Zengzhou Hao

A new simple concept for ocean colour remote sensing using parallel polarisation radiance

Ocean colour remote sensing has supported research on subjects ranging from marine ecosystems to climate change for almost 35 years. However, as the framework for ocean colour remote sensing is based on the radiation intensity at the top-of-atmosphere (TOA), the polarisation of the radiation, which contains additional information on atmospheric and water optical properties, has largely been neglected. In this study, we propose a new simple concept to ocean colour remote sensing that uses parallel polarisation radiance (PPR) instead of the traditional radiation intensity. We use vector radiative transfer simulation and polarimetric satellite sensing data to demonstrate that using PPR has two significant advantages in that it effectively diminishes the sun glint contamination and enhances the ocean colour signal at the TOA. This concept may open new doors for ocean colour remote sensing. We suggest that the next generation of ocean colour sensors should measure PPR to enhance observational capability.

Edge-Guided Image Object Detection in Multiscale Segmentation for High-Resolution Remotely Sensed Imagery

A new segmentation approach for high-resolution remotely sensed imagery that combines the global edge and region information is developed from a new scheme to monitor the best conditions for each growing object to obtain the corresponding meaningful image object during multiscale analysis. The approach, which is an extension of the image object detection approach, includes new algorithms for determination of region-growing criteria, edge-guided image object detection, and assessment of edges. The method consists of two stages: In the first stage, edges are acquired from edge detection with embedded confidence and stored in an R-tree, and initial objects are segmented by eCognition and organized in the region adjacency graph; in the second stage, meaningful image objects are obtained by incorporating multiscale segmentation and analyzing the edge completeness curve. The evaluation results of edge completeness are obtained within the process of multiscale segmentation, and the assessment for the segmentation results shows its merit in coastal remote sensing. Images containing plenty of weak edges or distributing scene objects with various sizes and shapes can fully embody the strength of this method.

The extremely high concentration of suspended particulate matter in Changjiang Estuary detected by MERIS data

The Changjiang River is the third largest river of the annual flux around the world, which has a great impact on the ecosystem of the East China Sea and adjacent areas. Because of the shallow water, tide mixing and the runoff of the Changjiang River and Qiantang River, the suspended particulate matter (SPM) concentration is extremely high in the Changjiang Estuary, which is ever up to 2000mg/L. Due to the large water-leaving radiance at the near-infrared wavelength, the operational atmospheric correction algorithm for the open ocean can not be applied to this region, and the existing remote sensing algorithms for SPM may not be applicable for this extremely high turbidity waters. In this paper, we firstly apply the blue wavelength atmospheric correction algorithm to MERIS Level-1 data to get the reasonable spectral water-leaving radiances in the Changjiang Estuary. Based on the winter cruise data in 2007, a regional SPM algorithm was developed using the bands ratio of the normalized water-leaving radiances between 779nm and 560nm. This algorithm was validated by the summer cruise data in 2006, and the results show that the performance of the algorithm was very well, and there was good agreement between the retrieved data and in-situ measured concentrations of the SPM in the Changjiang Estuary, with the correlation coefficient of 0.98 in the logarithm form and the averaged absolute relative error of 27.2%, and the standard deviation of 20.8mg/l in the linear form. Finally, the seasonal variations of the SPM in the Changjiang Estuary were analyzed by the MERIS SPM maps retrieved by the algorithms developed in this paper.

Sea fog characteristics based on MODIS data and streamer model

To achieve sea fog detection in China Sea with EOS MODIS data, the reflectance between band 1-7 of sea fog and other cloud regions is the pre-work. Base on satellite observations sampling from known sea fog and cloud regions, the spectral characteristics of sea fog and other clouds are analyzed. It shows that the visible reflectance (band 1-4) is generally from 0.2 to 0.4 in sea fog, while the reflectance of cloud regions is higher than 0.4. The near-infrared reflectance over different fog/cloud regions expresses some especial characteristics. At band 7, the reflectance varies observably relative to band 1-4 over sea fog/cloud regions and it is smallest. And the reflectance of band 5 and 6 may be higher than other bands in sea fog regions. Those results deduced from some instances with statistical method maybe present individual property. Therefore, with the Streamer radiative transfer model, the reflectance at the satellite altitude of the sea fog, low-cloud, mid-cloud and high-cloud with different cloud microphysical and observational conditions is simulated and re-analyzed. The simulations also show those results in extent and are consistent with the satellite observations. It shows that the near-infrared wavelength band 6 is useful to detect sea fog by MODIS. The reflectance of sea fog satisfies band3>band6>band2 while the general cloud is band3>band2>band6. Those properties are also simply explained by Mie scattering theory. It is the different scattering efficiency of sea fog and clouds at different wavelength that make some results. Those properties at sea fog in seven bands that is different from other clouds is nice for fog autodetection from EOS MODIS.

A dynamic sediment model based on satellite‐measured concentration of the surface suspended matter in the East China Sea

The concentration of total suspended matter (TSM) at the sea surface is derived from satellite data using a complex proxy TSM model in East China Sea from 1997 to 2008. The structure of the mean TSM image is similar to that of the topography, indicating that the distribution of the surface concentration is strongly related to the water depth. A dynamic sediment model (DSM) is constructed to relate the TSM concentration at the sea surface with suspended sediment at the benthic boundary layer, the Rouse number, and the water depth. The DSM model is improved through iteration with a convergence identified by the mean relative difference between two adjacent bottom TSM images which becomes smaller with the more iterations and the value is less than 1% after 50 iterations. The performance of the DSM model is validated by satellite-measured concentration with a mean relative error of 5.2% for the monthly mean images. The DSM model is used to deduce the bottom TSM concentration at the benthic boundary layer and the distribution of the Rouse number. The spatial distribution of the sea surface TSM concentration is determined predominately by both the bottom suspended sediment concentration and water depth. The temporal variation of the sea surface concentration mainly depends upon the Rouse number in the water column. Our result shows that the discharge of the Changjiang River can change the distribution of the Rouse number to form a band-shaped region in the Changjiang Estuary. The DSM model provides a framework for understanding some of the mechanisms of the formation and variation of the primary TSM plume and the secondary plume in the ECS. The primary TSM plume corresponds approximately to the region with depth shallower than 20 m and the secondary plume corresponds to the region with depths between 20 and 50 m.

SST diurnal warming in the China seas and northwestern Pacific Ocean using MTSAT satellite observations

Hourly sea surface temperature (SST) observations from the geostationary satellite are increasingly used in studies of the diurnal warming of the surface oceans. The aim of this study is to derive the spatial and temporal distribution of diurnal warming in the China seas and northwestern Pacific Ocean from Multi-functional Transport Satellite (MTSAT) SST. The MTSAT SST is validated against drifting buoy measurements firstly. It shows mean biases is about–0.2°C and standard deviation is about 0.6°C comparable to other satellite SST accuracy. The results show that the tropics, mid-latitudes controlled by subtropical high and marginal seas are frequently affected by large diurnal warming. The Kuroshio and its extension regions are smaller compared with the surrounding regions. A clear seasonal signal, peaking at spring and summer can be seen from the long time series of diurnal warming in the domain in average. It may due to large insolation and low wind speed in spring and summer, while the winter being the opposite. Surface wind speed modulates the amplitude of the diurnal cycle by influencing the surface heat flux and by determining the momentum flux. For the shallow marginal seas, such as the East China Sea, turbidity would be another important factor promoting diurnal warming. It suggests the need for the diurnal variation to be considered in SST measurement, air-sea flux estimation and multiple sensors SST blending.

Validation of S-NPP VIIRS Sea Surface Temperature Retrieved from NAVO

The validation of sea surface temperature (SST) retrieved from the new sensor Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-Orbiting Partnership (S-NPP) Satellite is essential for the interpretation, use, and improvement of the new generation SST product. In this study, the magnitude and characteristics of uncertainties in S-NPP VIIRS SST produced by the Naval Oceanographic Office (NAVO) are investigated. The NAVO S-NPP VIIRS SST and eight types of quality-controlled in situ SST from the National Oceanic and Atmospheric Administration in situ Quality Monitor (iQuam) are condensed into a Taylor diagram. Considering these comparisons and their spatial coverage, the NAVO S-NPP VIIRS SST is then validated using collocated drifters measured SST via a three-way error analysis which also includes SST derived from Moderate Resolution Imaging Spectro-radiometer (MODIS) onboard AQUA. The analysis shows that the NAVO S-NPP VIIRS SST is of high accuracy, which lies between the drifters measured SST and AQUA MODIS SST. The histogram of NAVO S-NPP VIIRS SST root-mean-square error (RMSE) shows normality in the range of 0–0.6 °C with a median of ~0.31 °C. Global distribution of NAVO VIIRS SST shows pronounced warm biases up to 0.5 °C in the Southern Hemisphere at high latitudes with respect to the drifters measured SST, while near-zero biases are observed in AQUA MODIS. It means that these biases may be caused by the NAVO S-NPP VIIRS SST retrieval algorithm rather than the nature of the SST. The reasons and correction for this bias need to be further studied.

On-orbit assessment of the polarization response of COCTS onboard HY-1B satellite

Polarization response could significant affect the accuracy of the radiance measured by the ocean color remote sensors, and it should be corrected before the atmospheric correction processing. For the Chinese Ocean Color and Temperature Scanner (COCTS) onboard the HY-1B satellite which was launched on 11 Apr., 2007, the design goal of the polarization response degree is less than 5% for the scanning angle less than 20°. However, the polarization response coefficients of Hy-1B/COCTS have not yet been completely measured pre-launched, which should be estimated by the on-orbit assessment method. In this paper, we have developed an on-bit assessment method of the polarization response coefficient for satellite ocean color remote sensor. First, the principle of the polarization response of the satellite ocean color sensor is introduced. Then, we provide the on-orbit assessment method of the polarization response for the satellite ocean color sensor. The method has been applied to the Aqua/MODIS to validate its applicability, and the derived polarization response coefficients consist well with the pre-launched measured values. Finally, we apply the method to the HY-1B/COCTS, and the results show that HY-1B/COCTS has large polarization response for the 412nm and 490nm bands with the maximum polarization response degree more than 30%, and the polarization responses at 443nm, 520nm and 565nm are relative small with the degree all less than 15%. The mean values of the polarization response degree are 17.2%, 9.4%, 23.2%, 7.7% and 4.7% for the first five bands of HY-1B/COCTS, respectively.

Observations of SST diurnal variability in the South China Sea

In this study, a 3-hourly time resolution gap free sea surface temperature (SST) analysis is generated to resolve the diurnal cycle in the South China Sea (SCS, 0°–25°N, 100°–125°E).It takes advantage of hourly geostationary satellite MTSAT observations and combines three infrared and two microwave polar satellite observations at different local times. First, all the data are classified into eight SST datasets at 3 hour intervals and then remapped to 0.05°resolution grids. A series of critical quality control is done to remove the outliers.Then bias adjustment is applied to the polar satellite observations with reference to the MTSAT data. Finally, the six satellites SST data are blended by using the optimal interpolated algorithm. The 3-hourly blended SST is compared against buoy measurements. It shows a good agreement that the biases do not exceed 0.2 °C and root mean square errors range from 0.5 to 0.65 °C. A typical diurnal cycle similar to sine wave is observed. The minimum SST occurs at around 0600h and warming peak occurring between 1300h and 1500h local solar time and then decrease in the late afternoon, tapering off at night on March 13, 2008 for example. The frequency of diurnal warming events derived from four years of the blended SST provides solid statistics to investigate the seasonal and spatial distributions of the diurnal warming in the SCS. The sea surface diurnal warming tends to appear more easily in spring, especially in the coastal regions than other seasons and the central regions.

A detection algorithm for Asian dust aerosol over China Seas based on MODIS observations

Asian dust storms, which often occur on spring, can long range transport and pass through the China Seas. During this process, it makes some impact on marine ecology and region climate. In this paper, the optical and thermal properties of Asian dust aerosols are firstly presented from the satellite MODIS observations. By comparing strong dust, weak dust, clear water and clouds, the reflectances of dust aerosols over ocean at the visible 0.47μm 0.86μm, and the near-infrared 1.64μm have some significant features, it satisfies R0.47<R1.64<R0.86 for strong dust aerosol over ocean, the weak dust aerosol meets R1.64<R0.47<R0.86, even R1.64<R0.86<R0.47, and the dust reflectance may be from 0.1 to 0.3. At the thermal atmospheric windows bands 8.5, 11 and 12μm, for cloud and clear water region, the brightness temperature at 12μm is highest and the temperature at 11μm is close to 12μm. However, for dust aerosols, the brightness temperature at 12μm is much greater than those at 8.5μm and 11μm. The brightness temperature difference between 8.5μm and 11μm is small and the lower is the difference, the stronger is the dust aerosol. Based on those visible and thermal characteristics, a detection algorithm for dust aerosols over ocean is designed and is conducted for some cases. It can identify the strong and the weak dust regions well and it is nice to study the dust properties deeply.