Chapter Mapping Yucca gloriosa in coastal dunes: evaluating the cost and time efficiency of photointerpretation, machine learning and field detection approaches
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, particu...
Bewaard in:
| Hoofdauteurs: | , , , , , |
|---|---|
| Formaat: | Online |
| Taal: | Engels |
| Gepubliceerd in: |
Firenze University Press
2025
|
| Onderwerpen: | |
| Online toegang: | ONIX_20250801T173835_9791221505566_266 |
| Tags: |
Geen labels, Wees de eerste die dit record labelt!
|
| _version_ | 1869518695960674304 |
|---|---|
| author | Cini, Elena Marzialetti, Flavio Paterni, Marco BERTON, ANDREA Acosta, Alicia T. R. CICCARELLI, DANIELA |
| author_browse | Acosta, Alicia T. R. BERTON, ANDREA CICCARELLI, DANIELA Cini, Elena Marzialetti, Flavio Paterni, Marco |
| author_facet | Cini, Elena Marzialetti, Flavio Paterni, Marco BERTON, ANDREA Acosta, Alicia T. R. CICCARELLI, DANIELA |
| author_sort | Cini, Elena |
| collection | Directory of Open Access Books |
| description | 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. |
| format | Online |
| id | doab-20.500.12854ir-163476 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | Firenze University Press |
| publisherStr | Firenze University Press |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1634762025-08-02T05:10:44Z Chapter Mapping Yucca gloriosa in coastal dunes: evaluating the cost and time efficiency of photointerpretation, machine learning and field detection approaches Cini, Elena Marzialetti, Flavio Paterni, Marco BERTON, ANDREA Acosta, Alicia T. R. CICCARELLI, DANIELA Alien plants Drones Monitoring RGB and multispectral Mapping 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. 2025-08-02T05:10:43Z 2025-08-02T05:10:43Z 2025-08-01T15:57:04Z 2024 chapter ONIX_20250801T173835_9791221505566_266 2975-0288 https://library.oapen.org/handle/20.500.12657/104816 9791221505566 https://directory.doabooks.org/handle/20.500.12854/163476 eng Monitoring of Mediterranean Coastal Areas: Problems and Measurement Techniques open access image/jpeg Attribution-NonCommercial-ShareAlike 4.0 International https://library.oapen.org/bitstream/20.500.12657/104816/1/43659.pdf Firenze University Press 10.36253/979-12-215-0556-6.14 10.36253/979-12-215-0556-6.14 2ec4474d-93b1-4cfa-b313-9c6019b51b1a 9791221505566 11 Florence open access |
| spellingShingle | Alien plants Drones Monitoring RGB and multispectral Mapping Cini, Elena Marzialetti, Flavio Paterni, Marco BERTON, ANDREA Acosta, Alicia T. R. CICCARELLI, DANIELA Chapter Mapping Yucca gloriosa in coastal dunes: evaluating the cost and time efficiency of photointerpretation, machine learning and field detection approaches |
| title | Chapter Mapping Yucca gloriosa in coastal dunes: evaluating the cost and time efficiency of photointerpretation, machine learning and field detection approaches |
| title_full | Chapter Mapping Yucca gloriosa in coastal dunes: evaluating the cost and time efficiency of photointerpretation, machine learning and field detection approaches |
| title_fullStr | Chapter Mapping Yucca gloriosa in coastal dunes: evaluating the cost and time efficiency of photointerpretation, machine learning and field detection approaches |
| title_full_unstemmed | Chapter Mapping Yucca gloriosa in coastal dunes: evaluating the cost and time efficiency of photointerpretation, machine learning and field detection approaches |
| title_short | Chapter Mapping Yucca gloriosa in coastal dunes: evaluating the cost and time efficiency of photointerpretation, machine learning and field detection approaches |
| title_sort | chapter mapping yucca gloriosa in coastal dunes evaluating the cost and time efficiency of photointerpretation machine learning and field detection approaches |
| topic | Alien plants Drones Monitoring RGB and multispectral Mapping |
| topic_facet | Alien plants Drones Monitoring RGB and multispectral Mapping |
| url | ONIX_20250801T173835_9791221505566_266 |
| work_keys_str_mv | AT cinielena chaptermappingyuccagloriosaincoastaldunesevaluatingthecostandtimeefficiencyofphotointerpretationmachinelearningandfielddetectionapproaches AT marzialettiflavio chaptermappingyuccagloriosaincoastaldunesevaluatingthecostandtimeefficiencyofphotointerpretationmachinelearningandfielddetectionapproaches AT paternimarco chaptermappingyuccagloriosaincoastaldunesevaluatingthecostandtimeefficiencyofphotointerpretationmachinelearningandfielddetectionapproaches AT bertonandrea chaptermappingyuccagloriosaincoastaldunesevaluatingthecostandtimeefficiencyofphotointerpretationmachinelearningandfielddetectionapproaches AT acostaaliciatr chaptermappingyuccagloriosaincoastaldunesevaluatingthecostandtimeefficiencyofphotointerpretationmachinelearningandfielddetectionapproaches AT ciccarellidaniela chaptermappingyuccagloriosaincoastaldunesevaluatingthecostandtimeefficiencyofphotointerpretationmachinelearningandfielddetectionapproaches |