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Citizen Science and Machine Learning for Research and Nature Conservation: The Case of Eurasian Lynx, Free-Ranging Rodents and Insects

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Digital Interaction and Machine Intelligence (MIDI 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 1076))

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Abstract

Technology is increasingly used in Nature Reserves and National Parks around the world to support conservation efforts. Endangered species, such as the Eurasian Lynx (Lynx lynx), are monitored by a network of automatic photo traps. Yet, this method produces vast amounts of data, which needs to be prepared, analyzed and interpreted. Therefore, researchers working in this area increasingly need support to process this incoming information. One opportunity is to seek support from volunteer Citizen Scientists who can help label the data, however, it is challenging to retain their interest. Another way is to automate the process with image recognition using convolutional neural networks. During the panel, we will discuss considerations related to nature research and conservation as well as opportunities for the use of Citizen Science and Machine Learning to expedite the process of data preparation, labelling and analysis.

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Notes

  1. 1.

    During our citizen science workshops with older adults we have shown a series of video recordings depicting photo trap field work in a Lynx conservation project filmed by J. Loch to see whether they would constitute an attractive edutainment reward.

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Acknowledgements

The Case of Eurasian Lynx research was funded by the Priority Research Area BioS under the program Excellence Initiative - Research University at the Jagiellonian University in Krakow.

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Authors and Affiliations

  1. XR Center, Polish-Japanese Academy of Information Technology, Warsaw, Poland

    Kinga Skorupska, Maciej Grzeszczuk, Piotr Gago, Jagoda Lazarek & Wiesław Kopeć

  2. Institute of Psychology, Polish Academy of Sciences, Warsaw, Poland

    Rafał Stryjek

  3. Institute of Environmental Sciences, Faculty of Biology, Jagiellonian University, Kraków, Poland

    Izabela Wierzbowska

  4. National Information Processing Institute, Warsaw, Poland

    Jarosław Kowalski

  5. Faculty of Biology, University of Warsaw, Warsaw, Poland

    Piotr Bebas

  6. Geografia Malownicza, Warsaw, Poland

    Maciej Krzywicki

Authors
  1. Kinga Skorupska
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  2. Rafał Stryjek
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  3. Izabela Wierzbowska
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  4. Piotr Bebas
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  5. Maciej Grzeszczuk
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  6. Piotr Gago
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  7. Jarosław Kowalski
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  8. Maciej Krzywicki
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  9. Jagoda Lazarek
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  10. Wiesław Kopeć
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Corresponding author

Correspondence to Kinga Skorupska .

Editor information

Editors and Affiliations

  1. National Research Institute, National Information Processing Institut, Warszaw, Poland

    Cezary Biele

  2. Polish Academy of Sciences, Systems Research Institute, Warsaw, Poland

    Janusz Kacprzyk

  3. Polish-Japanese Academy of Information Technology, Warsaw, Poland

    Wiesław Kopeć

  4. Mechatronics, Warsaw University of Technology, Warsaw, Poland

    Jakub Możaryn

  5. Polish Academy of Sciences, Systems Research Institute, Warsaw, Poland

    Jan W. Owsiński

  6. Institute of Applied Computer Science, Faculty of Electrical, Electronic, Computer and Control Engineering, Łódż University of Technology, LODZ, Poland

    Andrzej Romanowski

  7. Department of Applied Informatics in Management, Faculty of Management and Economics, Gdańsk University of Technology, Gdańsk, Poland

    Marcin Sikorski

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Skorupska, K. et al. (2024). Citizen Science and Machine Learning for Research and Nature Conservation: The Case of Eurasian Lynx, Free-Ranging Rodents and Insects. In: Biele, C., et al. Digital Interaction and Machine Intelligence. MIDI 2023. Lecture Notes in Networks and Systems, vol 1076. Springer, Cham. https://doi.org/10.1007/978-3-031-66594-3_37

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