Mengqiu Wang

Extracting Oil Slick Features From VIIRS Nighttime Imagery Using a Gaussian Filter and Morphological Constraints

Satellite images of reflected sunlight have been used to detect and monitor oil spills in oceans. However, such a capacity is often hindered by the image noise due to either a low signal-to-noise ratio or other image features such as clouds or cloud shadows. The problem is particularly severe for nighttime images captured by the Visible Infrared Imager Radiometer Suite (VIIRS). This letter proposes a practical method to extract oil slick features in a semiautomatic fashion from VIIRS nighttime images and other noisy optical remote sensing images. The method is based on statistical information and morphological operators, and it is demonstrated to be able to effectively remove the noise and identify line features with the appropriate selection of threshold values. Testing this method over VIIRS nighttime images shows the preliminary success of oil slick feature extraction. Experiments on daytime data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) also suggest the applicability of this method to other optical remote sensing images. However, the requirement of human intervention to determine optimal parameters points to the need for improved automation in future works.

Detecting surface oil slicks using VIIRS nighttime imagery under moon glint: a case study in the Gulf of Mexico

Using data collected over the Gulf of Mexico during night between May 2012 and September 2013 by the Visible Infrared Imager Radiometer Suite (VIIRS), we demonstrate a new application from its day-and-night band (DNB). Under cloud free and moon glint conditions, the DNB revealed surface oil slicks from natural oil seeps. This is despite the fact that the signal-to-noise ratio (SNR) of this wide band (505–890 nm) under moon glint is much lower (30:1–50:1) and its resolution is also coarser (750 m) than the VIIRS imaging bands (375 m) under daytime solar illumination. The DNB was designed to map light sources at night. Similar to its predecessor, the Defense Meteorological Satellite Program Operational Linescan System (OLS), the VIIRS DNB should be suitable to identifying bioluminescence at night. However, with its finer resolution and higher SNR than OLS, the VIIRS DNB is demonstrated here to be also able to complement other sensors in the detection and mapping of oil spills.

Floating algae blooms in the East China Sea

A floating algae bloom in the East China Sea was observed in MODIS imagery in May 2017. Using satellite imagery from MODIS, VIIRS, GOCI, and OLI, and combined with numerical particle tracing experiments and laboratory experiments, we examined the history of this bloom as well as similar blooms in previous years, and attempted to trace the bloom source and identify the algae type. Results suggest that one bloom origin is offshore Zhejiang coast where algae slicks have appeared in satellite imagery almost every February – March since 2012. Following the Kuroshio Current and Taiwan Warm Current, these “initial” algae slicks are first transported to the northeast to reach South Korea (Jeju Island) and Japan coastal waters (up to 135oE) by early April 2017, and then transported to the northwest to enter the Yellow Sea by the end of April. The transport pathway covers an area known to be rich in Sargassum horneri, and spectral analysis suggests that most of the algae slicks may contain large amount of S. horneri. The bloom covers a water area of ~160,000 km2 with pure algae coverage of ~530 km2, which exceeds the size of most Ulva blooms that occur every May – July in the Yellow Sea. While blooms of smaller size also occurred in previous years and especially in 2015, the 2017 bloom is hypothesized to be a result of record-high water temperature, increased light availability, and continuous expansion of Porphyra aquaculture along the ECS coast.

Predicting Sargassum blooms in the Caribbean Sea from MODIS observations

Recurrent and significant Sargassum beaching events in the Caribbean Sea (CS) have caused serious environmental and economic problems, calling for a long-term prediction capacity of Sargassum blooms. Here we present predictions based on a hindcast of 2000–2016 observations from Moderate Resolution Imaging Spectroradiometer (MODIS), which showed Sargassum abundance in the CS and the Central West Atlantic (CWA), as well as connectivity between the two regions with time lags. This information was used to derive bloom and nonbloom probability matrices for each 1° square in the CS for the months of May–August, predicted from bloom conditions in a hotspot region in the CWA in February. A suite of standard statistical measures were used to gauge the prediction accuracy, among which the users accuracy and kappa statistics showed high fidelity of the probability maps in predicting both blooms and nonblooms in the eastern CS with several months of lead time, with overall accuracy often exceeding 80%. The bloom probability maps from this hindcast analysis will provide early warnings to better study Sargassum blooms and prepare for beaching events near the study region. This approach may also be extendable to many other regions around the world that face similar challenges and opportunities of macroalgal blooms and beaching events.

Long-term spatiotemporal variability of southwest Florida whiting events from MODIS observations

ABSTRACT Whiting events, or waters with high concentrations of fine-grained calcium carbonate, have been previously reported in southwest Florida using three years of observations from the Moderate Resolution Imaging Spectroradiometer. Here, the initial case study has been expanded to 13 years (2003–2015) with a statistical analysis that includes environmental data to document and understand longer term temporal and spatial variability of whiting occurrence in the same region. Annual mean whiting coverage (km2) peaked in 2011 and 2012, with the highest daily coverage in 2008 (126.0 km2). Over the time series, whiting events showed spatial variability based on distance from shore. Whiting seasonality also varied within the extended time series. Multivariate linear and non-linear regressions between mean whiting coverage (km2) and several environmental variables (wind speed, sea surface temperature, precipitation, and nearby river discharge) were performed over the entire study region as well as subregions based on spatial division from the coast line. Statistically significant correlations have been found with sea surface temperature and river discharge in subregions. These findings suggest that although observing spatial and temporal patterns of whiting events is possible with modern satellites, understanding the mechanisms regulating their initiation and maintenance is more difficult.

On the continuity of quantifying floating algae of the Central West Atlantic between MODIS and VIIRS

ABSTRACT Studying abundance and distributions of floating macroalgae such as pelagic Sargassum calls for long-term continuous and consistent observations from multiple satellite sensors. Previous studies mainly relied on observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Medium Resolution Imaging Spectrometer (MERIS). As a follow-on sensor, the Visible Infrared Imager Radiometer Suite (VIIRS) also has the appropriate spectral bands to detect and quantify floating macroalgae. Based on previous works on MODIS, this study presents an improved procedure to extract floating algae pixels from VIIRS Alternative Floating Algae Index (AFAI) imagery, with image filtering used to suppress noise and adjusted thresholds used to mask sun glint, clouds, and cloud shadows. The overall extraction accuracy is about 85%. Simultaneous daily observations from MODIS and VIIRS over the Central West Atlantic (CWA) show consistent spatial patterns, but VIIRS estimations of the algae coverage (in km2) are consistently lower than MODIS (around – 19% mean relative difference or MRD), possibly due to lower sensitivity of the VIIRS near-infrared (NIR) bands than the corresponding MODIS bands. Similarly, at monthly scale VIIRS also shows lower coverage than MODIS, and their difference (around – 29% MRD) is larger than the difference between MODIS-Aqua and MODIS-Terra estimates (around – 14% MRD). Despite these differences, the spatial and temporal patterns between VIIRS and MODIS observed algae distributions match very well at all spatial and temporal scales. These results suggest that VIIRS can provide continuous and consistent observations of floating algae distributions and abundance from MODIS as long as their differences are accounted for, thus assuring continuity in the future. Furthermore, once Sargassum biomass per unit Sargassum area is determined from field measurements, conversion of these area estimates to Sargassum biomass is straightforward.

Using remote sensing to detect the polarized sunglint reflected from oil slicks beyond the critical angle

The critical angle at which the brightness of oil slicks and oil-free seawater is reversed occurs under sunglint and is often shown as an area of uncertainty due to different roughness and surface Fresnel reflection parameters. Consequently, differentiating oil slicks from the seawater in these areas using optical sensors is a challenge. Polarized optical remote sensing techniques provide complementary information for intensity imagery with different physical properties and, thus, possess the ability to resolve this difficult problem. In the polarized reflectance model, the degree of linear polarization (DOLP) of sunglint depends on accurately knowing the Stokes parameter for the reflected light, and varies with the refractive index of the surface layer and the viewing angles. For the polarized detection of oil slicks, the highest sensitivity of the DOLP to the refractive index is located within the specular reflection direction where the sum of the solar and sensor zenith angles is 82.6°. The modeled results clearly indicate that the DOLP of oil slicks is weaker in comparison with oil-free seawater under sunglint. Using measurements from the space-borne Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar (PARASOL) over the Deepwater Horizon oil spill in the Gulf of Mexico, we illustrate that the PARASOL-derived DOLP difference between the oil spill and seawater is obvious and is in accordance with the modeled results. These preliminary results suggest that the potential of multi-angle measurement and feasibility of deriving refractive index of ocean surface from space-borne sensors need further researches.

An alternative approach to determine critical angle of contrast reversal and surface roughness of oil slicks under sunglint

ABSTRACT The critical angle is the angle at which the contrast of oil slicks reverse their contrasts against the surrounding oil-free seawater under sunglint. Accurate determination of the critical angle can help estimate surface roughness and refractive index of the oil slicks. Although it’s difficult to determine a certain critical angle, the potential critical angle range help to improve the estimation accuracy. In this study, the angle between the viewing direction and the direction of mirror reflection is used as an indicator for quantifying the critical angle and could be calculated from the solar/viewing geometry from observations of the Moderate Resolution Imaging Spectroradiometer (MODIS). The natural seep oil slicks in the Gulf of Mexico were first delineated using a customized segmentation approach to remove noise and apply a morphological filter. On the basis of the histograms of the brightness values of the delineated oil slicks, the potential range of the critical angle was determined, and then an optimal critical angle between oil slicks and seawater was then determined from statistical and regression analyses in this range. This critical angle corresponds to the best fitting between the modeled and observed surface roughness of seep oil slicks and seawater.