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  • As the foundation of the aquatic food chain, phytoplankton are an integral part of the ecosystem, affecting trophic dynamics, nutrient cycling, habitat condition, light availability and fisheries resources. Chlorophyll-a, which is the primary light-harvesting pigment, is a proxy of phytoplankton biomass, and of trophic status. Earth observation techniques are a step forward for phytoplankton mapping, going beyond the local-scale and supporting regional to continental monitoring of the spatial and temporal dynamics of primary producers in freshwater ecosystems. Chlorophyll-a concentration maps are derived by CNR from an APEX image (airborne hyperspectral imager; 2016/09/01), and from two Sentinel-2(Contains modified Copernicus Sentinel data 2015-2016) images (2015/08/17; 2016/08/24) of the Curonian Lagoon in Lithuania.

  • Phytoplankton are an indicator of trophic status (water ecosystem productivity); a temporal shifting of bloom phenology as well as the spreading of cyanobacterial blooms might be an indicator of a lake’s response to climate change. The occurrence of harmful algal blooms (HABs) – also often associated with cyanobacteria – might hinder the use of water resources. The measurement of Phytoplankton pigments and functional types is therefore a key part of water quality monitoring programs worldwide. Maps of scum events in the Curonian Lagoon (Lithuania) are derived by CNR from a series of Landsat-8 (data courtesy of U.S. Geological Survey) images acquired in the period June-October (from 2013 to 2016), and from a Sentinel-2(Contains modified Copernicus Sentinel data 2015) image acquired in 2015/08/10. The phycocyanin map, a pigment typical of cyanobacteria species, is derived from an APEX image (airborne hyperspectral imager) of the Curonian Lagoon acquired in 2016/09/01.

  • Turbidity maps of the Po River (potamal zone and delta) in Italy are derived by CNR from six Landsat-8(data courtesy of U.S. Geological Survey) images (2014/03/08; 201/11/19; 2014/12/12; 2015/01/13; 2015/03/18), and from four Sentinel-2(Contains modified Copernicus Sentinel data 2015-2016) images (2015/08/20; 2016/01/17; 2016/08/14; 2016/12/22).

  • This time series of suspended sediment maps is derived by VITO from Landsat-8(data courtesy of U.S. Geological Survey) OLI and Sentinel-2 MSI (Contains modified Copernicus Sentinel data 2016) imagery over Lake Marken, covering a time period from 2013 – 2016.

  • Quantification of available light in the water column is key to evaluating water quality in lakes as it is one of the major factors determining primary production. The light environment in water is generally described in terms of the vertical attenuation coefficient (Kd) or the euphotic depth (Ze) defined as the depth where the light is reduced to 1% of its (just below) surface value. Remote sensing reflectance can be used to determine Kd and Ze with the quasi-analytical algorithms (QAA). Kd and Ze can be determined from remote sensing reflectance data through quasi-analytical algorithms (QAA). The QAA, originally developed for ocean colour sensors such as MERIS/MODIS, is desiged to derive absorption (a) and backscatter (bb) coefficients by inverting remote sensing reflectance (Rrs). The absorption and backscatter coefficients are subsequently used to estimate Kd. In INFORM this algorithm was adapted to be used for new sensors such as Landsat-8 (data courtesy of U.S. Geological Survey) OLI and Sentinel-2 (Contains modified Copernicus Sentinel data 2016) MSI for inland water cases. The QAA was refined by performing a spectral shift to the Rrs data to simulate MERIS-like bands from the Landsat-8 OLI and Sentinel-2 MSI data.

  • This suspended sediment map is derived by VITO from a Landsat-8 OLI image (data courtesy of U.S. Geological Survey) of the Gironde river in France acquired at 17/05/2014. More work on the Gironde river is published in E. Knaeps, , K.G. Ruddick, D. Doxaran, A.I. Dogliotti, B. Nechad, D. Raymaekers, S. Sterckx, A SWIR based algorithm to retrieve total suspended matter in extremely turbid waters, Remote Sensing of Environment Volume 168, October 2015, Pages 66–79; doi:10.1016/j.rse.2015.06.022.

  • To effectively monitor macrophytes in inland water ecosystems it is crucial to retrieve information on the spatio-temporal dynamics of some key biophysical parameters. Macrophyte biophysical parameters (BPs) of main interest from the point of view of monitoring by remote sensing are those related to biomass and density. Satellite imagery is used to map the extent and distribution of macrophytes, and to assess the presence of invasive species. Vegetation indices and in situ data are used to calibrate semi-empirical models for mapping fractional cover (fC), and above-water biomass (AWBiomass; dry weight). The approach is limited emergent, free floating and floating-leaved plants. Macrophyte fractional cover and above water biomass maps are derived by CNR from an APEX image (airborne hyperspectral imager; 2014/09/27), and from three Sentinel-2 (Contains modified Copernicus Sentinel data 2015-2016) images (2015/08/03; 2016/05/22; 2016/07/28) of the Mantua Lakes system (Italy).

  • Macrophytes are important components of inland freshwater ecosystems playing a significant role in the global carbon and nutrient cycles, as well as in the provision of suitable niches for nursery and feeding activities for several aquatic faunal species and threatened taxa. Earth observation techniques are a step forward for macrophyte mapping (extent, density and distribution), going beyond the local-scale and supporting regional to continental monitoring of the spatial and temporal dynamics of primary producers in freshwater ecosystems. Satellite imagery is used to map the extent and distribution of macrophytes, and to assess the presence of invasive species. A rule-based classification scheme was implemented for mapping four macrophyte community types (helophyte, emergent rhizophyte, floating, and submerged-floating association). Macrophyte community types mapping is derived by CNR from a series of Landsat-8 (data courtesy of U.S. Geological Survey) images of the Kis-Balaton wetland acquired during the growing season of 2014 and 2016.

  • Macrophytes are important components of inland freshwater ecosystems playing a significant role in the global carbon and nutrient cycles, as well as in the provision of suitable niches for nursery and feeding activities for several aquatic faunal species and threatened taxa. Earth observation techniques are a step forward for macrophyte mapping (extent, density and distribution), going beyond the local-scale and supporting regional to continental monitoring of the spatial and temporal dynamics of primary producers in freshwater ecosystems. Satellite imagery is used to map the extent and distribution of macrophytes, and to assess the presence of invasive species. A rule-based classification scheme was implemented for mapping four macrophyte community types (helophyte, emergent rhizophyte, floating, and submerged-floating association). Macrophyte community types mapping is derived by CNR from a series of Landsat-8(data courtesy of U.S. Geological Survey) images of the Mantua Lakes system acquired during the growing season of 2014 and 2016.

  • Phytoplankton are an indicator of trophic status (water ecosystem productivity); a temporal shifting of bloom phenology as well as the spreading of cyanobacterial blooms might be an indicator of a lake’s response to climate change. The occurrence of harmful algal blooms (HABs) – also often associated with cyanobacteria – might hinder the use of water resources. The measurement of Phytoplankton pigments and functional types is therefore a key part of water quality monitoring programs worldwide. The phycocyanin map, a pigment typical of cyanobacteria species, is derived by CNR from an APEX image (airborne hyperspectral imager) of the Mantua Lakes (Italy) acquired in 2011/09/21. Maps of phytoplankton functional types in the Mantua Lakes are derived from an APEX image (2014/09/27), and from two Sentinel-2(Contains modified Copernicus Sentinel data 2016) images acquired in July (28th) and September (19th) 2016.