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

Abstract

Marine macrophytes constitute one of the most productive ecosystems on the planet, as well as one of the most threatened by anthropogenic activities and climate change. Their monitoring is therefore essential, which has experienced a fast methodological evolution in recent years, from traditional in situ sampling to the use of satellite remote sensing, and subsequently by sensors mounted on unmanned aerial vehicles (UAV). This study aims to advance the monitoring of these ecosystems through the use of a UAV equipped with a 10-band multispectral camera, using different algorithms [i.e., maximum likelihood classifier (MLC), minimum distance classifier (MDC), and spectral angle classifier (SAC)], and using the Bay of Cádiz Natural Park (southern Spain) as a case of study. The results obtained with MLC confirm the suitability of this technique for detecting and differentiating seagrass meadows in a range of 0–2 m depth and the efficiency of this tool for studying and monitoring marine macrophytes in coastal areas. We inferred the existence of a cover of 25452 m2 of Cymodocea nodosa, and macroalgae species such as Caulerpa prolifera, covering 22172 m2 of Santibañez (inner Bay of Cádiz).

Fusion of Drone-Based RGB and Multi-Spectral Imagery for Shallow Water Bathymetry Inversion

“…The recent developments in drone technology offer tremendous opportunities for the development of novel geospatial applications. Drones are becoming increasingly popular in remote sensing studies since they are low-cost platforms; they provide centimeter-scale spatial resolution that is suitable for observing objects and/or processes in unique detail; they require negligible logistic effort, allowing for frequent deployment on demand, thus increasing the temporal resolution of imagery; and they operate in close range without being influenced by clouds or other atmospheric effects [29][30][31]. There have been a few recent studies applying empirical SDB algorithms (i.e., extensions of the logarithmic band-ratio technique) on drone-based multispectral imagery [31][32][33][34] showing relatively good results with up to 40 cm vertical errors.…”

“…Considering the issue of spectral resolution, there are several commercial sensors for drones, such as the MicaSense-RedEdge© dual camera offering 10 bands in the visible and near-infrared areas, and other lightweight RGB or hyperspectral cameras which are routinely used on various projects. These projects include environmental mapping [36], water quality monitoring [37] and intertidal/subtidal habitat mapping [30,32,36,[38][39][40][41]. Ideally, hyperspectral sensors would provide significant input data in shallow bathymetry inversion with analytical methods, due to their enhanced radiometric resolution in the visible range of the spectrum [32].…”

Monitoring Seasonal Morphobathymetric Change of Nearshore Seafloor Using Drone-Based Multispectral Imagery

“…The recent developments in drone technology provided new opportunities for the development of novel geospatial applications. Drones are becoming increasingly popular in remote sensing studies since they are low-cost platforms; they provide a centimeter-scale spatial resolution that is suitable for observing objects and/or processes in unique detail; they require negligible logistic effort, allowing for frequent deployment on demand, thus increasing the temporal resolution of imagery; they operate in close range without being influenced by clouds or other atmospheric effects (Alevizos, 2019;Román et al, 2021;Rossi et al, 2020). Until recently, there have been a few recent studies applying SDB algorithms on drone-based multispectral imagery (Alevizos et al, 2022b;Kabiri et al, 2020;Parsons et al, 2018;Rossi et al, 2020;Slocum et al, 2020;Starek and Giessel, 2017) showing relatively good results with up to 40 cm vertical errors.…”

Shallow water bathymetry inversion using hybrid multi-band composites resulted from integration of drone-based RGB and multispectral imagery

“…The recent developments in drone technology offered tremendous opportunities for the development of novel geospatial applications. Drones are becoming increasingly popular in remote sensing studies since they are low-cost platforms; they provide centimeter-scale spatial resolution that is suitable for observing objects and/or processes in unique detail; they require negligible logistic effort, allowing for frequent deployment on demand, thus increasing the temporal resolution of imagery; they operate in close range without being influenced by clouds or other atmospheric effects (Alevizos, 2019;Román et al, 2021;Rossi et al, 2020).…”

“…Considering proximal sensing, there are several commercial sensors for drones, such as the MicaSense-RedEdge© dual camera offering 10 bands in the visible and near infrared areas, and other lightweight RGB or hyperspectral cameras which are routinely used on various projects such as environmental mapping (Manfreda et al, 2018), water quality monitoring (Isgró et al, 2021) and intertidal/subtidal habitat mapping (Fallati et al, 2020;Manfreda et al, 2018;Murfitt et al, 2017;Parsons et al, 2018;Román et al, 2021;Rossiter et al, 2020). Ideally, hyperspectral sensors would provide significant input data for shallow bathymetry mapping with analytical methods, due to their enhanced radiometric resolution in the visible range of the spectrum (Parsons et al, 2018).…”