Abstract
Abstract. The compositional and structural characteristics of wetland vegetation play a vital role in the services that a wetland supplies. Apart from being important habitats, wetland vegetation also provide services such as flood attenuation and nutrient retention. South Africa is known to be a water scarce country. The protection and continuous monitoring of wetland ecosystems is therefore important. Factors such as site transformation and disturbance may completely change the vegetation of a wetland and the use of Unmanned Aerial Vehicle (UAV) imagery can play a valuable role in high-resolution monitoring and mapping. This study assessed if the use of UAV RGB imagery can enhance the determination of the present vegetation state of a wetland. The WET-Health level two (detailed on-site evaluation) methodology was followed for the vegetation assessment, where wetland health is a measure of the deviation of a wetland’s structure and function from its natural reference condition. The mapping of the disturbances classes was then undertaken using ultra-high resolution orthophotos, point clouds and digital surface models (DSM). The WET-Health vegetation module completed with the aid of the UAV products still indicates that the vegetation of the wetland is largely modified (“D” PES Category) and that the vegetation of the wetland will further deteriorate (change score). These results are the same as determined in the baseline study. However a higher impact (activities taking place within the wetland) score were determined. The assessment of various WET-Health vegetation indicators were significantly enhanced using the UAV imagery and derived products. The UAV products provided an accurate vantage point over the wetland and surroundings, and assisted to easily refine the assessment of the disturbance classes and disturbance units.
Highlights
Remote sensing data have not been available at the appropriate scale until recently; Unmanned Aerial Vehicle (UAV) can provide the appropriate spatial resolution needed by scientists (Zweig et al, 2015). Lucieer et al (2013) specified that the “primary advantage of UAV-based remote sensing is the ability to bridge the scale gap between fieldbased observations and full-scale airborne or satellite observations”
Remote sensing data have not been available at the appropriate scale until recently; UAVs can provide the appropriate spatial resolution needed by scientists (Zweig et al, 2015)
In previous studies we showed that UAV derived orthophotos, point clouds and digital surface models (DSM) can significantly enhance wetland delineation, classification and health assessment trough the extraction of relevant information from these imagery (Boon et al, 2016a) and that these imagery can be used for rapid and accurate mapping of wetlands (Boon et al, 2016b)
Summary
Remote sensing data have not been available at the appropriate scale until recently; UAVs can provide the appropriate spatial resolution needed by scientists (Zweig et al, 2015). Lucieer et al (2013) specified that the “primary advantage of UAV-based remote sensing is the ability to bridge the scale gap between fieldbased observations and full-scale airborne or satellite observations”. Remote sensing data have not been available at the appropriate scale until recently; UAVs can provide the appropriate spatial resolution needed by scientists (Zweig et al, 2015). Flener et al (2012) characterized upland swamps using objectbased classification methods and hyper-spatial resolution imagery acquired using a UAV. The orthophoto provided the possibility to assess the different land uses and the difference in phenology between the wet and the dry season. In a study by Zweig et al (2015) the use of UAVs to delineate fine-scale wetland vegetation communities were assessed. This analysis was one of the first not to only acquire map or orthophoto and data for fine-scale ecological community classification
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