Interactive Online Maps Make Satellite Ocean Data Accessible

The number of active satellite Earth observation missions has increased in recent years, and more missions are coming soon. This wealth of missions is allowing scientists to pay closer attention to ocean color, a vital indicator of the state of Earth’s environment. However, one often overlooked aspect of Earth observation from space is the sheer amount of data that such missions produce daily and how to provide the easiest access to the most relevant data for the widest viewership.

The mapping community has come up with elegant solutions for displaying scalable interactive maps online using such Web development libraries as OpenLayers. Some of the excellent online resources that use this framework to serve a variety of Earth science data products include NASA Worldview, NOAA View, and the Ocean Colour CCI web GIS portal hosted by the Plymouth Marine Laboratory in the United Kingdom.

The Ocean Color Viewer is primarily designed to interactively display sensor-specific satellite ocean color products.

Although the Ocean Color Viewer (OCView) resource from the National Oceanic and Atmospheric Administration (NOAA) shares some similarities with the others, it is primarily designed to interactively display sensor-specific satellite ocean color products. Within this particular focus area, it is very adaptable, making it easy to add and display new data. Thus, it is useful not only as a visualization platform for established data products but also as a tool for quality monitoring and evaluation of routine and experimental data products. Interactive imagery makes it easy to spot artifacts with spatial correlations, and it enables imagery intercomparisons.

A Brief History of Ocean Color Observations from Space

The Coastal Zone Color Scanner (CZCS, 1978–1986) performed the first satellite-based ocean color measurements. It was followed by the Sea-viewing Wide Field-of-view Sensor (SeaWiFS, 1997–2010). Two Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the Terra (1999 to present) and Aqua (2002 to present) satellites added more spectral bands. The Medium Resolution Imaging Spectrometer (MERIS, 2002–2012) on Envisat and the recently launched Ocean and Land Colour Instrument (OLCI, 2016 to present) on Sentinel-3A are notable European contributions to ocean color observation.

The Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Suomi National Polar-orbiting Partnership (Suomi NPP) satellite was launched on 28 October 2011. This satellite flies in a polar Sun-synchronous orbit. It sees Earth’s entire surface every day, and it passes over the equator around the same local time in the afternoon. VIIRS-Suomi NPP is the first satellite sensor in a series designed to ensure continuous consistent Earth observations, and it is currently the main workhorse for ocean color observations at NOAA.

With the emphasis on complete daily global coverage and good radiometric accuracy, most of the VIIRS bands have a moderate spatial resolution of 750 meters, an adequate resolution for studies of the global open ocean. Additional imagery bands with a spatial resolution of 375 meters are particularly useful for measurements over coastal and inland waters. VIIRS is the primary data source for OCView, which features the satellite’s mission-long imagery archive, and OCView is updated daily with new data.

Interactive Design with Layers of Imagery

The main part of the OCView page is the interactive map (Figure 1), which includes a zoom control, scale indicator, and a date/location indicator. OCView displays imagery in both the geographic and polar (Arctic and Antarctic) projections. The panel on the bottom of the OCView page allows selection of the particular type of data to be displayed, the imagery projection, and selection of the date for display. In the geographic projection, which spans longitudes from –180° to +180°, images from consecutive days are displayed side by side, allowing a continuous display of data across the 180th meridian, an important capability for studies that include this region. Any selection of options, as well as the date and center position of the map, is stored in permalink.

OCView page layout showing true-color satellite images with a chlorophyll a data overlay derived from ocean color imagery — Fig. 1. This OCView page layout shows VIIRS global true-color imagery overlaid with the corresponding chlorophyll a data (green and blue areas corresponding to the color scale) derived from ocean color imagery. The true-color image layer shows land areas and areas where cloud cover, high Sun glint, sea ice, or other factors prevent the derivation of ocean color data. In geographic projection (main panel), the imagery is continuous across the 180th meridian. Panels on the right show the data from the same day in Arctic and Antarctic polar projections.

The major strength of interactive online mapping resources is the ability to superimpose different types of imagery and data layers to form a more informative picture.

The major strength of interactive online mapping resources is the ability to superimpose different types of imagery and data layers to form a more informative picture. OCView currently supports two distinct types of satellite imagery: true-color and ocean color data products. Additional data layers include the land mask base layer and the shorelines overlay for geographic context, as well as latitude and longitude grid lines. The overlay of data granule boundaries allows users to identify the acquisition time for a particular location and day, and it provides a direct link to the corresponding ocean color data on the NOAA CoastWatch FTP site.

Earth in True Color

True-color images are derived from light reflected by Earth’s land, oceans, clouds, and other features, as seen from space. Images are constructed from light in the red, green, and blue spectral bands that has been corrected for Rayleigh scattering (the same type of light scattering that makes the sky appear blue to observers on the ground).

Thus, true-color images roughly represent Earth’s appearance as seen from just above the clouds, and they can be further enhanced to emphasize the features of the darker ocean surface. True-color imagery is only a qualitative indicator for ocean color, but this imagery also reveals a much wider range of phenomena over the land, in the ocean, and in the atmosphere (Figure 2).

Samples of VIIRS true-color satellite images from around the world — Fig. 2. Samples of VIIRS true-color imagery for (a) sea ice east of Labrador on 19 April 2017, (b) cloud vortices downwind from the Canary Islands on 8 June 2017, (c) sand blown from the Sahara over the Atlantic Ocean on 27 February 2015, (d) sediment plumes near the Mississippi River delta on 24 January 2017, (e) an algae bloom near Argentina on 14 April 2016, and (f) wildfires in California on 12 December 2017.

Seeing Ocean Color Through the Atmosphere

Measuring an ocean’s color from space requires observers to account for light absorption and scattering in the atmosphere and reflection at the water surface. This procedure is known as atmospheric correction [International Ocean-Color Coordinating Group, 2010], and it produces the spectral properties of the surface water layer. These data are known as the normalized water-leaving radiance spectra, and they determine the ocean color by factoring out the influence of the solar angle, viewing angles, and sky conditions.

Ocean color spectra can subsequently be related to various water biological and biogeochemical properties, such as chlorophyll a concentration [O’Reilly et al., 1998] and the water diffuse attenuation coefficient at the 490-nanometer wavelength [Wang et al., 2009], which quantifies the water turbidity. Thus, applying an accurate atmospheric correction algorithm is of paramount importance, and it is the subject of active research.

OCView showcases imagery derived with different retrieval algorithms and data streams. For VIIRS, the main data streams are the near-real-time data stream, which provides data with about a 12-hour delay, and the more accurate science-quality data streams, which have a longer delay. The science-quality data streams are obtained using various atmospheric correction algorithms, and they have improved sensor calibration and more accurate ancillary data. The science-quality data are periodically reprocessed to reflect the improvements in algorithms and sensor calibration, and the OCView imagery is then also updated.

OCView also features several experimental data products. For example, the chlorophyll a anomaly has been linked to algal bloom outbreaks [Stumpf et al., 2003], some of which may be toxic to marine life. Although most of the ocean color products are mapped in about 2-kilometer resolution, some data derived from VIIRS imagery bands are mapped at around 300-meter spatial resolution—the same scale as the true-color imagery (Figure 3).

Color-coded satellite data map of turbid waters in the Bohai Sea and Yellow Sea in February 2017 — Fig. 3. OCView can display a map of normalized water-leaving radiance (nLw, an indicator of water column properties) at the 638-nanometer wavelength, derived from the VIIRS I1 band. The brown areas in the background are true color. This image shows the turbid waters in the Bohai Sea and Yellow Sea, between China and the Korean Peninsula, on 14 March 2017.

Making a More Complete Picture

Many factors limit the ocean color measurements from space, including atmospheric conditions, high Sun glint, and high solar and sensor zenith angles. For some locations, it can take several satellite passes over a period of weeks to get a single ocean color retrieval. Averages over 8-day and monthly time periods provide more complete coverage and a clearer picture of the most prominent ocean features, but they do so at the cost of reduced spatial and temporal resolution (Figure 4).

OCView maps show four time averages for the VIIRS-derived chlorophyll a concentration in the world’s oceans — Fig. 4. OCView maps show four time averages for the VIIRS-derived chlorophyll a (Chl-a) concentration: (a) daily average, which may include orbit overlaps, (b) 8-day average, (c) monthly average, and (d) climatology derived from the mission-long data record. Note how areas with difficult retrieval conditions, such as polar and inland waters, are progressively revealed in longer time averages.

Several new missions promise to provide more data and bring scientists closer to continuous observation capability. NOAA-20, the follow-on to Suomi NPP that was launched on 18 November 2017, is carrying another VIIRS instrument. The true-color imagery from NOAA-20 VIIRS has been available on OCView since the first day of observations. The European Space Agency (ESA) and European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) launched Sentinel-3A carrying the OLCI on 16 February 2016, and it is flying in a polar Sun-synchronous orbit with a morning equator overpass (Figure 5). OCView has been one of the first platforms to display the OLCI true-color and OLCI Level-2 ocean color data product imageries.

OCView composite showing land mask base layer, true-color composite image, and chlorophyll a concentrations for 6 July 2017 — Fig. 5. Global true-color composite image shown by OCView, overlaid with chlorophyll a concentrations, derived from Sentinel-3A OLCI data acquired on 6 July 2017, with the land mask base layer in gray. The narrower observation swath from OLCI leaves gaps between adjacent orbits, which will be partially filled with data from its twin, the Sentinel-3B OLCI satellite, once it becomes operational (expected in 2018).

The NOAA OCView resource provides easy online access to satellite ocean color data for monitoring and studying global ocean and coastal and inland water features.

This is an exciting time for ocean color research and applications, with new satellite sensors making large amounts of new data available to the research and operational communities. The NOAA OCView resource provides easy online access to satellite ocean color data for monitoring and studying global ocean and coastal and inland water features. This resource is not only educational but also a powerful tool for ocean color research and operational monitoring. With additions of new data products from the existing and upcoming satellite sensors, OCView is becoming a more mature and powerful platform for satellite ocean color data visualization, monitoring, and comparison.

Acknowledgments

This work was supported by funding from the Joint Polar Satellite System (JPSS). The views, opinions, and findings contained in this paper are those of the authors and should not be construed as an official NOAA or U.S. government position, policy, or decision.

References

International Ocean-Color Coordinating Group (2010), Atmospheric Correction for Remotely-Sensed Ocean Colour Products, edited by M. Wang, Rep. Int. Ocean-Color Coord. Group 10, Dartmouth, NS, Canada, http://www.ioccg.org/reports/report10.pdf.

O’Reilly, J. E., et al. (1998), Ocean color chlorophyll algorithms for SeaWiFS, J. Geophys. Res., 103(C11), 24,937–24,953, https://doi.org/10.1029/98JC02160.

Stumpf, R. P., et al. (2003), Monitoring blooms in the Gulf of Mexico using satellite ocean color imagery and other data, Harmful Algae, 2, 147–160, https://doi.org/10.1016/S1568-9883(02)00083-5.

Wang, M., S. Son, and L. W. Harding Jr. (2009), Retrieval of diffuse attenuation coefficient in the Chesapeake Bay and turbid ocean regions for satellite ocean color applications, J. Geophys. Res., 114, C10011, https://doi.org/10.1029/2009JC005286.

Author Information

Karlis Mikelsons (email: karlis.mikelsons@noaa.gov), Center for Satellite Applications and Research, National Environmental Satellite, Data, and Information Service (NESDIS), National Oceanic and Atmospheric Administration (NOAA), College Park, Md.; also at Global Science and Technology, Inc., Greenbelt, Md.; and Menghua Wang, Center for Satellite Applications and Research, NESDIS, NOAA, College Park, Md.

Correction, 1 May 2018: An earlier version of this article contained several incorrect dates in the figure captions. These dates have been corrected.

Citation:

Mikelsons, K.,Wang, M. (2018), Interactive online maps make satellite ocean data accessible, Eos, 99, https://doi.org/10.1029/2018EO096563. Published on 01 May 2018.

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