Towards the Computational Assessment of the Conservation Status of a Habitat
Abstract
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.
Cite
Text
Manh et al. "Towards the Computational Assessment of the Conservation Status of a Habitat." European Conference on Computer Vision Workshops, 2022. doi:10.1007/978-3-031-25075-0_51Markdown
[Manh et al. "Towards the Computational Assessment of the Conservation Status of a Habitat." European Conference on Computer Vision Workshops, 2022.](https://mlanthology.org/eccvw/2022/manh2022eccvw-computational/) doi:10.1007/978-3-031-25075-0_51BibTeX
@inproceedings{manh2022eccvw-computational,
title = {{Towards the Computational Assessment of the Conservation Status of a Habitat}},
author = {Manh, X. Huy and Gigante, Daniela and Angiolini, Claudia and Bagella, Simonetta and Caccianiga, Marco and Angelini, Franco and Garabini, Manolo and Remagnino, Paolo},
booktitle = {European Conference on Computer Vision Workshops},
year = {2022},
pages = {751-764},
doi = {10.1007/978-3-031-25075-0_51},
url = {https://mlanthology.org/eccvw/2022/manh2022eccvw-computational/}
}