France
- Institute of Biotechnology, University of Helsinki, Helsinki, Finland
| | - Claire Eiselt
- Université de Strasbourg, CNRS, IPHC UMR 7178, F-67000, Strasbourg, France
| | - Ben Fabry
- Department of Physics, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | | | - Christoph Mark
- Department of Physics, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Astrid Mainka
- Department of Physics, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Delphine Ménard
- Université de Strasbourg, CNRS, IPHC UMR 7178, F-67000, Strasbourg, France
| | - Jennifer Morinay
- Université de Strasbourg, CNRS, IPHC UMR 7178, F-67000, Strasbourg, France
| | - Susie Pottier
- Université de Strasbourg, CNRS, IPHC UMR 7178, F-67000, Strasbourg, France
| | - Elodie Schloesing
- Université de Strasbourg, CNRS, IPHC UMR 7178, F-67000, Strasbourg, France
| | - Céline Le Bohec
- Université de Strasbourg, CNRS, IPHC UMR 7178, F-67000, Strasbourg, France.
- CEFE, Université de Montpellier, CNRS, EPHE, IRD, Montpellier, France.
- Centre Scientifique de Monaco, Département de Biologie Polaire, Monaco, Principality of Monaco.
| | - Daniel P Zitterbart
- Department of Physics, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany.
- Department of Applied Ocean Physics and Engineering, Woods Hole Oceanographic Institution, Woods Hole, USA.
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Neckel N, Fuchs N, Birnbaum G, Hutter N, Jutila A, Buth L, von Albedyll L, Ricker R, Haas C. Helicopter-borne RGB orthomosaics and photogrammetric digital elevation models from the MOSAiC Expedition. Sci Data 2023; 10:426. [PMID: 37400570 DOI: 10.1038/s41597-023-02318-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Accepted: 06/15/2023] [Indexed: 07/05/2023] Open
Abstract
The Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition took place between October 2019 and September 2020 giving the rare opportunity to monitor sea-ice properties over a full annual cycle. Here we present 24 high-resolution orthomosaics and 14 photogrammetric digital elevation models of the sea-ice surface around the icebreaker RV Polarstern between March and September 2020. The dataset is based on >34.000 images acquired by a helicopter-borne optical camera system with survey flights covering areas between 1.8 and 96.5 km2 around the vessel. Depending on the flight pattern and altitude of the helicopter, ground resolutions of the orthomosaics range between 0.03 and 0.5 m. By combining the photogrammetric products with contemporaneously acquired airborne laser scanner reflectance measurements selected orthomosaics could be corrected for cloud shadows which facilitates their usage for sea-ice and melt pond classification algorithms. The presented dataset is a valuable data source for the interdisciplinary MOSAiC community building a temporal and spatially resolved baseline to accompany various remote sensing and in situ research projects.
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Affiliation(s)
- Niklas Neckel
- Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, 27570, Germany.
| | - Niels Fuchs
- Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, 27570, Germany
- Institute of Oceanography, Center for Earth System Research and Sustainability (CEN), Universität Hamburg, Hamburg, Germany
| | - Gerit Birnbaum
- Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, 27570, Germany
| | - Nils Hutter
- Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, 27570, Germany
- Cooperative Institute for Climate, Ocean and Ecosystem Studies, University of Washington, Seattle, WA, 98105, USA
| | - Arttu Jutila
- Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, 27570, Germany
- Finnish Meteorological Institute, Helsinki, 00560, Finland
| | - Lena Buth
- Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, 27570, Germany
| | - Luisa von Albedyll
- Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, 27570, Germany
| | - Robert Ricker
- NORCE Norwegian Research Centre, Tromsø, 9019, Norway
| | - Christian Haas
- Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, 27570, Germany
- Institute of Environmental Physics, University of Bremen, Bremen, 28334, Germany
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Non-Destructive Fast Estimation of Tree Stem Height and Volume Using Image Processing. Symmetry (Basel) 2021. [DOI: 10.3390/sym13030374] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Measuring biometric tree characteristics to estimate the volume of wood in a forest area is a time consuming task. It is usually performed by a team of two or more people, who measure the diameter and height of several trees in sampling plots. The results are then extrapolated for the forest stand. The present paper describes a method which facilitates estimating tree biometric parameters using computational techniques. A camera takes two pictures of each sample tree, with an especially designed target placed close to the tree, to facilitate image processing and camera calibration steps. Taking advantage of the trees’ natural shape and assuming a symmetric stem, the diameter and height of the tree stems are estimated from the images and the volumes of the tree stems are calculated. Experimental trials show promising results, exhibiting errors similar to the traditional methods used currently, in the range of 10%, showing that the method is suitable for forest inventory.
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Winterl A, Richter S, Houstin A, Nesterova AP, Bonadonna F, Schneider W, Fabry B, Le Bohec C, Zitterbart DP. micrObs - A customizable time-lapse camera for ecological studies. HARDWAREX 2020; 8:e00134. [PMID: 35498253 PMCID: PMC9041239 DOI: 10.1016/j.ohx.2020.e00134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Revised: 08/13/2020] [Accepted: 08/15/2020] [Indexed: 06/14/2023]
Abstract
Camera traps for motion-triggered or continuous time-lapse recordings are readily available on the market. For demanding applications in ecology and environmental sciences, however, commercial systems often lack flexibility to freely adjust recording time intervals, suffer from mechanical component wear, and can be difficult to combine with auxiliary sensors such as GPS, weather stations, or light sensors. We present a robust time-lapse camera system that has been operating continuously since 2013 under the harsh climatic conditions of the Antarctic and Subantarctic regions. Thus far, we have recorded over one million images with individual cameras. The system consumes 122 mW of power in standby mode and captures up to 200,000 high-resolution (16 MPix) images without maintenance such as battery or image memory replacement. It offers time-lapse intervals between 2 s and 1 h, low-light or night-time power saving, and data logging capabilities for additional inputs such as GPS and weather data.
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Affiliation(s)
- Alexander Winterl
- Department of Physics, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
- Department of Applied Ocean Physics and Engineering, Woods Hole Oceanographic Institution, Woods Hole, USA
| | - Sebastian Richter
- Department of Physics, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
- Department of Applied Ocean Physics and Engineering, Woods Hole Oceanographic Institution, Woods Hole, USA
| | - Aymeric Houstin
- Centre Scientifique de Monaco, Département de Biologie Polaire, Monaco, Monaco
- Université de Strasbourg, CNRS, IPHC, UMR 7178, Strasbourg, France
| | - Anna P. Nesterova
- INRAE, CNRS, Université de Tours, PRC, UMR 7247, Nouzilly, France
- CEFE, Univ Montpellier, CNRS, Univ Paul Valéry Montpellier 3, EPHE, IRD, Montpellier, France
| | - Francesco Bonadonna
- CEFE, Univ Montpellier, CNRS, Univ Paul Valéry Montpellier 3, EPHE, IRD, Montpellier, France
| | - Werner Schneider
- Department of Physics, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Ben Fabry
- Department of Physics, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Céline Le Bohec
- Centre Scientifique de Monaco, Département de Biologie Polaire, Monaco, Monaco
- Université de Strasbourg, CNRS, IPHC, UMR 7178, Strasbourg, France
| | - Daniel P. Zitterbart
- Department of Physics, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
- Department of Applied Ocean Physics and Engineering, Woods Hole Oceanographic Institution, Woods Hole, USA
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