Low-cost UAV monitoring: insights into seasonal volumetric changes of an oyster reef in the German Wadden Sea

• Published in: Frontiers in Marine Science
• Main Authors: Tom K. Hoffmann, Kai Pfennings, Jan Hitzegrad, Leon Brohmann, Mario Welzel, Maike Paul, Nils Goseberg, Achim Wehrmann, Torsten Schlurmann
• Format: Article in Journal/Newspaper
• Language: English
• Published: Frontiers Media S.A. 2023
• Subjects: Magallana gigas; remote sensing; monitoring; classification; random forest; error propagation; Science; Q; General. Including nature conservation; geographical distribution; QH1-199.5; Pacific; Pacific oyster
• Online Access: https://doi.org/10.3389/fmars.2023.1245926; https://doaj.org/article/58a5052cc6124bf0879624f96a4ec7b3

This study aims to quantify the dimensions of an oyster reef over two years via low-cost unoccupied aerial vehicle (UAV) monitoring and to examine the seasonal volumetric changes. No current study investigated via UAV monitoring the seasonal changes of the reef-building Pacific oyster (Magallana gigas) in the German Wadden Sea, considering the uncertainty of measurements and processing. Previous studies have concentrated on classifying and mapping smaller oyster reefs using terrestrial laser scanning (TLS) or hyperspectral remote sensing data recorded by UAVs or satellites. This study employed a consumer-grade UAV with a low spectral resolution to semi-annually record the reef dimensions for generating digital elevation models (DEM) and orthomosaics via structure from motion (SfM), enabling identifying oysters. The machine learning algorithm Random Forest (RF) proved to be an accurate classifier to identify oysters in low-spectral UAV data. Based on the classified data, the reef was spatially analysed, and digital elevation models of difference (DoDs) were used to estimate the volumetric changes. The introduction of propagation errors supported determining the uncertainty of the vertical and volumetric changes with a confidence level of 68% and 95%, highlighting the significant change detection. The results indicate a volume increase of 22 m³ and a loss of 2 m³ in the study period, considering a confidence level of 95%. In particular, the reef lost an area between September 2020 and March 2021, when the reef was exposed to air for more than ten hours. The reef top elevation increased from -15.5 ± 3.6 cm NHN in March 2020 to -14.8 ± 3.9 cm NHN in March 2022, but the study could not determine a consistent annual growth rate. As long as the environmental and hydrodynamic conditions are given, the reef is expected to continue growing on higher elevations of tidal flats, only limited by air exposure. The growth rates suggest a further reef expansion, resulting in an increased roughness surface area that contributes ...