| 1. |
|
|
| 2. |
- Valente, Andre, et al.
(författare)
-
A compilation of global bio-optical in situ data for ocean-colour satellite applications
- 2016
-
Ingår i: Earth System Science Data. - : Copernicus GmbH. - 1866-3508 .- 1866-3516. ; 8:1, s. 235-252
-
Tidskriftsartikel (refereegranskat)abstract
- A compiled set of in situ data is important to evaluate the quality of ocean-colour satellite-data records. Here we describe the data compiled for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The data were acquired from several sources (MOBY, BOUSSOLE, AERONET-OC, SeaBASS, NOMAD, MERMAID, AMT, ICES, HOT, GeP&CO), span between 1997 and 2012, and have a global distribution. Observations of the following variables were compiled: spectral remote-sensing reflectances, concentrations of chlorophyll a, spectral inherent optical properties and spectral diffuse attenuation coefficients. The data were from multi-project archives acquired via the open internet services or from individual projects, acquired directly from data providers. Methodologies were implemented for homogenisation, quality control and merging of all data. No changes were made to the original data, other than averaging of observations that were close in time and space, elimination of some points after quality control and conversion to a standard format. The final result is a merged table designed for validation of satellite-derived ocean-colour products and available in text format. Metadata of each in situ measurement (original source, cruise or experiment, principal investigator) were preserved throughout the work and made available in the final table. Using all the data in a validation exercise increases the number of matchups and enhances the representativeness of different marine regimes. By making available the metadata, it is also possible to analyse each set of data separately. The compiled data are available at doi: 10.1594/PANGAEA.854832 (Valente et al., 2015).
|
|
| 3. |
- Valente, André, et al.
(författare)
-
A compilation of global bio-optical in situ data for ocean-colour satellite applications - version two
- 2019
-
Ingår i: Earth System Science Data. - : Copernicus GmbH. - 1866-3508 .- 1866-3516. ; 11:3, s. 1037-1068
-
Tidskriftsartikel (refereegranskat)abstract
- A global compilation of in situ data is useful to evaluate the quality of ocean-colour satellite data records. Here we describe the data compiled for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The data were acquired from several sources (including, inter alia, MOBY, BOUSSOLE, AERONET-OC, SeaBASS, NOMAD, MERMAID, AMT, ICES, HOT and GeP&CO) and span the period from 1997 to 2018. Observations of the following variables were compiled: spectral remote-sensing reflectances, concentrations of chlorophyll a, spectral inherent optical properties, spectral diffuse attenuation coefficients and total suspended matter. The data were from multi-project archives acquired via open internet services or from individual projects, acquired directly from data providers. Methodologies were implemented for homogenization, quality control and merging of all data. No changes were made to the original data, other than averaging of observations that were close in time and space, elimination of some points after quality control and conversion to a standard format. The final result is a merged table designed for validation of satellite-derived ocean-colour products and available in text format. Metadata of each in situ measurement (original source, cruise or experiment, principal investigator) was propagated throughout the work and made available in the final table. By making the metadata available, provenance is better documented, and it is also possible to analyse each set of data separately. This paper also describes the changes that were made to the compilation in relation to the previous version (Valente et al., 2016). The compiled data are available at https://doi.org/10.1594/PANGAEA.898188 (Valente et al., 2019).
|
|
| 4. |
|
|
| 5. |
- Muelbert, Jose H., et al.
(författare)
-
ILTER : The International Long-Term Ecological Research Network as a Platform for Global Coastal and Ocean Observation
- 2019
-
Ingår i: Frontiers in Marine Science. - : Frontiers Media S.A.. - 2296-7745. ; 6
-
Forskningsöversikt (refereegranskat)abstract
- Understanding the threats to global biodiversity and ecosystem services posed by human impacts on coastal and marine environments requires the establishment and maintenance of ecological observatories that integrate the biological, physical, geological, and biogeochemical aspects of ecosystems. This is crucial to provide scientists and stakeholders with the support and knowledge necessary to quantify environmental change and its impact on the sustainable use of the seas and coasts. In this paper, we explore the potential for the coastal and marine components of the International Long-Term Ecological Research Network (ILTER) to fill this need for integrated global observation, and highlight how ecological observations are necessary to address the challenges posed by climate change and evolving human needs and stressors within the coastal zone. The ILTER is a global network encompassing 44 countries and 700 research sites in a variety of ecosystems across the planet, more than 100 of which are located in coastal and marine environments (ILTER-CMS). While most of the ILTER-CMS were established after the year 2000, in some cases they date back to the early 1900s. At ILTER sites, a broad variety of abiotic and biotic variables are measured, which may feed into other global initiatives. The ILTER community has produced tools to harmonize and compare measurements and methods, allowing for data integration workflows and analyses between and within individual ILTER sites. After a brief historical overview of ILTER, with emphasis on the marine component, we analyze the potential contribution of the ILTER-CMS to global coastal and ocean observation, adopting the "Strength, Weakness, Opportunity and Threats (SWOT)" approach. We also identify ways in which the in situ parameters collected at ILTER sites currently fit within the Essential Ocean Variables framework (as proposed by the Framework for Ocean Observation recommendations) and provide insights on the use of new technology in long-term studies. Final recommendations point at the need to further develop observational activities at LTER sites and improve coordination among them and with external related initiatives in order to maximize their exploitation and address present and future challenges in ocean observations.
|
|
| 6. |
- Sathyendranath, Shubha, et al.
(författare)
-
An Ocean-Colour Time Series for Use in Climate Studies : The Experience of the Ocean-Colour Climate Change Initiative (OC-CCI)
- 2019
-
Ingår i: Sensors. - : MDPI AG. - 1424-8220. ; 19:19
-
Tidskriftsartikel (refereegranskat)abstract
- Ocean colour is recognised as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS); and spectrally-resolved water-leaving radiances (or remote-sensing reflectances) in the visible domain, and chlorophyll-a concentration are identified as required ECV products. Time series of the products at the global scale and at high spatial resolution, derived from ocean-colour data, are key to studying the dynamics of phytoplankton at seasonal and inter-annual scales; their role in marine biogeochemistry; the global carbon cycle; the modulation of how phytoplankton distribute solar-induced heat in the upper layers of the ocean; and the response of the marine ecosystem to climate variability and change. However, generating a long time series of these products from ocean-colour data is not a trivial task: algorithms that are best suited for climate studies have to be selected from a number that are available for atmospheric correction of the satellite signal and for retrieval of chlorophyll-a concentration; since satellites have a finite life span, data from multiple sensors have to be merged to create a single time series, and any uncorrected inter-sensor biases could introduce artefacts in the series, e.g., different sensors monitor radiances at different wavebands such that producing a consistent time series of reflectances is not straightforward. Another requirement is that the products have to be validated against in situ observations. Furthermore, the uncertainties in the products have to be quantified, ideally on a pixel-by-pixel basis, to facilitate applications and interpretations that are consistent with the quality of the data. This paper outlines an approach that was adopted for generating an ocean-colour time series for climate studies, using data from the MERIS (MEdium spectral Resolution Imaging Spectrometer) sensor of the European Space Agency; the SeaWiFS (Sea-viewing Wide-Field-of-view Sensor) and MODIS-Aqua (Moderate-resolution Imaging Spectroradiometer-Aqua) sensors from the National Aeronautics and Space Administration (USA); and VIIRS (Visible and Infrared Imaging Radiometer Suite) from the National Oceanic and Atmospheric Administration (USA). The time series now covers the period from late 1997 to end of 2018. To ensure that the products meet, as well as possible, the requirements of the user community, marine-ecosystem modellers, and remote-sensing scientists were consulted at the outset on their immediate and longer-term requirements as well as on their expectations of ocean-colour data for use in climate research. Taking the user requirements into account, a series of objective criteria were established, against which available algorithms for processing ocean-colour data were evaluated and ranked. The algorithms that performed best with respect to the climate user requirements were selected to process data from the satellite sensors. Remote-sensing reflectance data from MODIS-Aqua, MERIS, and VIIRS were band-shifted to match the wavebands of SeaWiFS. Overlapping data were used to correct for mean biases between sensors at every pixel. The remote-sensing reflectance data derived from the sensors were merged, and the selected in-water algorithm was applied to the merged data to generate maps of chlorophyll concentration, inherent optical properties at SeaWiFS wavelengths, and the diffuse attenuation coefficient at 490 nm. The merged products were validated against in situ observations. The uncertainties established on the basis of comparisons with in situ data were combined with an optical classification of the remote-sensing reflectance data using a fuzzy-logic approach, and were used to generate uncertainties (root mean square difference and bias) for each product at each pixel.
|
|
| 7. |
- Wei, Jianwei, et al.
(författare)
-
Global satellite water classification data products over oceanic, coastal, and inland waters
- 2022
-
Ingår i: Remote Sensing of Environment. - : Elsevier BV. - 0034-4257 .- 1879-0704. ; 282
-
Tidskriftsartikel (refereegranskat)abstract
- Satellites have generated extensive data of remote sensing reflectance spectra (Rrs(λ)) covering diverse water classes or types across global waters. Spectral classification of satellite Rrs(λ) data allows for the distinguishing and grouping of waters with characteristic bio-optical/biogeochemical features that may influence the productivity of a given water body. This study reports new satellite water class products (Level-2 and Level-3) from the Visible Infrared Imaging Radiometer Suite (VIIRS). We developed and implemented a hyperspectral scheme that accounts for the Rrs(λ) spectral shapes and globally resolves oceanic, coastal, and inland waters into 23 water classes. We characterized the light absorption and scattering coefficients, chlorophyll-a concentration, diffuse attenuation coefficient, and suspended particulate matter for individual water classes. It is shown that the water classes are separable by their distinct bio-optical and biogeochemical properties. Furthermore, validation result suggests that the VIIRS water class products are accurate globally. Finally, we examined the spatial and temporal variability of the water classes in case studies for a demonstration of applications. The water class data in open oceans reveal that the subtropical ocean gyres have experienced dramatic expansion over the last decade. In addition, the water class data appear to be a valuable (and qualitative) indicator for water quality in coastal and inland waters with compelling evidence. We stress that this new satellite product is an excellent addition to the aquatic science database, despite the need for continuous improvement toward perfection.
|
|
