Biological invasions threaten biodiversity and cause significant economic and ecological costs. Effective management of invasive species is crucial, as highlighted by the European Community's Regulation 1143/2014 on Invasive Alien Species (IAS). This study focuses on coastal dune ecosystems, particularly assessing the time and cost-effectiveness of three monitoring methods for detecting and mapping alien plants: photointerpretation, machine learning classification, and field monitoring. Yucca gloriosa L., an invasive species in Regional Park of Migliarino-San Rossore-Massaciuccoli (Tuscany, Italy), served as the target species. Using RGB DJI Phantom 4 Pro v. 2.0 and DJI P4 Multispectral drones, images were analyzed via photointerpretation and machine learning. Photointerpretation, though precise, was time-consuming and subjective. Machine learning minimized human effort but required extensive computing. Field monitoring produced accurate maps but was labor-intensive and limited by accessibility issues. This study concludes that UAV-based monitoring of Y. gloriosa is optimal for balancing cost and time efficiency in coastal dune ecosystems.
Roma Tre University, Italy - ORCID: 0009-0003-9396-1352
University of Sassari, Italy - ORCID: 0000-0001-5661-4683
Clinical Physiology Institute CNR, Italy - ORCID: 0000-0002-9799-7059
Clinical Physiology Institute CNR, Italy - ORCID: 0000-0002-8798-9469
Roma Tre University, Italy - ORCID: 0000-0001-6572-3187
University of Pisa, Italy - ORCID: 0000-0001-9715-9779
Chapter Title
Mapping Yucca gloriosa in coastal dunes: evaluating the cost and time efficiency of photointerpretation, machine learning and field detection approaches
Authors
Elena Cini, Flavio Marzialetti, Marco Paterni, Andrea Berton, Alicia Teresa Rosario Acosta, Daniela Ciccarelli
Language
Italian
DOI
10.36253/979-12-215-0556-6.14
Peer Reviewed
Publication Year
2024
Copyright Information
© 2024 Author(s)
Content License
Metadata License
Book Title
Tenth International Symposium Monitoring of Mediterranean Coastal Areas: Problems and Measurement Techniques
Book Subtitle
Livorno (Italy) 11th-13th June 2024
Editors
Laura Bonora, Marcantonio Catelani, Matteo De Vincenzi, Giorgio Matteucci
Peer Reviewed
Publication Year
2024
Copyright Information
© 2024 Author(s)
Content License
Metadata License
Publisher Name
Firenze University Press
DOI
10.36253/979-12-215-0556-6
eISBN (pdf)
979-12-215-0556-6
eISBN (xml)
979-12-215-0557-3
Series Title
Monitoring of Mediterranean Coastal Areas: Problems and Measurement Techniques
Series E-ISSN
2975-0288