Application of multiplatform, multispectral remote sensors for mapping intertidal macroalgae: A comparative approach

Abstract

1. Intertidal macroalgal communities are economically and ecologically important and, with a likely increase in anthropogenic pressures, there is need to evaluate and monitor these diverse habitats. Efforts to conserve and sustainably manage these habitats must be underpinned by accurate, cost-effective, and efficient data collection methods. The high spatial and temporal resolution of unmanned aerial vehicles (UAVs), compared with satellites and aircraft, combined with the development of lightweight sensors, provides researchers with a valuable set of tools to research intertidal macroalgal communities.2. The ability of multispectral sensors, mounted on a satellite, an aircraft, and a UAV, to identify and accurately map the intertidal brown fucoid Ascophyllum nodosum (Fucales, Ochrophyta) at a site with a low species diversity of macroalgae were compared.3. Visual analysis confirmed that the spatial resolution of satellite imagery was too coarse to map intertidal macroalgae as it could not capture the fine spatial patterns of the macroalgal community. High-resolution RGB (colour) imagery, taken during the aircraft and UAV surveys, was used to collect training and reference data through the visual identification and digital delineation of species. Classes were determined based on the level of taxonomic detail that could be observed, with higher levels of taxonomic detail observed in the UAV imagery over the aircraft imagery. Data from both were used to train a maximum-likelihood classifier (MLC).4. The UAV imagery was able to more accurately classify a distinct A. nodosum class, along with other macroalgal and substratum classes (overall accuracy, OA, 92%), than the aerial imagery, which could only identify a lower taxonomic resolution of mixed A. nodosum and fucoid class, achieving a lower OA (78.9%). This study has demonstrated that in a coastal site with low macroalgal species diversity, and despite the spectral similarity of macroalgal species, UAV-mounted multispectral sensors proved the most accurate for focused assessments of individual canopyforming species.

Seaweed Habitats on the Shore: Characterization through Hyperspectral UAV Imagery and Field Sampling

“…The present work focuses on an easy habitat classification through high spatial resolution pictures, obtained by a UAV and by applying commonly used algorithms. To characterize seaweed-dominated habitats, maximum likelihood (MLC) is currently the most widely used method of supervised classifications [48], along with the spectral angle mapper (SAM) [49][50][51][52].…”

Missing the Forest and the Trees: Utility, Limits and Caveats for Drone Imaging of Coastal Marine Ecosystems

“…Unlike satellites, unmanned aerial vehicles (UAVs or drones) can overcome many of these challenges. They have very high pixel resolution, deployment can be timed to coincide with appropriate meteorological and oceanographic conditions, and in-situ validation sampling can be completed simultaneously [23,[26][27][28][29]). Accurately relating remotely measured spectral signatures to in situ observations provides the key mechanism for building effective detection algorithms and assessing their accuracy [27].…”

“…They have very high pixel resolution, deployment can be timed to coincide with appropriate meteorological and oceanographic conditions, and in-situ validation sampling can be completed simultaneously [23,[26][27][28][29]). Accurately relating remotely measured spectral signatures to in situ observations provides the key mechanism for building effective detection algorithms and assessing their accuracy [27]. Spectral libraries provide promise for remote taxonomic surveys [30], especially when aligned with low elevation hyperspectral imaging surveys [29,31], but challenges remain to deal appropriately with fundamental and realised spectra of species across seasons and under multiple scenarios of water coverage [29].…”

“…Appropriate validation of observations is also an area with no widely accepted protocols, although embedding transects has been widely used [23,26]. Previous work on UAVs and rocky reef imaging [23,[26][27][28][29] show the value of small-scale aerial imagery for marine rocky reefs, and the difficulties of using passive remote sensing (Figure 1). While satellite imaging sensors are increasingly offering submetre pixel resolution (e.g., Maxar, 15-30 cm resolution), the high return frequency satellites (e.g., Sentinel-2 and Landsat-8) offer a minimum pixel size of 10-30 m, allowing only broad detection of emersed vegetation visible in near-infra-red (Figure 1).…”

Using a UAV-Mounted Multispectral Camera for the Monitoring of Marine Macrophytes

“…Unmanned aerial vehicles present a number of advantages for monitoring marine macrophytes: (i) they offer a spatial and spectral resolution accurate enough to taxonomically identify seagrass or other organisms with a high level of detail (centimeter scale); (ii) they provide greater control of temporal resolution than satellites, increasing the flexibility for image acquisition; (iii) they are not affected by cloud cover; (iv) they are costeffective tool because of the rapid technological development, and improvements related to longer battery life and higher spatial resolutions (Kellaris et al, 2019;Rossiter et al, 2020a). However, the use of UAVs for mapping submerged habitats has some limitations such as the environmental conditions at the time of data acquisition, they cannot cover large areas due to the battery autonomy, the need for trained personnel and they need to comply with the specific regulations of each territory for their deployment (Nahirnick et al, 2018).…”