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Cost-effective environmental management tools: Coastal monitoring using aerial and submersible drones

Reference number
Coordinator Göteborgs Universitet - Institutionen för Marina Vetenskaper
Funding from Vinnova SEK 1 100 000
Project duration May 2018 - June 2019
Status Completed
Venture Drones
Call Drones of the future - Drones for citizens and community

Purpose and goal

The purpose of the project has been achieved. A new method to use drones for coastal mapping was explored, showing that drones are a cost-efficient tool for mapping coastal shallow areas. Using drone images, it was possible to identify shallow aquatic species such as eelgrass (Zostera marina), Ruppia maritima, macroalgae, etc. This method can be used for regular monitoring of coastal bays to identify environmental impacts caused by human activities or climate change.

Expected effects and result

The coastal maps generated with drone images had an accuracy of 82%, while the accuracy of of satellite images from Sentinel-2 had an average accuracy of 63%. The satellite accuracy varied per locations (55-80%) while drone accuracy was similar in all locations. Using pre-programmed automated drone flights to collected images was fast, (average 16min/site), whereas image processing and classification was more time consuming (3h/site), but this will improve as the technique develops.

Planned approach and implementation

The new method using small, inexpensive drones to obtain high-resolution aerial images (3-5 cm per pixel) showed very promising results. For mapping and monitoring of small-scale changes in areal distribution of vegetation within sites, a combination of remote sensing with drones and drop-video is recommended while for monitoring of large-scale changes in whole regions, satellite image analysis is recommended. Using the results from the small-scale monitoring with drones and the satellite images could improve the accuracy of the large-scale monitoring.

External links

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 8 January 2019

Reference number 2018-01745

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