Unoccupied aerial vehicle-assisted monitoring of benthic vegetation in the coastal zone enhances the quality of ecological data

Abstract

Traditional monitoring (e.g., in-water based surveys) of eelgrass meadows and perennial macroalgae in coastal areas is time and labor intensive, requires extensive equipment, and the collected data has a low temporal resolution. Further, divers and Remotely Operated Vehicles (ROVs) have a low spatial extent that cover small fractions of full systems. The inherent heterogeneity of eelgrass meadows and macroalgae assemblages in these coastal systems makes interpolation and extrapolation of observations complicated and, as such, methods to collect data on larger spatial scales whilst retaining high spatial resolution is required to guide management. Recently, the utilization of Unoccupied Aerial Vehicles (UAVs) has gained popularity in ecological sciences due to their ability to rapidly collect large amounts of area-based and georeferenced data, making it possible to monitor the spatial extent and status of SAV communities with limited equipment requirements compared to ROVs or diver surveys. This paper is focused on the increased value provided by UAV-based, data collection (visual/Red Green Blue imagery) and Object Based Image Analysis for gaining an improved understanding of eelgrass recovery. It is demonstrated that delineation and classification of two species of SAV ( Fucus vesiculosus and Zostera marina) is possible; with an error matrix indicating 86–92% accuracy. Classified maps also highlighted the increasing biomass and areal coverage of F. vesiculosus as a potential stressor to eelgrass meadows. Further, authors derive a statistically significant conversion of percentage cover to biomass ( R2 = 0.96 for Fucus vesiculosus, R2 = 0.89 for Zostera marina total biomass, and R2 = 0.94 for AGB alone, p < 0.001). Results here provide an example of mapping cover and biomass of SAV and provide a tool to undertake spatio-temporal analyses to enhance the understanding of eelgrass ecosystem dynamics.

UAV-Based Subsurface Data Collection Using a Low-Tech Ground-Truthing Payload System Enhances Shallow-Water Monitoring

“…One example is the collection of high-resolution ground-truthing data needed as training and validation samples for the classification of the obtained aerial imagery. Low-altitude images taken by a conventional UAV-mounted camera are occasionally of sufficient quality to be used for ground-truthing purposes, given the right environmental conditions and favorable properties of the study area [3]. In most areas, however, this method is limited to areas of a maximum depth of a few decimeters, while at the same time being very weather dependent, as the spectral signal reflecting from benthic substrates quickly gets absorbed or scattered with increasing depth, low visibilities or wind-induced movements at the water surface, not allowing for a clear determination of present species or habitats from low-altitude imagery [5,24,25].…”

“…Unoccupied Aerial Vehicles (UAVs) have become a widely applied tool in the field of spatial ecology [1,2], including the mapping and monitoring of shallow-water habitats [3][4][5][6][7][8][9]. Their ability to collect aerial imagery with a high spatial and temporal resolution over relatively large areas in a cost-and time-efficient way has allowed researchers to study ecosystems on new spatial scales by bridging the gap between traditional satellite and plane-based remote sensing and in-water techniques, including diver and vessel-based surveys [10].…”

“…Especially, lightweight multirotor platforms have gained popularity among researchers due to their low acquisition cost, vertical take-off and landing capability, easy handling, flexible payload arrangements and their ability to hover in a fixed position over a point of interest. Examples of research conducted in shallow-water habitats using UAVs include mapping and monitoring coral reefs [11][12][13], submerged vegetation in marine [3,4,[14][15][16] and freshwater [17][18][19][20] environments, as well as of submerged habitats as a whole [21][22][23].…”

Comparative Assessment of Five Machine Learning Algorithms for Supervised Object-Based Classification of Submerged Seagrass Beds Using High-Resolution UAS Imagery

“…Traditional air-and space-borne remote sensing techniques on the other hand have the ability to map large areas at a lower cost per unit area [14], but are, however, often lacking the spatial resolution required to solve specific monitoring tasks. In recent years, unoccupied aerial systems (UAS) have received attention due to their potential of compromising between the survey methods by performing monitoring tasks with a high spatial and temporal resolution over relatively large areas in a cost-and time-effective way [15][16][17]. The high spatial resolution of the data provided by UASs further allows for alternative methods of image analysis by, for example, adopting an object-based image analysis (OBIA) approach instead of using traditional pixel-based methods.…”

Drone exploration of bat echolocation: A UAV‐borne multimicrophone array to study bat echolocation

“…Unmanned aerial vehicles (UAVs) are used increasingly in ecological surveys as they offer great speed, maneuverability, and precision, and they can easily explore environments not readily available to traditional survey methods (Fu et al, 2018 ; Scholten et al, 2019 ; Svane, Flindt, et al, 2022 ; Svane, Lange, et al, 2022 ; Wilson et al, 2017 ). As such, combining ultrasonic recordings with UAVs presents an opportunity to overcome the major limitations of traditional microphone array recordings, that is, they are stationary and ground based.…”