An evaluation of imagery from an unmanned aerial vehicle (UAV) for the mapping of intertidal macroalgae on Seal Sands, Tees Estuary, UK

Abstract

The Seal Sands area of Teesmouth is designated a Special Protection Area under the habitats directive because guideline concentrations of nutrients in coastal waters are exceeded. This may be responsible for extensive growth of the green filamentous macroalgae Enteromorpha sp., and literature suggests that algal cover in the intertidal zone is detrimental to the feeding behaviour of wading bird species. Although numerous studies have highlighted the causes and consequences of macroalgal cover, the complex spatial and temporal dynamics of macroalgal bloom growth are not as well understood, and hence there is a need to develop a precise and cost effective monitoring method for the mapping and quantifying of algal biomass. Previous studies have highlighted several image processing techniques that could be applied to high resolution airborne imagery in order to predict algal biomass. In order to test these methods, high resolution imagery was acquired in the Sea լ Sands area using a lightweight SmartPlanes SmartOne unmanned aerial vehicle (UAV) equipped with a near-infrared sensitive 5-megapixel Canon IXUS compact camera, a standard 6-megapixel Canon IXUS compact camera and a Garmin Geko 201 handheld GPS device. Imagery was acquired in November 2006 and June 2007 in order to examine the spectral response of Enteromorpha sp. at different time periods within a macroalgal growth cycle. Images were mosaicked and georeferenced using ground control points located with a Leica 1200 differential GPS and processed to allow for analysis of their spectral and textural properties. Samples of macroalgal cover were collected, georeferenced and their dry biomass content obtained for ground truthing. Although textural entropy and inertia did not correlate significantly with macroalgal biomass, normalised green-red difference index (NGRDI), normalised difference vegetation index (NDVI) and colour saturation computed on the imagery showed a good degree of linear correlation with Enteromorpha sp. dry weight, achieving coefficients of determination in excess of r(^2)= 0.6 for both the November2006 and June 2007 image sets. Linear regression was used to establish predictive models to estimate macroalgal biomass from image spectral properties. Enteromorpha sp. Biomass estimations of 71.4 g DW m(^-2) and 7.9g DW m(^-2) were established for the November 2006 and June2007 data acquisition sessions respectively. Despite a lack of previous biomass quantification for Seal Sands, the favourable performance of a UAV in terms of operating cost and man hours required for image acquisition suggests that unmanned aerial vehicles may present a viable method for the mapping of intertidal algal biomass on an annual basis.