Abstract
Aquatic vegetation has important ecological and regulatory functions and should be monitored in order to detect ecosystem changes. Field data collection is often costly and time-consuming; remote sensing with unmanned aircraft systems (UASs) provides aerial images with sub-decimetre resolution and offers a potential data source for vegetation mapping. In a manual mapping approach, UAS true-colour images with 5-cm-resolution pixels allowed for the identification of non-submerged aquatic vegetation at the species level. However, manual mapping is labour-intensive, and while automated classification methods are available, they have rarely been evaluated for aquatic vegetation, particularly at the scale of individual vegetation stands. We evaluated classification accuracy and time-efficiency for mapping non-submerged aquatic vegetation at three levels of detail at five test sites (100 m × 100 m) differing in vegetation complexity. We used object-based image analysis and tested two classification methods (threshold classification and Random Forest) using eCognition®. The automated classification results were compared to results from manual mapping. Using threshold classification, overall accuracy at the five test sites ranged from 93% to 99% for the water-versus-vegetation level and from 62% to 90% for the growth-form level. Using Random Forest classification, overall accuracy ranged from 56% to 94% for the growth-form level and from 52% to 75% for the dominant-taxon level. Overall classification accuracy decreased with increasing vegetation complexity. In test sites with more complex vegetation, automated classification was more time-efficient than manual mapping. This study demonstrated that automated classification of non-submerged aquatic vegetation from true-colour UAS images was feasible, indicating good potential for operative mapping of aquatic vegetation. When choosing the preferred mapping method (manual versus automated) the desired level of thematic detail and the required accuracy for the mapping task needs to be considered.
Highlights
Aquatic vegetation has important ecological and regulatory functions in aquatic ecosystems.Aquatic plants serve as food and habitat for many organisms, including microflora, zooplankton, Remote Sens. 2016, 8, 724; doi:10.3390/rs8090724 www.mdpi.com/journal/remotesensingRemote Sens. 2016, 8, 724 macroinvertebrates, fish, and waterfowl [1]
In a previous study based on visual interpretation, we found that true-colour digital images collected from a unmanned aircraft systems (UASs) platform allowed for the identification of 21 non-submerged aquatic and riparian species [16]
True-colour images taken by UASs with sub-decimetre spatial resolution will be increasingly available for ecological applications in the future
Summary
Aquatic vegetation has important ecological and regulatory functions in aquatic ecosystems.Aquatic plants serve as food and habitat for many organisms, including microflora, zooplankton, Remote Sens. 2016, 8, 724; doi:10.3390/rs8090724 www.mdpi.com/journal/remotesensingRemote Sens. 2016, 8, 724 macroinvertebrates, fish, and waterfowl [1]. Aquatic vegetation has important ecological and regulatory functions in aquatic ecosystems. Aquatic plants serve as food and habitat for many organisms, including microflora, zooplankton, Remote Sens. Aquatic vegetation alters the composition of its physical environment by absorbing wave energy, thereby stabilizing sediments [1]. It forms an interface between the surrounding land and water, and intercepts terrestrial nutrient run-off [1,5]. Aquatic plant species are important indicators for environmental pressures and are integrated globally in the assessment of ecological status of aquatic ecosystems [6,7,8]
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