Remote sensing ocean colour studies at coastal areas have long been used to determine water quality, the distribution of coastal habitats, or even nutrient availability in such complex and dynamic ecosystems.
These studies are essential to ensure continuous (‘operational’) environmental monitoring of coastal resources, especially in those regions affected by human activities. In fact, the recent surge in coastal activities such as aquaculture, tourism, or in blue economy sectors, has led to an intensification of phenomena such as eutrophication, hypoxia, or death of marine life.
An international team of scientists at the University of Malta have retrieved water quality parameters (Chlorophyll-a and Total Suspended Solids concentration) from multispectral images captured by means of a drone at two different sites along the north-western Maltese coastline.
The Cumnija Sewage Treatment Plant and the Cirkewwa Reverse Osmosis Plant were chosen as examples of operational discharge points of pollutants, which could give rise to biogeochemical changes that in turn, may led to variations in the water-quality indicators. In addition, a new robust algorithm to generate an orthomosaic over water areas, was implemented.
This study represents the most accurate approximation of water quality for the region of interest. The centimetre-scale drone data improves on the high-resolution Sentinel-2 satellite data that is available with a spatial resolution of 10 m, and on the Sentinel-3 OLCI imagery that offers a much lower spatial resolution of 300 m. Although discharges from the monitored installations were expected to influence the water-quality considerable, the results suggest that this is not the case. In fact, the Chl-a values obtained were in the range of 0 to 1.5 mg/m3, whilst the TSS values were between 10 and 20 mg/m3, reflecting acceptable water quality values.
The compilation of georeferenced orthomosaics over aquatic regions from drone-obtained imagery is very challenging. Although a number of Structure from Motion (SfM) photogrammetry techniques that identify and stitch common points between different photos exist, these fail when applied over water areas.
Therefore, so far, the majority of water-quality studies that rely on remote-sensing, were limited to the coastline or to small water bodies such as lakes and reservoirs. Preliminary results obtained in this study suggest that the proposed mosaicking technique provides promised results that improve on the current state-of-the-art.
This research was funded through grants PY20-00244 SAT4ALGAE (Junta de Andalucia), RTI2018-098784-J-I00 (Sen2Coast Project), IJC2019-039382-I (Juan de la Cierva Incorporación), funded by MCIN/AEI/10.13039/501100011033, and supported by “ERDF A way of making Europe”. A.R. is supported by grant FPU19/04557, funded by the Ministry of Universities of the Spanish Government.
The study was carried out by Alejandro Román, Dr Adam Gauci, Prof. Alan Deidun, Prof Sebastiano D’Amico, and Emanuele Colica from the Department of Geosciences within the Faculty of Science. The results were published in the International Journal of Remote Sensing. The team involved in this study includes scientists from Spain, Italy, and Malta.
