Robust Satellite Techniques for oil spill detection and monitoring using AVHRR thermal infrared bands

In this article, a new satellite technique for oil spill detection and monitoring is fully presented and discussed. It is based on the general RST (Robust Satellite Techniques) approach applied to Advanced Very High Resolution Radiometer (AVHRR) observations in the thermal infrared region of the electromagnetic spectrum. The proposed approach, which exploits the analysis of multi-temporal satellite records, seems to be able to detect the anomalous signals on the sea due to the oil polluted areas with excellent reliability (0% of false alarms) and good sensitivity in different observational conditions. Its performances have also been evaluated in comparison with another well-known AVHRR approach, analysing the spill event which happened during the Gulf War off the Kuwait and Saudi Arabia coasts in January 1991. The results confirm the reliability of the proposed approach which promises to offer new economically sustainable opportunities for building a near-real-time monitoring system for oil spills on a global scale. Moreover, in order to further assess the exportability of the proposed approach in different observational and environmental conditions, outcomes obtained by applying it to the Seki–Baynunah event affecting the Gulf of Oman in March 1994 are also shown.     

Extending the use and interpretation of ocean satellite data using Lagrangian modelling

We propose a new methodology for synthesizing satellite or in situ observations with ocean circulation velocity fields from an operational model. This is done by attaching values taken from the satellite observations to virtual particles seeded at the surface in the domain of a circulation model and advecting them in a Lagrangian fashion. It is then possible to track the fate and change in composition of individual water parcels between two satellite images, and hence estimate the change in satellite‐derived properties along the trajectories of water parcels. The power of the method lies in deciphering the change in sea surface properties from satellite data in the Lagrangian (advective) frame. We use this to estimate rates of biological processes. Further, we generate a dynamically correct time‐interpolation of satellite fields by considering the temporal change in water properties as occurring along trajectories of moving water parcels, rather than in a static medium. We use the methodology to interpret and interpolate MODIS satellite fields in the Gulf of Maine, which has notoriously intermittent satellite coverage. The dynamic interpretation is made possible for this region by the availability of time‐specific velocity fields from an operational coastal circulation model.     

Automatic detection of oil spills from SAR images

A probabilistic method has been developed that distinguishes oil spills from other similar sea surface features in synthetic aperture radar (SAR) images. It considers both the radiometric and the geometric characteristics of the areas being tested. In order to minimize the operator intervention, it adopts automatic selection criteria to extract the potentially polluted areas from the images. The method has an a priori percentage of correct classification higher than 90% on the training dataset; the performance is confirmed on a different dataset of verified slicks. Some analyses have been conducted using images with different radiometric and geometric resolutions to test its suitability with SAR images different from European Remote Sensing (ERS) satellite ones. The system and its ability to detect and classify oil and non‐oil surface features are described. Starting from a set of verified oil spills detected offshore and over the coastline, the ability of SAR to reveal oil spills is tested by analysing wind intensity, deduced from the image itself, and the distance from the coast.     

Dynamics of the slope water off New England and its influence on the Gulf Stream as inferred from satellite IR data

The movements of warm core rings and the Gulf Stream front were studied in the New England slope water region by using both satellite IR data and available in situ sea surface temperature data. It is found that: (1) the rotating speed of the rings exhibits a marked seasonal variation with the maximum speed occurring in the winter and the minimum in the late fall; (2) the surface area of the rings increases monotonically with time; and (3) the Gulf Stream front at the north wall migrates seasonally and attains its northernmost position in the late fall. Based on these findings we calculated the horizontal eddy viscosity for the rings as $\text{4 × 10}{}^8\text{cm}{}^2\text{5}$. Furthermore, by comparing the seasonal variations of the rotational velocity of the rings and the total mass transport of the Gulf Stream, we suggest that the seasonal variation of the slope water hydrography through local air-sea interactions could play an important role in the dynamics of the Gulf Stream system.     

Book reviews

We present a new method to determine the near surface air temperature (T_a ) from satellite observations. The satellite observed parameters of total precipitable water (W), atmospheric boundary layer (～500 m) water vapour (W_b ), and sea surface temperature (SST) are used to derive T_a . A genetic algorithm (GA) is used to find the optimum relation between the input (W, W_b , SST) and output (T_a) parameters. The input data consist of 6 years (1988–1993) of instantaneous as well as monthly averages of W, W_b from the Special Sensor Microwave Imager (SSM/I), and SST data from the Advanced Very High Resolution Radiometer (AVHRR). T_a observations based on Comprehensive Ocean Atmospheric Data Set (COADS) are used to develop and evaluate the new methodology. The global mean root mean square (rms) error for instantaneous T_a estimates is 1.4°C and for monthly averages it decreases to 0.74°C. Slightly higher discrepancies between T_a derived from the new method and in situ data are found over the western boundary currents (such as the Kuroshio and Gulf Stream) during wintertime. These regions are characterized by continental cold air outbreak and seasonal current systems, particularly during wintertime. During these conditions weak coupling between SST and T_a may be one of the reasons for large error over these regions. Our method improves upon the air temperature estimates of earlier studies.     

Comparison of polar and geostationary satellite infrared observations of sea surface temperatures in the Gulf of Maine

A comparison is made between the polar orbiting (NOAA) and the geostationary (GOES) satellite infrared observations of sea surface temperatures in the Gulf of Maine between 23 May and 6 June 1978. Color image enhancement is used to demonstrate that both satellites are capable of detecting the large-scale surface patterns associated with the Gulf Stream and sea surface temperature fronts in the vicinity of Georges Bank and Nova Scotia. The main difference between the range of surface temperatures detected by the two satellites is due to their different spacial resolution: 1 km for the NOAA and 8 km for the GOES. The equivalent blackbody temperatures recorded by the GOES are 2–3°C lower than those obtained by the NOAA satellite because of a GOES calibration offset. The comparison of the NOAA data with ship observations off Nantucket indicates that, at sea surface temperatures of 6–7°C, the NOAA Satellite and ship observations agree within 1°C. A similar comparison in the Gulf Stream at sea surface temperatures of 23–27°C, indicates that the NOAA measurements are 2–3°C lower than in situ observations. Coastal radiosonde profiles are used to estimate the correction for atmospheric attenuation of the infrared radiation. A comparison of Maul and Sidran (1973) and Weinreb and Neuendorffer (1973) models for attenuation of infrared by atmospheric water vapor shows significant differences. It was not possible to resolve the discrepancy between the models because of measurement uncertainties.     

基于NOAA18的渤海烟台海域溢油遥感研究

概述了海洋溢油监测的国内外研究现状,并指出了研究的切入点和研究意义所在。研究采用的是NOAA18的数据,由于溢油区域与非溢油区域的比热容不同,从而引起海表面的辐射发生变化,反映在卫星图片上是灰度值不同。因此利用发生溢油区域在卫星图片上的灰度值不同而呈现出深色区域,进而在卫星图片上找出疑似溢油区域,再进行人工解译,进一步确定溢油的发生区域。以烟台“金玫瑰”号溢油事故为例,综合考虑烟台海域水文因素等,分析得出溢油发生的范围。     

Validation of ATSR sea surface temperatures in the Faeroes region

Abstract. Sea temperatures measured by a thermosalinograph at a mean depth of 5 m during a cruise on the RRS Ckarles Darwin in a region to the north-east of the Faeroe Islands were compared with high resolution (～l km( and low resolution (0·5 degree spatially averaged( Along Track Scanning Radiometer (ATSR( sea surface temperature products. In both cases the satellite measurements were biased cooler than the in situ sea temperatures within an amount consistent with the cool skin effect and within the ±0.5deg-K design specification of the ATSR. The comparison with the low resolution data gave a bias of 0·3degK compared with 0·4degK for the high resolution sea surface temperatures. In each case these biases were equivalent in magnitude to the mean estimated skin effect for the period of the comparisons. The smaller bias may result from the fact that horizontal displacement of temperature gradients during the period between satellite and in situ measurements becomes less important as the size of the averaging area is increased. Owing to cloud conditions it was necessary to relax the time window for the comparisons.     

Validation of chlorophyll-α concentration maps from Aqua MODIS over the Gulf of Gabes (Tunisia): comparison between MedOC3 and OC3M bio-optical algorithms

Few studies have focused on the use of ocean colour remote sensors in the Gulf of Gabes (southeastern Tunisia). This work is the first study to evaluate the ocean colour chlorophyll-a product in this area. Chlorophyll-a concentrations were measured during oceanographic cruises performed off the Gulf of Gabes. These measurements were used to validate satellite data acquired from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite. First, two atmospheric correction procedures (standard and shortwave infrared) were tested to derive the remote-sensing reflectance, and then a comparison between two bio-optical (OC3M and MedOC3) algorithms were realized using the in situ measurements. Both atmospheric correction procedures gave similar results when applied to our study area indicating that most pixels were non-turbid. The comparison between bio-optical algorithms shows that using the regional bio-optical algorithm MedOC3 improves chlorophyll-a estimation in the Gulf of Gabes for the low values of this parameter.     

High-resolution satellite measurements of coastal wind field and sea state

Methods to derive wind speed and sea state by simple empirical models from synthetic aperture radar (SAR) data are presented and applied for use in high-resolution numerical modelling for coastal applications. The new radar satellite, TerraSAR-X (TS-X), images the surface of the sea with a high resolution up to 1 m. Therefore, not only wind information and integrated sea state parameters but also individual ocean waves with wavelengths down to 30 m are detectable. Two-dimensional information on the ocean surface retrieved using TS-X data is validated for different oceanographic applications: derivation of finely resolved wind fields (XMOD algorithm) and integrated sea state parameters (XWAVE algorithm). Both algorithms are capable of taking into account fine-scale effects in coastal areas. Wind and sea state information retrieved from SAR data are applied as the input for a wave numerical spectral model (wind forcing and boundary condition) running at a fine spatial horizontal resolution of 100 m. Results are compared to collocated buoy measurements. Studies are carried out for varying wind speeds and comparisons against wave height, simulated using original TS-X-derived wind data, showing the sensitivity of waves to local wind variation and thus the importance of local wind effects on wave behaviour in coastal areas. Examples for the German Bight (North Sea) are shown. The TS-X satellite scenes render well-developed ocean wave patterns of developed swell at the sea surface. Refraction of individual long swell waves at a water depth shallower than about 70 m, caused by the influence of underwater topography in coastal areas, is imaged on the radar scenes. A technique is developed for tracking wave rays depending on changes in swell wavelength and direction. We estimate the wave energy flux along wave tracks from deep water to the coastline based on SAR information: wave height and wavelength are derived from TS-X data.     

Chlorophyll variability in the northeastern Gulf of Mexico

Changes in chlorophyll concentration distribution in surface waters of the northeastern Gulf of Mexico (NEGOM) were examined using satellite and in situ data collected between November 1997 and August 2000. The patterns of chlorophyll distribution derived from in situ data consistently matched the satellite observations, even though the satellite-derived concentrations in coastal and offshore waters influenced by rivers were overestimated by the standard satellite data processing algorithms. River discharge and wind-driven upwelling were the major factors influencing surface chlorophyll-a variability for inshore regions. High in situ chlorophyll-a concentrations (≥1 mg m^?3) occurred inshore and particularly near major river mouths during the summer seasons of 1998, 1999 and 2000. Plumes of Mississippi River water extended offshore to the southeast of the delta over distances >500 km from the river delta for maximum periods of 14 weeks between May and September every year and could reach the Florida Keys in certain years. The offshore transport of the plume was initiated by eastward or southeastward winds and then by separate anticyclonic eddies located southeast of the Mississippi delta and nearby shelf every year. Chlorophyll concentrations during the winter to spring transition in 1998 off Escambia, Choctawhatchee, Apalachicola and Suwannee Rivers and off Tampa Bay were up to 4 times higher than during the same periods in 1999 and 2000. This was related to higher freshwater discharge during the 1997–1998 winter–spring transition, coinciding with an El Niño–Southern Oscillation event, and to the unusually strong upwelling observed along the coast in spring 1998.     

A new algorithm for microwave radiometer remote sensing of sea surface salinity without influence of wind

The microwave radiation of the sea surface, which is denoted by the sea surface brightness temperature, is not only related with sea surface salinity (SSS) and temperature (SST), but also influenced by sea surface wind. The errors of wind detected by satellite sensor have significant influences on the accuracy of SSS retrieval. The effect of sea surface wind on sea surface brightness temperature, i.e. ΔT_h,v , and the relations among ΔT_h,v , wind speed, sea surface temperature, sea surface salinity and incidence angle of observation are investigated. Based on the investigations, a new algorithm depending on the design of a single radiometer with dual polarizations and multi‐incidence angles is proposed. The algorithm excludes the influence of sea surface wind on SSS retrieval, and provides a new method for remote sensing of SSS.     

Validation of coastal sea and lake surface temperature measurements derived from NOAA/AVHRR data

An interactive validation monitoring system is being used at the NOAA/NESDIS to validate the sea surface temperature (SST) derived from the NOAA-12 and NOAA-14 polar orbiting satellite AVHRR sensors for the NOAA CoastWatch program. In 1997, we validated the SST in coastal regions of the Gulf of Mexico, Southeast US and Northeast US and the lake surface temperatures in the Great Lakes every other month. The in situ     

An algorithm to estimate soil moisture over vegetated areas based on in situ and remote sensing information

An algorithm is proposed for estimating soil moisture over vegetated areas. The algorithm uses in situ and remote sensing information and statistical tools to estimate soil moisture at 1 km spatial resolution and at 20 cm depth over Puerto Rico. Soil moisture within the study region is characterized by spatial and temporal variability. The temporal variability for a given area exhibits long- and short-term variations that can be expressed by two empirical models. The average monthly soil moisture exhibits the long-term variability and is modelled by an artificial neural network (ANN), whereas the short-term variability is determined by hourly variation and is represented by a nonlinear stochastic transfer function model. Monthly vegetation index, land surface temperature, accumulated rainfall and soil texture are the major drivers of the ANN to estimate the monthly soil moisture. Radar, satellite and in situ observations are the major sources of information of the soil moisture empirical models. A self-organized ANN was also used to identify spatial variability to be able to determine a similar transfer function that best resembles the properties of a particular grid point and estimate the hourly soil moisture across the island. Validation techniques reveal an average absolute error of 3.34% of volumetric water content and this result shows that the proposed algorithm is a potential tool for estimating soil moisture over vegetated areas.     

Joint experiments programme in remote sensing of marine fish resources

A joint experiments programme was undertaken between three government agencies to pool their resources and expertise to develop techniques for ocean-colour sensing. During October, November and December 1981 a remote-sensing experiment was carried out using vessel-based observations and aircraft underflights synchronous to NIMBUS-7 overpasses in coastal waters off Cochin. The area is well known for the abundance of surface schools of oil sardine (Sardinella hngiceps Val) and mackerel (Rastrelliger kanagurta). An aircraft sensor (Ocean Colour Radiometer) with spectral channels similar to that of the Coastal Zone Colour Scanner (CZCS) on board the NIMBUS-7 satellite was flown to collect data at different altitudes to examine the aspects of atmospheric correction and developing a pigment algorithm. From the analysis of the data it was found that (i) vessel-based measurement of upwelling/downwelling irradiance and the derivation of the spectral diffuse attenuation coefficient and reflectance factor is useful in understanding the optical properties of ocean water, (ii) upwelled radiance data derived from the aircraft sensor could be suitably used in the understanding of atmospheric effects and in developing a pigment algorithm and (iii) a non-linear relationship is observed between fish catch and pigment concentration.     

Spatio-temporal variability of surface chlorophyll-a in the Halmahera Sea and its relation to ENSO and the Indian Ocean Dipole

ABSTRACT

Long-term satellite data are used to investigate the variability of ocean surface chlorophyll-a (chl-a) concentration in the Halmahera Sea (HS) under influence of the Australian-Indonesian Monsoon (AIM), the El Niño-Southern Oscillation (ENSO), and the Indian Ocean Dipole (IOD). In this study, we first analysed the seasonal variability of chl-a, and then examine the relationship between surface chl-a, sea surface temperature (SST), and sea surface wind stress in the area. Our results suggest that prevailing southeasterly winds play a fundamental role in generating chl-a blooms in the HS. Particularly on a seasonal timescale, through the mechanism of Ekman mass transport, strengthening of southeasterly wind stress during the Southeast Monsoon season (June – August) produces enhanced chl-a concentrations associated with ocean surface cooling in the area of study. On the other hand, the chl-a bloom completely diminishes during the Northwest Monsoon season (December – February) due to weakening of wind stress and Ekman transport. On an interannual timescale, sea level pressure and wind stress are coherent with ENSO and IOD phases. During El Niño and positive IOD events (La Niña and negative IOD events), both sea level pressure and wind stress greatly increase (decrease) over the HS. These conditions cause an anomaly in southerly (northerly) wind stress, which is favourable to an enhancement (reduction) of the chl-a concentration in the region. This study demonstrates that sea level pressure and wind stress are the critical factors in determining the magnitude of chl-a bloom in the HS.     

Evaluating the impact of coastal land uses on water‐clarity conditions from Landsat TM/ETM+ imagery: Candarli Bay,Aegean Sea

Landsat TM and ETM+ imagery was evaluated as a potential data source for monitoring the coastal degradation of Candarli Bay and its basin on the eastern coast of the Aegean Sea. The bay is under pressure from conflicting uses, and there is an information need for future management plans for the area surrounding the bay. Spatial and temporal distributions of land use/land cover patterns were derived by unsupervised classification with the ISODATA algorithm. The post‐classification comparison technique was applied to evaluate decadal changes in land area. The turbidity patterns of the bay were determined from sea surface reflectances, and at‐satellite temperatures for the sea area were calculated. The processed images show that the water clarity conditions were affected by the adjacent coastal land uses and by river discharges. In accordance with the change‐detection analysis of land‐use patterns, the forested areas were decreased by 21%, whereas the increase in urban areas was determined as 105% within a decade.     

The satellite-measured sea surface temperature change in the Gulf of Finland

Climate change in Baltic region and in the Gulf of Finland is an accomplished fact in human brains and in science. The purpose of this research is to retrieve quantitative level of changes for sea surface temperature (SST) of the Gulf of Finland. Two space systems National Oceanic and Atmospheric Administration/Advanced Very High Resolution Radiometer (NOAA/AVHRR) and Aqua/Moderate Resolution Imaging Spectroradiometer (MODIS) provided satellite data about temperature of the sea surface. SST data covers period 1981–2014 and includes 444 monthly data scenes with spatial resolution about 10 km. Data quality analysis displays high reliability of NOAA/AVHRR and Aqua/MODIS satellite information. The Gulf of Finland’s average annual SST has changed from 6.8°C in 1982 up to 8.2°C in 2014. Its mean speed of warming is about 0.04°C year^–1. The growth of the temperature was irregular, in the middle of 80th year, the temperature dropped down to 5.0°C, and then sharply increased up to 7.3°C in 1989. SST growth in the Gulf of Finland coincides with air temperature and sea temperature growth. The climate change in the Gulf of Finland has special significance due to the fragility of the northern ecosystems and high anthropogenic load.     

Correction of bottom influence in ocean colour satellite images of shallow water areas of the Baltic Sea

Ocean colour satellite measurements are mainly disturbed by the atmosphere, the sea surface and the sea bottom in shallow water areas. In such areas special features of bottom topography can be recognized in satellite images of the visible spectrum and the derived concentrations of water constituents are often misinterpreted. The influence of the sea bottom depends on the water depth, the transmission of the water column, the reflectance of the water, the reflectivity of the bottom materials and the used spectral channels of satellite sensors. The influence of the sea bottom on the spectral reflectance at the sea surface is discussed here on the basis of model computations. The calculations are realized for examples of shallow water areas of the Baltic Sea. Furthermore, a technique for the identification of sea bottom disturbed pixels in satellite images and for the elimination of bottom effects is presented. A linear regression analysis between the bottom depth and the spectral reflectance in the different satellite sensor channels is used in order to test the correlation between these two variables. If a relationship exists, the reflectances have to be corrected. This procedure and the elimination of the bottom influence will be explained for specific satellite systems.     

Asterionella blooms in the northwestern Bay of Bengal during 2004

Asterionella glacialis Castracane, a diatom species of marine phytoplankton, bloomed in the coastal waters of the northwestern Bay of Bengal during 24 March to 4 April 2004. This species dominated by 99% in cell concentration on 26 March 2004. During the bloom period, phytoplankton population density increased by three orders of magnitude, while the chlorophyll a concentration increased by 70 to 80 times relative to the pre‐bloom situation. The blooming was associated with coastal upwelling and influenced water quality. Corresponding to the blooming period, satellite sensor‐derived products of sea surface temperature (SST) and chlorophyll a data were analysed to understand the coverage and dynamics of phytoplankton in the area.