Quantifying ocean surface green tides using high-spatial resolution thermal images.

The use of thermal remote sensing for marine green tide monitoring has not been clearly demonstrated due to the lack of high-resolution spaceborne thermal observation data. This problem has been effectively solved using high-spatial resolution thermal and optical images collected from the sensors onboard the Ziyuan-1 02E (ZY01-02E) satellite of China. The characteristics and principles of spaceborne thermal remote sensing of green tides were investigated in this study. Spaceborne thermal cameras can capture marine green tides depending on the brightness temperature difference (BTD) between green tides and background seawater, which shows a positive or negative BTD contrast between them in the daytime or nighttime. There is a significant difference between thermal and optical remote sensing in the ability to detect green tides; compared with optical remote sensing, pixels containing less algae are not easily distinguishable in thermal images. However, there is a good linear statistical relationship between the BTD and the optical parameter (scaled algae index of virtual baseline height of floating macroalgae, SAI(VB)) of green tides, which indicates that the BTD can be used to quantify the green tide coverage area in a pixel or biomass per area. Then, the uncertainty in thermal quantitative remote sensing of green tides was clarified according to the pixel-to-pixel relationship between optical and thermal images. In a mixed pixel, green tide coverage and algal thickness have different thermal signal responses, which results in this uncertainty. In future research, more thermally remotely sensed images with high spatial resolution are needed to increase the observation frequency in the daytime and nighttime for the dynamic monitoring of green tides.

Evaluation of regions suitable for vicarious calibration of ocean color satellite sensors in the South China Sea.

Accurate retrieval of biogeochemical components of the ocean at a global scale from space requires accurately calibrated top-of-atmosphere (TOA) radiance, which is usually achieved by deriving a vicarious gain coefficient (g-factor) through a process called system vicarious calibration (SVC). Currently, only two SVC sites, Marine Optical Buoy (MOBY) and BOUée pour l'acquiSition d'une Série Optique à Long termE (BOUSSOLE), are routinely operated to support the SVC process for all on-orbit ocean color satellite payloads. However, high-quality matchups between satellite observations and in situ measurements are rare because of the strict requirements of the SVC process. Meanwhile, a stable g-factor is usually computed by averaging sufficient gain measurements. Therefore, more SVC sites are required to derive a stable g-factor in a short duration, particularly for the initial calibration of newly launched satellite sensors. In this study, nearly twenty years of well-calibrated ocean color satellite data were used to calculate the mean and standard deviation of physical and optical properties of waters and the atmosphere in the South China Sea (SCS) to evaluate the feasibility of establishing a SVC site. A region was identified that meets all requirements that were used to evaluate the MOBY and BOUSSOLE sites. Two in situ measurements within this region were used to derive a g-factor for MODIS-Terra and MODIS-Aqua and were compared with the g-factor derived using MOBY data. The consistence of the two g-factors indicates that the identified region in the SCS could be a potential area for establishing a long-term moored SVC site.

Vicarious calibration of COCTS-HY1C at visible and near-infrared bands for ocean color application.

Remote sensing reflectance obtained from space-borne ocean color sensors is of great importance to carbon cycle and ocean-atmospheric interactions by providing biogeochemical parameters on the global scale using specific algorithms. Vicarious calibration is necessary for obtaining accurate remote sensing reflectance that meets the application demands of atmospheric correction algorithms. For ocean color sensors, vicarious calibration must be done prior to atmospheric correction. The third Chinese Ocean Color and Temperature Scanner (COCTS) aboard the HY1C satellite was launched on September 7, 2018, and it will provide essential ocean color data that will complement those of existing missions. We used field measurements from the Marine Optical Buoy (MOBY) and aerosol information provided by the MODerate Imaging Spectroradiometer (MODIS) aboard the Terra satellite to calculate vicarious calibration coefficients, and we further evaluated the applicability of the established vicarious calibration approach by cross-calibration using MODIS data on the global scale. Finally, the established vicarious calibration coefficients were used to retrieve the aerosol optical depth and remote sensing reflectance, which were compared to Aerosol Robotic Network-Ocean Color (AERONET-OC) data and MODIS-Terra and Ocean and Land Color Instrument (OLCI)-Sentinel-3A operational products. The results show that the vicarious calibration coefficients are relatively stable and reliable for all bands ranging from visible to near-infrared and can be used to obtain accurate high-quality data.

Estimating causal interaction between prefrontal cortex and striatum by transfer entropy.

Transfer entropy (TE) is an information-theoretic measure for the investigation of causal interaction between two systems without a requirement of pre-specific interaction model (such as: linear or nonlinear). We introduced an efficient algorithm to calculate TE values between two systems based on observed time signals. By this method, we demonstrated that the TE correctly estimated the coupling strength and the direction of information transmission of two nonlinearly coupled systems. We also calculated TE values of real local field potentials (LFPs) recorded simultaneously in the lateral prefrontal cortex (LPFC) and the striatum of the behavioral monkey, and observed that the TE value from the LPFC to the striatum was stronger than that from the striatum to the LPFC, consistent with anatomical structure between the two areas. Moreover, the TE value dynamically varied dependent on behavior stages of the monkey. These results from simulated and real LFPs data suggested that the TE was able to effectively estimate functional connectivity between different brain regions and characterized their dynamical properties.