Abstract
Monitoring of aquatic vegetation is an important component in the assessment of freshwater ecosystems. Remote sensing with unmanned aircraft systems (UASs) can provide sub-decimetre-resolution aerial images and is a useful tool for detailed vegetation mapping. In a previous study, non-submerged aquatic vegetation was successfully mapped using automated classification of spectral and textural features from a true-colour UAS-orthoimage with 5-cm pixels. In the present study, height data from a digital surface model (DSM) created from overlapping UAS-images has been incorporated together with the spectral and textural features from the UAS-orthoimage to test if classification accuracy can be improved further. We studied two levels of thematic detail: (a) Growth forms including the classes of water, nymphaeid, and helophyte; and (b) dominant taxa including seven vegetation classes. We hypothesized that the incorporation of height data together with spectral and textural features would increase classification accuracy as compared to using spectral and textural features alone, at both levels of thematic detail. We tested our hypothesis at five test sites (100 m × 100 m each) with varying vegetation complexity and image quality using automated object-based image analysis in combination with Random Forest classification. Overall accuracy at each of the five test sites ranged from 78% to 87% at the growth-form level and from 66% to 85% at the dominant-taxon level. In comparison to using spectral and textural features alone, the inclusion of height data increased the overall accuracy significantly by 4%–21% for growth-forms and 3%–30% for dominant taxa. The biggest improvement gained by adding height data was observed at the test site with the most complex vegetation. Height data derived from UAS-images has a large potential to efficiently increase the accuracy of automated classification of non-submerged aquatic vegetation, indicating good possibilities for operative mapping.
Highlights
Unmanned aircraft systems (UASs) offer a potential data source for detailed surveying of aquatic vegetation with images having centimetre-level spatial resolutions [1]
In a previous study [2], we showed that a true-colour UAS-orthoimage with 5-cm pixels allowed for automated classification of growth-forms and six dominant taxa of non-submerged aquatic vegetation in a lake in northern Sweden
One main reason for misclassification was the confusion of taxa that appeared similar in the UAS-orthoimage, but belonged to different growth forms
Summary
Unmanned aircraft systems (UASs) offer a potential data source for detailed surveying of aquatic vegetation with images having centimetre-level spatial resolutions [1]. 2017, 9, 247 resolution, distinguishing structural details of individual plants is possible, for example, floating leaves on the water surface. In a previous study [2], we showed that a true-colour UAS-orthoimage with 5-cm pixels allowed for automated classification of growth-forms and six dominant taxa of non-submerged aquatic vegetation in a lake in northern Sweden. While floating-leaved vegetation generally grows a couple of centimetres above the water surface, emergent plants can reach a considerable vegetation height, for example, 1–4 m for Phragmites australis, 1–3 m for Schoenoplectus lacustris, and 0.3–1.5 m for Equisetum fluviatile [3]
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