With the implementation of the EU Water Framework Directive there is a need for better knowledge on water quality in all larger lakes in Denmark by 2015. Currently, the national monitoring programme in Denmark (NOVANA) is based on traditional in-situ sampling and an extension of this monitoring programme would be a very expensive and time consuming task.
Activities related to monitoring of the marine environment by use of satellite (for examples see http://www.grasdk.com/Solutions/MarineApplications) have proven to be a cost-efficient addition to the in-situ based monitoring programme. Monitoring of water quality through remote sensing is one of the core competences at GRAS and the thorough knowledge gained in this field will be applied in this project to investigate the potential of very high resolution satellite images for water quality monitoring. In order to test the possibilities of transferring the methods and experiences from the marine monitoring activities in Denmark to the monitoring of lakes a research project funded by the EcoInnovation sector of the Danish Ministry of Environment was initiated in 2010 with the aim of optimizing monitoring of the freshwater lakes in Denmark and demonstrate the capabilities of satellite based methods. The project focuses on chlorophyll mapping using time series of both the newest very high resolution satellite data (2m resolution) and the traditional medium resolution satellite data (300 m resolution). Furthermore, an important component is to prepare for the coming Sentinel-2 data flow which will significantly improve the large scale monitoring potential from use of satellite data in national monitoring obligations to comply with the Water Framework Directive.
During the project it will furthermore be investigated how the integration of satellite data into ecological lake models can be improved and extended and thereby complement the existing monitoring programme of freshwater areas in Denmark.
Preliminary results – WorldView-2
During the summer period of 2011two ‘twin’ acquisitions of WorldView-2 8-band images were realised (time difference between the images in each twin acquisition was 4 and 2 days). Simultaneous field campaignswere made in between each twin acquisition in order to be able to calibrate the satellite data to chlorophyll concentrations.
Following a thorough pre-processing of the data (calibration and atmospheric correction) a multiple regression analysis was performed to identify the best possible variable(s) for the chlorophyll conversion.
Example of Chl-A mapping based on 8-band WorldView2 data
The results are very promising and clearly demonstrate the value of adding satellite based information to the current monitoring programme. The spatial variation for the individual lakes displayed in the satellite data highlights the uncertainty in point-based measurements – they are not necessarily representative for an entire lake. On the other hand, the in-situ data is needed to secure a good calibration of the satellite data to chlorophyll concentrations and for validation purposes.
The spatial resolution of the coming Sentinel-2 data combined with its temporal and spectral resolution will make the data an important source of information for monitoring purposes on regional scale. The open and free of charge Sentinel Data Policy will limit the price of incorporating the data into the existing traditional monitoring programme compared to using commercially available VHR data.
Preparatory activities for Sentinel-2 based monitoring are therefore an important part of the project. These activities will enable a faster and better inclusion of the data into services shortly after the data becomes available.
The DK Lake Monitoring Project is a partnership between GRAS, DHI Water and Environment and the National Environmental Research Institute (NERI) – Department of Freshwater Ecology. GRAS’ competences in satellite based monitoring of the environment in general and the marine environment in particular is a central part of the project that runs from 2010 – 2012.
Satellite data being used in the study includes Landsat, WorldView-2 and MERIS Full Resolution data.
Further information at www.grasdk.com