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The project “Novel estimation of shallow water bathymetry using ICESat-2 laser altimetry, signal processing and machine learning and Sentinel-2 optical data in a highly automated approach” was funded under the European Space Agencies’ Open Space Innovation Platform (OSIP). The overall objective was to build a self-calibrating and efficient bathymetry mapping system by leveraging accurate and consistent ICESat-2 laser altimeter data as a calibration source for high-resolution Copernicus Sentinel-2 based water depth retrievals.

“Remote Sensing for Marine Litter - RESMALI” has identified the ideal parameters to study marine litter (ML) from space, including spectral bands with affordable signal-to-noise ratio (SNR) at top-of-atmosphere (TOA) level, in a range of wavelengths from visible to SWIR. To continue this path towards a dedicated mission, performance assessment against simulated real-case scenarios of ML is key. We want to build a simulator to estimate ML signal at TOA from a set of scenarios representing the various applications already targeted by the community (e.g.

The focus of study is to build near-IR capability onto Si CCDs for Time-Delay-Integration (TDI) applications, with the main requirement being charge domain summation, which allows the lowest noise performance on these types of devices. Currently there is no product that exists to do this. Si CCDs are a well-established technology which, whilst being an “old” technology, are still world leading in certain applications up to a wavelength of ~1μm.

Detecting, identifying, quantifying and tracking strategies for leakage plastic litter in terrestrial as well as aquatic environments using remote sensing technologies is expected to support future continuous monitoring of waste pollution at wide covering geo-spatial scales.