Unmanned aerial systems‐based monitoring of the eco‐geomorphology of coastal dunes through spectral Rao’s Q

Marco Malavasi, Manuele Bazzichetto, Jan Komárek, Vítězslav Moudry, Duccio Rocchini, Simonetta Bagella, Alicia Teresa Rosario Acosta & Maria Laura Carranza

Optical data collected by the drone and elaborated computing Rao’s Q diversity index allowed describing the study sites’ bio-physical heterogeneity and assessing the dune systems’ integrity.

Coastal dunes deliver important ecosystem services which are essential for our wellbeing. These services include coastal defence, groundwater storage, nutrient recycling and recreation, among others. The stable delivery of such services depends on dunes’ bio-physical integrity, which is guaranteed by the interaction between sediment and coastal plants adapted to sand burial. Specifically, the sand deposited on the beach by sea currents and storms is blown inland by the wind and gets eventually trapped by coastal vegetation which acts as a natural barrier to sediment dispersal. In turn, sand burial fosters coastal plants’ growth, favouring the formation of new dunes and stabilizing existing ones. Maintaining such positive feedback between sand circulation and vegetation is crucial for assuring coastal dunes’ integrity and the steady provisioning of the ecosystem services mentioned above.

Several natural and anthropogenic processes (e.g. erosion, construction of harbours and dams, tourism) can alter coastal dunes’ integrity and functioning. One possible solution to mitigate the degradation of dune ecosystems is to regularly monitor their conservation status. This is generally done by collecting data on biological (e.g. plant diversity and biomass) and topographical attributes (e.g. dune elevation and slope) through ground surveys. However, field sampling has many limitations: it is time-consuming, resource-intensive, and provides rather local insights on natural systems. In this respect, the use of remote sensing data acquired by drones has recently opened to new opportunities for ecosystem monitoring. The strength of drones is their capacity to collect a considerable amount of highly detailed data on bio-physical parameters in a relatively short time and over very large geographic extents. Diversity indices, such as those commonly used in ecology to measure biodiversity, can then be applied to drone images for assessing the integrity of natural systems.

Light fixed-wing Unmanned Aerial Vehicle (eBee Cassic, senseFly, Switzerland) used to acquire optical data during the field campaign on the Lazio coast (location: Montalto di Castro, Italy). Photo credit: Jan Komárek.

Our study investigated whether applying diversity metrics to remote sensing data acquired by drones allows discriminating the conservation status of dune systems undergoing different human pressure. The idea is that high human pressure simplifies the typical bio-physical heterogeneity encountered in well-preserved dune systems, and that this phenomenon can be detected using drone images and diversity metrics. To test this hypothesis, we obtained images by flying a drone in two Mediterranean sites, which we identified as representative of dune systems subjected to low and high human pressure. We derived layers representing the spatial configuration of the dune vegetation and morphology along the two coastal sites by processing these images with dedicated algorithms. We then applied the Rao’s Q diversity index to the obtained layers to summarize the sites’ bio-physical heterogeneity. We observed that using Rao’s Q on drone images effectively allowed highlighting differences in the conservation status of the coastal sites affected by different human pressure. In particular, Rao’s Q presented more heterogeneous values in the site subjected to low human pressure. This result perfectly matches the idea of well-preserved dune systems characterized by complex vegetation mosaics and articulated dune morphology. Our study is the first attempt to apply diversity indices to drone images. Nonetheless, it constitutes a good starting point for further studies combining drone data and diversity metrics to assess ecosystem integrity.

This is a plain language summary for the paper of Malavasi et al. published in Applied Vegetation Science (https://doi.org/10.1111/avsc.12567).