Imaging Spectrometry of Inland and Coastal Waters: State of the Art, Achievements and Perspectives

Abstract

Imaging spectrometry of non-oceanic aquatic ecosystems has been in development since the late 1980s when the first airborne hyperspectral sensors were deployed over lakes. Most water quality management applications were, however, developed using multispectral mid-spatial resolution satellites or coarse spatial resolution ocean colour satellites till now. This situation is about to change with a suite of upcoming imaging spectrometers being deployed from experimental satellites or from the International Space Station. We review the science of developing applications for inland and coastal aquatic ecosystems * C. Giardino

Research Trends in the Use of Remote Sensing for Inland Water Quality Science: Moving Towards Multidisciplinary Applications

“…Analytical and semi-analytical models are physics based and involve parameterization based on the inherent optical properties (IOPs) of water and the atmosphere, where IOPs refer to the optical properties of the medium of interest that are independent of the ambient light field [57,69]. The IOPs of a given waterbody are modelled in coordination with apparent optical properties (including illumination conditions, sensor orientation, and field of view) to construct theoretical absorption and backscattering values which can then be decomposed through an inverse equation to estimate optically active water quality constituents (described below) [18,57,70,165]. For purely analytical models, the inverse equation is parameterized based purely on light physics; however, these are rarely used for optically complex waters where the interactions of numerous water quality constituents become difficult to model.…”

“…Early development of semi-analytical modelling for inland waters was led by researchers such as Dekker [26,172] and Kutser [173] [176] applied semi-analytical algorithms across multi-and hyper-spectral data to detect TSS in shallow lagoons. For a more detailed description of semi-analytical modelling, see Peters (2001, 2002) [177,178], Giardino et al (2019) [18], Morel (2001) [165], and IOCCG (2000) [57].…”

“…Ocean color sensors including MODIS, SeaWiFS, and MERIS have higher spectral resolution and frequent return periods, but they lack the spatial resolution to capture narrower inland water bodies, particularly rivers (see [4,17] for detailed discussion). The newest generation of sensors has been designed to overcome some of these issues [18,19], though the limited precision of broad spectral bands remains a challenge. While they lack certain band centers useful for inland water remote sensing, new sensors such as the Landsat 8 Operational Land Imager (OLI) and the Sentinel 2 MultiSpectral Instrument (MSI) have increased signal to noise ratios, improved radiometric and temporal resolution, and aerosol-specific bands making them better equipped to handle the size and complexity of inland waters [194,195].…”

“…These airborne campaigns are working towards satellite missions such as NASA's Surface Biology and Geology mission (SBG, in development), Italy's PRecursore IperSpettrale della Missione Applicativa (PRISMA, launched 22 March 2019), Japan's Hyperspectral Imaging Suite (HISUI, planned 2019), and Germany's Environmental Mapping and Analysis Program (EnMAP, planned 2020) [247]. These spaceborne imaging spectrometers will increase spatiotemporal transferability of retrieval models, improve overall constituent retrieval, facilitate biogeochemical composition analysis, enable benthic habitat identification in optically shallow water bodies, and allow for the retrieval of additional detectable water quality parameters that are currently unfeasible with broadband, multispectral sensors, all while providing global hyperspectral data at roughly 30 m resolution [17,18]. Traditional governmental satellite missions are being supplemented with a host of novel earth observation technologies being developed by commercial companies such as Planet (https://www.planet.com/), MAXAR (https://www.maxar.com/), and Airbus (https://www.airbus.com/).…”

“…Specific studies, sensor information, and modelling approaches focusing on the listed parameters and included in the review can be accessed through the inland water quality remote sensing index linked to in Appendix A. For a more detailed, technical discussion of specific algorithms and spectral responses for each parameter, see Matthews (2011) [4], Gholizadeh et al (2016) [3], and Giardino et al (2019) [18]. Table S2: Summary of the common approaches to algorithm development for remote sensing of inland waters studies.…”