Assessing the effectiveness of UAV data for accurate coastal dune habitat mapping

ABSTRACT

Coastal dunes are considered some of the most threatened and vulnerable habitats in the European Union. Mapping the spatial distribution of these habitats is an essential task for their conservation. Advances in Unoccupied Aerial Vehicles (UAVs) facilitate the flexible acquisition of high-resolution imagery for identifying detailed spatial distributions of habitats within dune systems. This study aimed to assess the effectiveness of UAV remote sensing for mapping these habitat types. Specifically, we determined the impact of temporally acquired UAV-derived spectral and topographic information on classification accuracy. The work combined the multi-temporal UAV imagery with field observation data and used the Random Forest machine learning algorithm to classify dune habitats. Results showed that using multi-temporal UAV imagery increased classification accuracy compared to using uni-temporal UAV imagery (92.37% vs. 84.09%, respectively). Also, including topographic information consistently improved accuracy, regardless of the number of image sets used (the highest accuracy increased from 84.81% to 92.57% for a uni-temporal model). Temporal analyses showed that the data acquired in the middle period of the growing season were better than those acquired in the early or late periods. The methodology presented here demonstrates the potential of using UAV data for detailed mapping and monitoring of habitat types.

KEYWORDS:

• UAV
• coastal dunes
• EU Habitats Directive
• Random Forest
• multi-temporal
• habitat mapping

Acknowledgments

The presented work in this paper is part of the Habitat Mapping, Monitoring, and Assessment using High-Resolution Imagery (iHabiMap) project. This project is funded under the EPA Research Programme 2014-2020 (project code 2018-NC-LS-4). The EPA Research Programme is a Government of Ireland initiative funded by the Department of the Environment, Climate and Communications. The authors would also like to thank Dr Rory Hodd for his assistance with the ecological field surveys, Dr Eugene Farrell (National University in Galway) and the Magharees Community Group for their support during the field surveys, and the anonymous reviewers for their valuable comments and suggestions to improve the manuscript.

Disclosure statement

No potential conflict of interest was reported by the authors.

Data Availability Statement

The data supporting this study’s findings are available from the corresponding author, Charmaine Cruz ([email protected]), upon reasonable request.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/22797254.2023.2191870

Additional information

Funding

The work was supported by the Environmental Protection Agency [Project number: 2018-NC-LS-4]