# A New Orbiting Deployable System for Small Satellite Observations for Ecology and Earth Observation
## 3 Study Cases
### Application 4: Posidonia Oceanica Monitoring  
_Posidonia oceanica_ (L). Delile, an endemic seagrass of the Mediterranean Sea, forms extensive meadows, which are among the most efficient ecosystems on the planet in terms of the number of services per area [189; 190; 191; 192; 193; 194]. These include the stabilization of the sediment and the mitigation of hydrodynamic stress on the coastline, by protecting it from erosive processes (e.g., [195; 196; 197; 198]). At the same time, _P. oceanica_ meadows are essential for preserving coastal biodiversity and natural resources, and are serviceable for nursery grounds and fish habitats [193; 200; 201]. Additionally, they represent one of the largest carbon supplies in the Mediterranean Sea [201; 202] and other shallow coastal areas across the world [203]. _P. oceanica_ meadows can extend from the surface down to 35-40 m deep, depending mostly upon water transparency, and they colonize multiple substrates (e.g., [195; 196; 204]). The variation of the geomorphological, chemical, and physical characteristics that follow one another along the environmental gradients (e.g., bathymetric variations) determine very heterogeneous grasslands in terms of density, biomass, and associated fauna (e.g., [204]). In recent decades, _P. oceanica_ underwent a gradual areal regression, by as much as \(\sim\)34% in the Mediterranean basin, and 25% in the Italian seas, when comparing historical and the early 2000s maps (e.g., [205]). This regression was caused by anthropogenic processes including fish farm activities, such as trawling and anchoring, gas pipeline refilling, and polluting agents in the coastal areas [205; 206; 198; 207; 208]. An updated database is thus crucial to study the evolution of the ecosystems formed by the meadows [209], and to safeguard and manage such habitats and biodiversity [189; 180]. Remote sensing would be very effective in obtaining a spatial and temporal survey of the meadows, through the generation of a broad and synoptic view of the coastal system, and a complete study of biotic and abiotic variables [200; 211; 212; 213; 214]. Aquatic ecosystems are indeed characterized by strong optical signals deriving from the distinctive photosynthetic pigments of the various plant groups, from phytoplankton to submerged or emerged macroalgae, from marine phanerogams to coastal-terrestrial plants [215]. However, a good optical depth of water is a necessary condition for mapping the meadows on the sea floor, urging the emergency of contrasting coastal pollution and anthropogenic activities [200]. The evolution of the _P. oceanica_ and their erosion can be then modelled from the optical images (once they have been geometrically and radiometrically corrected, e.g., [213]) by means of machine learning techniques (e.g., [216; 217; 218]). Additionally, biotic properties of meadows (primary production and density) and abiotic factors (turbidity, bathymetry, and the presence of suspended solids) can be identified in the processed images as geomorphological characterization of the coastal area (e.g., [194]). The predicted complexity and diversity of the _P. oceanica_ environment requires spatial resolutions down a few meters (e.g., [219]). For a detailed _P. oceanica_ mapping, remote sensing images at a spatial resolution of about 1 m at nadir in the panchromatic (0.45-0.8 \(\upmu\)m), and 2 m at nadir in the multispectral filter band are demanded for an accurate mapping of the meadows. At the same time, a high spectral resolution is required for a finer ocean color acquisition and the correct identification and mapping of the grassland. The multispectral band should include eight filters: (i) 'Blue' (0.45-0.51 \(\upmu\)m) and (ii) 'Green' (0.51-0.58 \(\upmu\)m), which are reflected by the water column and leaves of _P.