92 research outputs found

    Hydrographic remote sensing made in Germany

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    Feasibility Study for an Aquatic Ecosystem Earth Observing System Version 1.2.

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    International audienceMany Earth observing sensors have been designed, built and launched with primary objectives of either terrestrial or ocean remote sensing applications. Often the data from these sensors are also used for freshwater, estuarine and coastal water quality observations, bathymetry and benthic mapping. However, such land and ocean specific sensors are not designed for these complex aquatic environments and consequently are not likely to perform as well as a dedicated sensor would. As a CEOS action, CSIRO and DLR have taken the lead on a feasibility assessment to determine the benefits and technological difficulties of designing an Earth observing satellite mission focused on the biogeochemistry of inland, estuarine, deltaic and near coastal waters as well as mapping macrophytes, macro-algae, sea grasses and coral reefs. These environments need higher spatial resolution than current and planned ocean colour sensors offer and need higher spectral resolution than current and planned land Earth observing sensors offer (with the exception of several R&D type imaging spectrometry satellite missions). The results indicate that a dedicated sensor of (non-oceanic) aquatic ecosystems could be a multispectral sensor with ~26 bands in the 380-780 nm wavelength range for retrieving the aquatic ecosystem variables as well as another 15 spectral bands between 360-380 nm and 780-1400 nm for removing atmospheric and air-water interface effects. These requirements are very close to defining an imaging spectrometer with spectral bands between 360 and 1000 nm (suitable for Si based detectors), possibly augmented by a SWIR imaging spectrometer. In that case the spectral bands would ideally have 5 nm spacing and Full Width Half Maximum (FWHM), although it may be necessary to go to 8 nm wide spectral bands (between 380 to 780nm where the fine spectral features occur -mainly due to photosynthetic or accessory pigments) to obtain enough signal to noise. The spatial resolution of such a global mapping mission would be between ~17 and ~33 m enabling imaging of the vast majority of water bodies (lakes, reservoirs, lagoons, estuaries etc.) larger than 0.2 ha and ~25% of river reaches globally (at ~17 m resolution) whilst maintaining sufficient radiometric resolution

    The CEOS Feasibility Study for an aquatic ecosystem imaging spectrometer

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    The Committee on Earth Observation Satellites (CEOS) response to the Group on Earth Observations System of Systems (GEOSS) Water Strategy developed under the auspices of the Water Strategy Implementation Study Team was endorsed by CEOS at the 2015 Plenary. As one of the actions, CSIRO has taken the lead on recommendation C.10: A feasibility assessment to determine the benefits and technological difficulties of designing a hyperspectral satellite mission focused on water quality measurements. More specifically this report is a highlevel feasibility assessment of the benefits and technological difficulties of designing a hyperspectral satellite mission focused on biogeochemistry of inland, estuarine, deltaic and near coastal waters as well as mapping macrophytes, macroalgae , seagrasses and coral reefs at significantly higher spatial resolution than 250 m, which is the maximum spatial resolution of dedicated current aquatic sensors such as Sentinel3 and future planned aquatic sensors such as the Coastal Ocean Color Imager (COCI – 100 m res). Further, the GEO Community of Practice Aquawatch suggested that alternative approaches, involving augmenting designs of spaceborne sensors for terrestrial and ocean colour applications to allow improved inland, near coastal waters and benthic applications, could offer an alternative pathway to addressing the same underlying science questions. Accordingly, this study also analizes the benefits and technological difficulties of this option as part of the highlevel feasibility study

    Mapping of submerged aquatic vegetation using hyperspectral airborne data and a physically based process chain

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