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Towards the Computational Assessment of the Conservation Status of a Habitat

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Computer Vision – ECCV 2022 Workshops (ECCV 2022)

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We propose methods to automatically assess the conservation status of a habitat. Habitat monitoring is usually performed by botanists and other specialists in their field work, searching for the presence or lack of typical plant species (Evans D, Arvela M (2011) Assessment and reporting under Article 17 of the Habitats Directive. Explanatory Notes & Guidelines for the period 2007–2012. European Commission, Brussels.) and other elements (such as vegetation cover) that might indicate the degradation of a habitat. We present preliminary work that makes use of a robotic platform employed to help botanists in their tasks. Three methods are proposed. First a color segmentation method, to detect the amount of green in a given area, a detection method to automatically detect the presence of a given plant, and finally a classification method used to identify a plant in a single image.

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    Grant agreement No. 101016970, European Union’s Horizon 2020 Research and Innovation Programme - ICT-47-2020.

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    Douglas Evans and Marita Arvela. Assessment and reporting under article 17 of the habitats directive. explanatory notes & guidelines for the period 2007–2012. European Commission, Brussels, 2011.

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    Habitats Directive. Council directive 92/43/EEC of 21 may 1992 on the conservation of natural habitats and of wild fauna and flora. Official Journal of the European Union, 206:7–50, 1992.

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This research is supported by Grant Agreement No. 10101697, under the European Union’s Horizon2020 Research and Innovation Programme.

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Correspondence to Paolo Remagnino .

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Manh, X.H. et al. (2023). Towards the Computational Assessment of the Conservation Status of a Habitat. In: Karlinsky, L., Michaeli, T., Nishino, K. (eds) Computer Vision – ECCV 2022 Workshops. ECCV 2022. Lecture Notes in Computer Science, vol 13806. Springer, Cham.

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