Baltic Sea and Finnish lakes (Landsat-8 OLI) 2016–/Daily Secchi depth of the Baltic Sea and Finnish lakes (Landsat-8 OLI) 2016—

**[EN]** Observations of satellite instruments monitor water depth from cloud-free areas during molten water from Finnish sea areas and lakes. The depth of vision describes the permeability of water and its assessment is related to the determination of the eutrophication level e.g.. The depth of view interpreted from satellite observations is in the process of method development and the data on the interface covers examples of observations. Visual depth is interpreted from the observations of the Landsat-8 satellite OLI instrument (as well as the Sentinel-2 series MSI instruments, separate metadata), the data will start in 2016. The interpretation shall be made to the nearest 60 metres. The C2RCC (Case-2 Regional CoastColour) model (Brockmann et al. 2016). The model is openly available through the SNAP software. However, in SYKE’s data, the final result of the model has been adapted to reflect the optical characteristics of Finland’s coastal and lake areas. The arrangement is based on field campaigns and environmental management position sampling on the coast and lakes (the basic principle described in Attila et al., 2013). Purpose: Monitoring of water quality in the Baltic Sea and Finnish lakes. The material is part of SYKE’s open data (CC BY 4.0). *** **[En]** Satellite observations are used to monitor the Secchi depth of water from cloudless regions during ice-free periods from Finnish sea areas and lakes. Secchi depth describes the transparency of the water. Secchi depth interpreted from the satellite observations is as material in the method development phase and the material consists of sample Interpretations. The interpretation utilises Landsat-8 satellite OLI instrument (as well as the Sentinel-2 series MSI instruments, separate metadata) starting from year 2016.The a spatial resolution of the material is 60 m. Secchi depth is estimated from the satellite instrument observations using a neural network-based model C2RCC (Case-2 Regional CoastColour), (Brockmann et al. 2016). Within the material available by SYKE, however, the final result of the model has been adapted to correspond to the optical properties of the Finnish coast and lake areas. The adaptation is based on field campaigns and station sampling (as exemplified e.g. in Attila et al., 2013 but with MERIS observations). *** ## References/References Attila, J., Koponen, S., Kallio, K., Lindfors, A., Kaitala, S., & Uptalo, P. (2013). Meris Case II water processor comparison on coastal sites of the northern Baltic Sea, Remote Sensing of Environment, 128, 138-149. Brockmann, C & Doerffer, R. (2016). Evolution of the C2RCC neural network for Sentinel 2 and 3 for the retrieval of ocean colour products in normal and extreme optically complex waters. PROC. Living Planet Symposium, ESA SP-470. *** **WMS server/WMS service endpoint**: https://geoserver2.ymparisto.fi/geoserver/eo/wms **WMS level/WMS layer**: EO_HR_WQ_LC8_SDT *** **[EN]** Visual depth data resulting from remote sensing monitoring. Sample data from 2016 onwards on Finnish sea areas and lakes. Processing history: The visual depth has been interpreted from the materials of the Landsat-8 OLI satellite instrument. The original satellite data is downloaded from USGS/NASA download services. In the heart rate, the visual depth data are calculated using the Case-2 Regional CoastColour (C2RCC). *** **[En]** Satellite observations are used to monitor secchi depth. Example data from years 2016- for the Finnish sea areas and lakes. Processing history: The Landsat-8 OLI data have been received from USGS/NASA service. The dataset has been processed to secchi depth values in SYKE using the C2RCC algorithm, which includes atmospheric correction.