Abstract
Marine conservation and management require detailed and accurate habitat mapping, which is usually produced by collecting data using remote sensing methods. In recent years, unmanned aerial systems (UAS) are used for marine data acquisition, as they provide detailed and reliable information through very high-resolution orthophoto-maps. However, as for all remotely sensed data, it is important to study and understand the accuracy and reliability of the produced maps. In this study, the effect of different environmental conditions on the quality of UAS orthophoto-maps was examined through a positional and thematic accuracy assessment. Selected objects on the orthophoto-maps were also assessed as to their position, shape, and extent. The accuracy assessment results showed significant errors in the different maps and objects. The accuracy of the classified images varied between 2.1% and 27%. Seagrasses were under-classified, while the mixed substrate class was overclassified when environmental conditions were not optimal. The highest misclassifications were caused due to sunglint presence in combination with a rough sea-surface. A change detection workflow resulted in detecting misclassifications of up to 45%, on orthophoto-maps that had been generated under non-optimal environmental conditions. The results confirmed the importance of optimal conditions for the acquisition of reliable marine information using UAS.
Highlights
The mapping and monitoring of marine habitats are essential for conservation management, protection of marine habitats, and assessment of the environmental status of marine ecosystems [1]
Considering the published studies, we examined the effect of environmental conditions on the quality of unmanned aerial systems (UAS) derived data
We examined the effect of environmental conditions on the quality and reliability of UAS remotely sensed marine information
Summary
The mapping and monitoring of marine habitats are essential for conservation management, protection of marine habitats, and assessment of the environmental status of marine ecosystems [1]. 10–100 m is often appropriate for mapping while a spatial resolution of smaller than 10 m is increasingly being used for coastal applications [9]. There is a plethora of satellite sensors that offer different resolutions, these methods are often expensive, unavailable at regular intervals, and not flexible as to the extent and level of detail [10,11,12,13]. Satellite data and airborne digital imagery (e.g., Compact airborne spectrographic imager-CASI) allow the location and extent of seagrass beds to be mapped when there is a continuous area of seagrass with high-dense beds [9]. High-resolution data are often required for the detection of small marine features, the distinction of marine species, and the detection of marine habitat changes
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