Overcoming the UAS limitations in the coastal environment for accurate habitat mapping

Unmanned Aerial Systems (UAS) have been recently used as a close-range remote sensing tool, providing high spatial and temporal resolutions compared to other remote sensing methods. Their abilities have constantly increased their use in many environmental studies with very satisfactory results. However, the acquisition of reliable information for accurate marine habitat mapping is still challenging due to the plethora of parameters (mostly environmental conditions) that affect the accurate depiction and delineation of habitats in aerial imagery. In this study we are proposing an efficient methodology for marine habitat mapping that includes three main steps: i) data acquisition and processing of UAS imagery, ii) Object-Based Image Analysis (OBIA) and classification of marine habitats, iii) image quality and accuracy assessment of high-resolution thematic maps. This methodology overcomes the UAS limitations in the coastal environment by identifying the optimal acquisition times through the UASea toolbox and fully exploits the potentials of UAS in environmental applications. Moreover, the OBIA workflow and classification combined with the image quality and accuracy assessment demonstrates the importance of such methods in producing very high-resolution and reliable maps of marine habitats. The proposed methodology was implemented in four coastal areas, in Greece, with different characteristics and prevalent environmental conditions, using different UAS with RGB sensors. In particular, the efficiency of the methodology was tested by acquiring data in several conditions in each site and by comparing the results as to the image quality and the classification accuracies. The results showed that the imagery acquired in the proposed acquisition times was of higher quality along with high classification accuracies. This methodology offers an efficient solution for the acquisition of high-resolution and reliable marine information and accurate habitat delineation that can be adaptable in a range of ecological and environmental studies.

Automated summary

This study proposes an efficient methodology for marine habitat mapping using unmanned aerial systems (UAS) and object-based image analysis (OBIA), along with image quality and accuracy assessment. The methodology was tested in four coastal areas in Greece, demonstrating its effectiveness and reliability.