Lide Jiang

Atmospheric correction using near-infrared bands for satellite ocean color data processing in the turbid western Pacific region

A regional near-infrared (NIR) ocean normalized water-leaving radiance (nL(w)(λ)) model is proposed for atmospheric correction for ocean color data processing in the western Pacific region, including the Bohai Sea, Yellow Sea, and East China Sea. Our motivation for this work is to derive ocean color products in the highly turbid western Pacific region using the Geostationary Ocean Color Imager (GOCI) onboard South Korean Communication, Ocean, and Meteorological Satellite (COMS). GOCI has eight spectral bands from 412 to 865 nm but does not have shortwave infrared (SWIR) bands that are needed for satellite ocean color remote sensing in the turbid ocean region. Based on a regional empirical relationship between the NIR nL(w)(λ) and diffuse attenuation coefficient at 490 nm (K(d)(490)), which is derived from the long-term measurements with the Moderate-resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite, an iterative scheme with the NIR-based atmospheric correction algorithm has been developed. Results from MODIS-Aqua measurements show that ocean color products in the region derived from the new proposed NIR-corrected atmospheric correction algorithm match well with those from the SWIR atmospheric correction algorithm. Thus, the proposed new atmospheric correction method provides an alternative for ocean color data processing for GOCI (and other ocean color satellite sensors without SWIR bands) in the turbid ocean regions of the Bohai Sea, Yellow Sea, and East China Sea, although the SWIR-based atmospheric correction approach is still much preferred. The proposed atmospheric correction methodology can also be applied to other turbid coastal regions.

Ocean color products from the Korean Geostationary Ocean Color Imager (GOCI)

The first geostationary ocean color satellite sensor, Geostationary Ocean Color Imager (GOCI), which is onboard South Korean Communication, Ocean, and Meteorological Satellite (COMS), was successfully launched in June of 2010. GOCI has a local area coverage of the western Pacific region centered at around 36°N and 130°E and covers ~2500 × 2500 km(2). GOCI has eight spectral bands from 412 to 865 nm with an hourly measurement during daytime from 9:00 to 16:00 local time, i.e., eight images per day. In a collaboration between NOAA Center for Satellite Applications and Research (STAR) and Korea Institute of Ocean Science and Technology (KIOST), we have been working on deriving and improving GOCI ocean color products, e.g., normalized water-leaving radiance spectra (nLw(λ)), chlorophyll-a concentration, diffuse attenuation coefficient at the wavelength of 490 nm (Kd(490)), etc. The GOCI-covered ocean region includes one of the worlds most turbid and optically complex waters. To improve the GOCI-derived nLw(λ) spectra, a new atmospheric correction algorithm was developed and implemented in the GOCI ocean color data processing. The new algorithm was developed specifically for GOCI-like ocean color data processing for this highly turbid western Pacific region. In this paper, we show GOCI ocean color results from our collaboration effort. From in situ validation analyses, ocean color products derived from the new GOCI ocean color data processing have been significantly improved. Generally, the new GOCI ocean color products have a comparable data quality as those from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the satellite Aqua. We show that GOCI-derived ocean color data can provide an effective tool to monitor ocean phenomenon in the region such as tide-induced re-suspension of sediments, diurnal variation of ocean optical and biogeochemical properties, and horizontal advection of river discharge. In particular, we show some examples of ocean diurnal variations in the region, which can be provided effectively from satellite geostationary measurements.

Improved near-infrared ocean reflectance correction algorithm for satellite ocean color data processing

A new approach for the near-infrared (NIR) ocean reflectance correction in atmospheric correction for satellite ocean color data processing in coastal and inland waters is proposed, which combines the advantages of the three existing NIR ocean reflectance correction algorithms, i.e., Bailey et al. (2010) [Opt. Express18, 7521 (2010)Appl. Opt.39, 897 (2000)Opt. Express20, 741 (2012)], and is named BMW. The normalized water-leaving radiance spectra nLw(λ) obtained from this new NIR-based atmospheric correction approach are evaluated against those obtained from the shortwave infrared (SWIR)-based atmospheric correction algorithm, as well as those from some existing NIR atmospheric correction algorithms based on several case studies. The scenes selected for case studies are obtained from two different satellite ocean color sensors, i.e., the Moderate Resolution Imaging Spectroradiometer (MODIS) on the satellite Aqua and the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (SNPP), with an emphasis on several turbid water regions in the world. The new approach has shown to produce nLw(λ) spectra most consistent with the SWIR results among all NIR algorithms. Furthermore, validations against the in situ measurements also show that in less turbid water regions the new approach produces reasonable and similar results comparable to the current operational algorithm. In addition, by combining the new NIR atmospheric correction with the SWIR-based approach, the new NIR-SWIR atmospheric correction can produce further improved ocean color products. The new NIR atmospheric correction can be implemented in a global operational satellite ocean color data processing system.

Destriping algorithm for improved satellite-derived ocean color product imagery

While modern multi-detector sensors offer a much improved image resolution and signal-to-noise ratio among other performance benefits, the multi-detector arrangement gives rise to striping in satellite imagery due to various sources, which cannot be perfectly corrected by sensor calibration. Recently, Bouali and Ignatov (2014) [J. Atmos. Oceanic Technol., 31, 150-163 (2014)] introduced a new approach to remove relatively small detector performance-related striping from thermal infrared bands for improved sea surface temperature data. We show that this methodology, with appropriately chosen parameters and adjustments, can also be applied to remove striping of a much larger variance from the solar reflective band data. Specifically, we modify and apply this new approach to remove striping from satellite-derived normalized water-leaving radiance spectra nLw(λ) obtained from solar reflective bands. It is important that the destriping approach not be applied to the top-of-atmosphere radiances. The results show a significant improvement in image quality for both nLw(λ) spectra and nLw(λ)-derived ocean biological and biogeochemical products such as chlorophyll-a concentration, and the water diffuse attenuation coefficient at the wavelength of 490 nm Kd(490).

Evaluation of VIIRS ocean color products

The Suomi National Polar-orbiting Partnership (SNPP) was successfully launched on October 28, 2011. The Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi NPP, which has 22 spectral bands (from visible to infrared) similar to the NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS), is a multi-disciplinary sensor providing observations for the Earth’s atmosphere, land, and ocean properties. In this paper, we provide some evaluations and assessments of VIIRS ocean color data products, or ocean color Environmental Data Records (EDR), including normalized water-leaving radiance spectra nLw(λ) at VIIRS five spectral bands, chlorophyll-a (Chl-a) concentration, and water diffuse attenuation coefficient at the wavelength of 490 nm Kd(490). Specifically, VIIRS ocean color products derived from the NOAA Multi-Sensor Level-1 to Level-2 (NOAA-MSL12) ocean color data processing system are evaluated and compared with MODIS ocean color products and in situ measurements. MSL12 is now NOAA’s official ocean color data processing system for VIIRS. In addition, VIIRS Sensor Data Records (SDR or Level- 1B data) have been evaluated. In particular, VIIRS SDR and ocean color EDR have been compared with a series of in situ data from the Marine Optical Buoy (MOBY) in the waters off Hawaii. A notable discrepancy of global deep water Chl-a derived from MODIS and VIIRS between 2012 and 2013 is observed. This discrepancy is attributed to the SDR (or Level-1B data) calibration issue and particularly related to VIIRS green band at 551 nm. To resolve this calibration issue, we have worked on our own sensor calibration by combining the lunar calibration effect into the current calibration method. The ocean color products derived from our new calibrated SDR in the South Pacific Gyre show that the Chl-a differences between 2012 and 2013 are significantly reduced. Although there are still some issues, our results show that VIIRS is capable of providing high-quality global ocean color products in support of science research and operational applications. The VIIRS evaluation and monitoring results can be found at the website: http://www.star.nesdis.noaa.gov/sod/mecb/color/index.html.

NIR- and SWIR-based on-orbit vicarious calibrations for satellite ocean color sensors

The near-infrared (NIR) and shortwave infrared (SWIR)-based atmospheric correction algorithms are used in satellite ocean color data processing, with the SWIR-based algorithm particularly useful for turbid coastal and inland waters. In this study, we describe the NIR- and two SWIR-based on-orbit vicarious calibration approaches for satellite ocean color sensors, and compare results from these three on-orbit vicarious calibrations using satellite measurements from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP). Vicarious calibration gains for VIIRS spectral bands are derived using the in situ normalized water-leaving radiance nLw(λ) spectra from the Marine Optical Buoy (MOBY) in waters off Hawaii. The SWIR vicarious gains are determined using VIIRS measurements from the South Pacific Gyre region, where waters are the clearest and generally stable. Specifically, vicarious gain sets for VIIRS spectral bands of 410, 443, 486, 551, and 671 nm derived from the NIR method using the NIR 745 and 862 nm bands, the SWIR method using the SWIR 1238 and 1601 nm bands, and the SWIR method using the SWIR 1238 and 2257 nm bands are (0.979954, 0.974892, 0.974685, 0.965832, 0.979042), (0.980344, 0.975344, 0.975357, 0.965531, 0.979518), and (0.980820, 0.975609, 0.975761, 0.965888, 0.978576), respectively. Thus, the NIR-based vicarious calibration gains are consistent with those from the two SWIR-based approaches with discrepancies mostly within ~0.05% from three data processing methods. In addition, the NIR vicarious gains (745 and 862 nm) derived from the two SWIR methods are (0.982065, 1.00001) and (0.981811, 1.00000), respectively, with the difference ~0.03% at the NIR 745 nm band. This is the fundamental basis for the NIR-SWIR combined atmospheric correction algorithm, which has been used to derive improved satellite ocean color products over open oceans and turbid coastal/inland waters. Therefore, a unified vicarious gain set for VIIRS bands M1-M8 and M10-M11 has been implemented in the VIIRS ocean color data processing. Using the unified vicarious gain set, VIIRS mission-long ocean color data have been successfully reprocessed using the NIR-, SWIR-, and NIR-SWIR-based atmospheric correction algorithms.

Technique for monitoring performance of VIIRS reflective solar bands for ocean color data processing

A technique for monitoring and evaluating the performance of on-orbit calibration for satellite ocean color sensors has been developed. The method is based on the sensor on-orbit vicarious calibration approach using in situ ocean optics measurements and radiative transfer simulations to predict (calculate) sensor-measured top-of-atmosphere spectral radiances. Using this monitoring method with in situ normalized water-leaving radiance nLw(λ) data from the Marine Optical Buoy (MOBY) in waters off Hawaii, we show that the root-cause for an abnormal inter-annual difference of chlorophyll-a data over global oligotrophic waters between 2012 and 2013 from the Visible Infrared Imaging Radiometer Suite (VIIRS) is primarily due to the VIIRS on-orbit calibration performance. In particular, VIIRS-produced Sensor Data Records (SDR) (or Level-1B data) are biased low by ~1% at the wavelength of 551 nm in 2013 compared with those in 2012. The VIIRS calibration uncertainty led to biased low chlorophyll-a data in 2013 by ~30-40% over global oligotrophic waters. The methodology developed in this study can be implemented for the routine monitoring of on-orbit satellite sensor performance (such as VIIRS). Particularly, long-term Chl-a data over open oceans can also be used as an additional source to evaluate ocean color satellite sensor performance. We show that accurate long-term and consistent MOBY in situ measurements can be used not only for the required system vicarious calibration for satellite ocean color data processing, but also can be used to characterize and monitor both the short-term and long-term sensor on-orbit performances.

VIIRS ocean color products: A progress update

In this paper, we provide overview of the progress on the evaluations of the Visible Infrared Imaging Radiometer Suite (VIIRS) ocean color products with long-term time series and more in situ data for matchup analysis. Specifically, VIIRS ocean color products include normalized water-leaving radiance spectra nLw(λ) at VIIRS five spectral bands, chlorophyll-a concentration (Chl-a), water diffuse attenuation coefficients at the wavelength of 490 nm, Kd(490), and at the domain of photosynthetically available radiation (PAR), Kd(PAR). VIIRS ocean color products derived from the NOAA Multi-Sensor Level-1 to Level-2 (MSL12) ocean color data processing system are evaluated and compared routinely with in situ data from the Marine Optical Buoy (MOBY) and several AERONET-OC sites. In order to meet requirements from all users, we propose to routinely produce two ocean color data streams, i.e., the near-real-time (NRT) data and delayed science quality data. The NRT ocean color data stream has the advantage of quick data turn around with data latency -12-24 hours, while the science quality data stream has high consistence (with the mission-long data reprocessing) and accuracy of ocean color products. In addition, we have significantly improved on-orbit sensor calibration by combining the lunar calibration into the current solar calibration method. Our results show that VIIRS is now providing high-quality global ocean color products in support of the scientific research and operational applications.

VIIRS ocean color research and applications

In this paper, we provide evaluations and assessments of the Visible Infrared Imaging Radiometer Suite (VIIRS) ocean color products, including normalized water-leaving radiance spectra nLw(λ) at VIIRS five spectral bands, chlorophyll-a concentration (Chl-a), water diffuse attenuation coefficients at the wavelength of 490 nm, Kd(490), and at the domain of photosynthetically available radiation (PAR), Kd(PAR). Specifically, VIIRS ocean color products derived from the NOAA Multi-Sensor Level-1 to Level-2 (MSL12) ocean color data processing system are evaluated and compared with in situ data from the Marine Optical Buoy (MOBY) and measurements from the Moderate Resolution Imaging Spectroradiometer (MODIS). In general, VIIRS ocean color products are matched well with MOBY in situ measurements, and are also consistent with those from MODIS-Aqua. Ocean color products were found to be highly sensitive to some operational sensor calibration issues. We have improved sensor calibration by combining the lunar calibration into the current calibration method. Here, the ocean color products based on the new sensor calibration are evaluated. Our results show that VIIRS is capable of providing high-quality global ocean color products in support of the scientific research and operational applications.

Observations of ocean diurnal variations from the Korean geostationary ocean color imager (GOCI)

The first geostationary ocean color satellite sensor, Geostationary Ocean Color Imager (GOCI) onboard the Korean Communication, Ocean, and Meteorological Satellite (COMS), which was launched in June of 2010 and has eight spectral bands from the blue to the near-infrared (NIR) wavelengths in 412–865 nm, can monitor and measure ocean phenomenon over a local area of the western Pacific region centered at 36°N and 130°E and covering ~2500 × 2500 km2. Hourly measurements during daytime (i.e., eight images per day from local 9:00 to 16:00) are a unique capability of GOCI to be used for the short- and long-term regional ocean environmental monitoring. A recent study from a collaboration between NOAA Center for Satellite Applications and Research (STAR) and Korean Institute of Ocean Science and Technology (KIOST) showed that the GOCI ocean color products such as normalized water-leaving radiance spectra, nLw(λ), for GOCI coverage region derived using an iterative NIR-corrected atmospheric correction algorithm (Wang et al., Opt. Express, vol. 20, 741–753, 2012) were significantly improved compared with the original GOCI data products and have a comparable data quality as from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Aqua in this region (Wang et al., Opt. Express, vol. 21, 3835–3849, 2013). It is also shown that the GOCI-derived ocean color data can be used to effectively monitor ocean phenomenon in the region such as tide-induced re-suspension of sediments, diurnal variations of ocean optical and biogeochemical properties, and horizontal advection of river discharge. In this paper, we show some more recent results of GOCI-measured ocean diurnal variations in various coastal regions of the Bohai Sea, Yellow Sea, and East China Sea. With possibly eight-time measurements daily, GOCI provides a unique capability to monitor the ocean environments in near real-time, and GOCI data can be used to address the diurnal variability in the ecosystem of the GOCI coverage region. In addition, more in situ data measured around the Korean coastal regions are used to validate the GOCI ocean color data quality, including evaluation of ocean diurnal variations in the region. The GOCI results demonstrate that GOCI can effectively provide real-time monitoring of water optical, biological, and biogeochemical variability of the ocean ecosystem in the region.