Question

Does spectral diversity captured by unmanned aerial systems (UAS) provide reliable information for monitoring the eco-geomorphological integrity of Mediterranean coastal dune ecosystems? Can this information discriminate between two coastal areas with low (LP) and high (HP) human pressure?

Location

Tyrrhenian coast, Central Italy.

Methods

By processing UAS images, we derived the normalized difference vegetation index (NDVI) and topographic variables at high spatial resolution (0.5 m) for 150 m wide strips starting from the coastline inland on two representative coastal tracts under low and high human pressure. We mapped the sea–inland heterogeneity applying Rao's Q index to the plant biomass (NDVI) and geomorphology variables (elevation and slope). Since Rao's Q index can be calculated in a multidimensional space, we summarized the variability of these three variables into a single eco-geomorphological layer. We then inspected and compared how the Rao's Q index values for plant biomass, geomorphology and eco-geomorphology change as a function of the distance from the sea between the two coastal sites.

Results

Rao's Q heterogeneity values vary along the sea–inland gradient of well-preserved sites (LP). The maximum eco-geomorphological heterogeneity was found at intermediate distances from the sea and decreased toward the inner sector where the dune geomorphology was more stable and vegetation more homogeneously distributed. Instead, Rao's Q heterogeneity values featured constant low values along the gradient on the HP site, highlighting a simplified eco-geomorphological gradient related to the high human pressure.

Conclusions

Using UAS, the eco-geomorphological gradient of coastal dunes can be quantified at a very fine spatial resolution over management-relevant extents. Rao's Q index applied to sensing imagery successfully captured the differences in the eco-geomorphological heterogeneity along the sea–inland dune gradient and among sites with different levels of anthropic pressure. This approach supports frequent surveys and is particularly suitable for spatial monitoring of key coastal functions and services.

https://doi.org/10.1111/avsc.12567

https://vegsciblog.org/2021/03/17/uas-based-monitoring-of-coastal-dunes/