Chapter Using multispectral UAV imagery and ground truthing to assess the success of vegetation reinforcement in a coastal area – the case of Inwadar National Park, Malta
Ground-based methods of vegetation survey are slow and expensive, but recent technological developments have made UAVs (Unoccupied Aerial Vehicles or drones) accessible to consumer budgets, facilitating their use in vegetation monitoring. We propose a method for using UAVs to evaluate a vegetation r...
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| 格式: | Online |
| 語言: | 英语 |
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Firenze University Press
2025
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| 主題: | |
| 在線閱讀: | ONIX_20250801T173835_9791221505566_311 |
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| _version_ | 1869524036173692928 |
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| author | Camilleri, Leanne Lanfranco, Sandro |
| author_browse | Camilleri, Leanne Lanfranco, Sandro |
| author_facet | Camilleri, Leanne Lanfranco, Sandro |
| author_sort | Camilleri, Leanne |
| collection | Directory of Open Access Books |
| description | Ground-based methods of vegetation survey are slow and expensive, but recent technological developments have made UAVs (Unoccupied Aerial Vehicles or drones) accessible to consumer budgets, facilitating their use in vegetation monitoring. We propose a method for using UAVs to evaluate a vegetation reinforcement programme in a coastal area in Malta and compare its accuracy and cost-effectiveness with that of ground-based methods (including walkthrough-surveys and measurements of chlorophyll-a content). Multi-seasonal imaging of the site was captured using a DJI Phantom 4 drone equipped with sensors sensitive to visible, near infrared (NIR) and red edge (RE) light. These images were used to construct NDVIs of the site from which vegetation characteristics were deduced. Results suggest that UAVs provides a cost-effective way to map, quantify, and detect changes in vegetation cover which can enable assessment of physiological performance once a calibration procedure has been carried out. With an accuracy comparable to ground-based surveys, but quicker and cheaper, drone-based methods provide a viable and economically-attractive alternative to manual surveying methods. |
| format | Online |
| id | doab-20.500.12854ir-163394 |
| 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-1633942025-08-02T05:06:08Z Chapter Using multispectral UAV imagery and ground truthing to assess the success of vegetation reinforcement in a coastal area – the case of Inwadar National Park, Malta Camilleri, Leanne Lanfranco, Sandro UAVs vegetation monitoring reinforcement programme NDVIs cost-effectiveness Ground-based methods of vegetation survey are slow and expensive, but recent technological developments have made UAVs (Unoccupied Aerial Vehicles or drones) accessible to consumer budgets, facilitating their use in vegetation monitoring. We propose a method for using UAVs to evaluate a vegetation reinforcement programme in a coastal area in Malta and compare its accuracy and cost-effectiveness with that of ground-based methods (including walkthrough-surveys and measurements of chlorophyll-a content). Multi-seasonal imaging of the site was captured using a DJI Phantom 4 drone equipped with sensors sensitive to visible, near infrared (NIR) and red edge (RE) light. These images were used to construct NDVIs of the site from which vegetation characteristics were deduced. Results suggest that UAVs provides a cost-effective way to map, quantify, and detect changes in vegetation cover which can enable assessment of physiological performance once a calibration procedure has been carried out. With an accuracy comparable to ground-based surveys, but quicker and cheaper, drone-based methods provide a viable and economically-attractive alternative to manual surveying methods. 2025-08-02T05:06:07Z 2025-08-02T05:06:07Z 2025-08-01T16:00:12Z 2024 chapter ONIX_20250801T173835_9791221505566_311 2975-0288 https://library.oapen.org/handle/20.500.12657/104861 9791221505566 https://directory.doabooks.org/handle/20.500.12854/163394 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/20.500.12657/104861/1/43654.pdf Firenze University Press 10.36253/979-12-215-0556-6.09 10.36253/979-12-215-0556-6.09 2ec4474d-93b1-4cfa-b313-9c6019b51b1a 9791221505566 12 Florence open access |
| spellingShingle | UAVs vegetation monitoring reinforcement programme NDVIs cost-effectiveness Camilleri, Leanne Lanfranco, Sandro Chapter Using multispectral UAV imagery and ground truthing to assess the success of vegetation reinforcement in a coastal area – the case of Inwadar National Park, Malta |
| title | Chapter Using multispectral UAV imagery and ground truthing to assess the success of vegetation reinforcement in a coastal area – the case of Inwadar National Park, Malta |
| title_full | Chapter Using multispectral UAV imagery and ground truthing to assess the success of vegetation reinforcement in a coastal area – the case of Inwadar National Park, Malta |
| title_fullStr | Chapter Using multispectral UAV imagery and ground truthing to assess the success of vegetation reinforcement in a coastal area – the case of Inwadar National Park, Malta |
| title_full_unstemmed | Chapter Using multispectral UAV imagery and ground truthing to assess the success of vegetation reinforcement in a coastal area – the case of Inwadar National Park, Malta |
| title_short | Chapter Using multispectral UAV imagery and ground truthing to assess the success of vegetation reinforcement in a coastal area – the case of Inwadar National Park, Malta |
| title_sort | chapter using multispectral uav imagery and ground truthing to assess the success of vegetation reinforcement in a coastal area the case of inwadar national park malta |
| topic | UAVs vegetation monitoring reinforcement programme NDVIs cost-effectiveness |
| topic_facet | UAVs vegetation monitoring reinforcement programme NDVIs cost-effectiveness |
| url | ONIX_20250801T173835_9791221505566_311 |
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