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Mapping coastal bio-geomorphic dune development with UAV-imaging

Corjan Nolet, Marinka Van Puijenbroek, Juha Suomalainen, Juul Limpens, Michel Riksen
Wageningen University, Wageningen, The Netherlands

In 2011 an unprecedented large nourishment of sand (Sand Motor, www.zandmotor.nl) was laid down along a stretch of the Dutch coast. An important objective of this Sand Motor is increased transport of sand by wind over the beach towards the dunes, enabling the dunes to naturally grow in volume. Predictions, however, of coastal dune development are hampered by an incomplete understanding of a number of processes, most notably mesoscale aeolian sand transport and bio-geomorphological interactions (Keijsers et al. 2014b).

It is clear that coastal dunes in the Netherlands develop by a mutually reinforcing interaction between aeolian sand deposition and dune-building grass species. Sand Couch (E. juncea) and Marram Grass (A. arenaria), in particular, not only act to trap sand but positively thrive under certain conditions of sand burial (Hesp 1989, Van der Putten et al. 1993; Lancaster and Baas 1998; Maun 2009; Zarnetske et al. 2012a). This introduces a positive bio-geomorphic feedback, where adequate levels of sand trapping encourage the plants to grow, in turn enhancing the plant’s capacity to trap sand.  However, even though these processes are understood, little quantitative information is available on how these physical-biological feedbacks control dune morphology.

Therefore, in order to help elucidate how reinforcing feedbacks between plant growth and sand trapping promote dune growth, coastal bio-geomorphic dune development on the Sand Motor has been extensively mapped using an unmanned aerial vehicle (UAV). Over the course of a year, working within the WUR Unmanned Aerial Remote Sensing Facility (www.wageningenur.nl/uarsf), a high spatial-temporal resolution topographic and ecologic dataset has been constructed by applying the Structure from Motion (SfM) and Multi-View Stereo (MVS) algorithms to unstructured aerial images. The camera was modified for indicating a Normalized Difference Vegetation Index (red channel = near infrared 680-800 nm), ensuring enriched applicability for ecological monitoring.

Analysis of the data is focused on relationships between differences in vegetation densities and changes in dune height, as well as rates of aeolian deposition and changes in vegetation cover & vitality (i.e. greenness of the plant). The latter may serve as an indicator of plant response to burial and/or optimal burial levels.

(note: bibliography could not be included due to exceedance of word count)