Integrated approach to monitor water dynamics with drones
CEDA Dredging Days 2017 - Sustainable Dredging - Continued Benefits
Raymaekers D., De Keukelaere L., Knaeps E., Strackx G., Verstappen T., De Crop B., Bollen M.
Abstract: Remote Sensing (RS) has been used for more than 20 years to estimate water quality in the open ocean and study the evolution of vegetation on land. More recently, big improvements have been made to extend these practices to coastal and inland waters, opening new monitoring opportunities, eg. monitoring the impact of dredging activities on the aquatic environment. While satellite sensors can provide complete coverage and historical information of the study area, they are limited in their temporal revisit time and spatial resolution. Therefore, deployment of drones can create an added value and in combination with satellite information, sediment transport models and bouys, increase insights in the dynamics and actors of coastal and aquatic systems. Drones have the advantages of monitoring at high spatial detail (cm scale), with high frequency and are flexible. In this paper, the potential of using drones is investigated for mapping of sediment concentrations in natural waters. In the area around the harbor of Breskens, The Netherlands, located in the estuary of the river Scheldt, several drone flights were organized in summer and winter period of 2016. An automated processing chain was developed to generate true colour maps and sediment concentration maps which are analysed at high spatial and temporal resolution. Image products coming from these type of drone sensors can only be applied if they meet the specific requirements in terms of quality, processing speed and are presented in a user-friendly platform. For this purpose a spatial data infrastructure has been established to be able to visualize the drone images and products in a web-interface, overlaying information from different source (RS and in-situ) and give basic analyzing tools like displaying multi-temporal information in graphical representation.
Key words: Environment, water quality, sediment, total suspended material, remote sensing, drone, image analytics