Satellite-derived bathymetry based on machine learning models and an updated quasi-analytical algorithm approach.

Retrieving the water depth by satellite is a rapid and effective method for obtaining underwater terrain. In the optical shallow waters, the bottom signal has a great impact on the radiation from the water which related to water depth. In the optical shallow waters, the spatial distribution characteristic of water quality parameters derived by the updated quasi analysis algorithm (UQAA) is highly correlated with the bottom brightness. Because the bottom reflection signal is strongly correlated with the spatial distribution of water depth, the derived water quality parameters may helpful and applicable for optical remote sensing based satellite derived bathymetry. Therefore, the influence on bathymetry retrieval of the UQAA IOPs is worth discussing. In this article, different machine learning algorithms using a UQAA were tested and remote sensing reflectance at water depth in situ points and their detection accuracy were evaluated by using Worldwiew-2 multispectral remote sensing images and laser measurement data. A backpropagation (BP) neural network, extreme value learning machine (ELM), random forest (RF), Adaboost, and support vector regression (SVR) machine models were utilized to compute the water depth retrieval of Ganquan Island in the South China Sea. According to the obtained results, bathymetry using the UQAA and remote sensing reflectance is better than that computed using only remote sensing reflectance, in which the overall improvements in the root mean square error (RMSE) were 1 cm to 5 cm and the overall improvement in the mean relative error (MRE) was 1% to 5%. The results showed that the results of the UQAA could be used as a main water depth estimation eigenvalue to increase water depth estimation accuracy.

Remote sensing of seawater optical properties and the subsurface phytoplankton layer in coastal waters using an airborne multiwavelength polarimetric ocean lidar.

The vertical profiles of the seawater optical properties and subsurface phytoplankton layer observed during an airborne lidar flight experiment carried out on 29 January 2021 in the coastal waters near Qionghai city were studied. We employed a hybrid inversion model combining the Klett and perturbation retrieval methods to estimate the seawater optical properties, while the vertical subsurface phytoplankton layer profiles were obtained by an adaptive evaluation. The airborne lidar data preprocessing scheme and inversion of the seawater optical properties were described in detail, and the effects of water environment parameters on the airborne lidar detection performance in coastal waters were discussed. The obtained seawater optical properties and phytoplankton layer profiles exhibit characteristic spatiotemporal distributions. The vertical stratification of seawater optical properties along a flight track from 19.19°N to 19.27°N is more pronounced than that from 19.27°N to 19.31°N. The subsurface phytoplankton layer appears along the flight track at water depths of 5-14 m with a thickness of 2-8.3 m. The high concentrations of chlorophyll, colored dissolved organic matter (CDOM), and suspended particulate matter (SPM) in coastal waters are the main factors leading to the shallower detection depth for airborne lidar. A 532 nm laser emission wavelength is more suitable than 486 nm for investigating coastal waters. The 532 nm receiving channel with 25 mrad receiving field of view achieves a better detection performance than that with 6 mrad. These results indicate that lidar technology has great potential for the wide-range and long-term monitoring of coastal waters.

Ocean mixed layer depth estimation using airborne Brillouin scattering lidar: simulation and model.

The potential of Brillouin scattering lidar for detecting the mixed layer depth (MLD) was studied. We simulated the Brillouin scattering lidar signal in various water environmental parameters and developed an MLD retrieval model for Brillouin scattering lidar data. We first analyzed the theoretical maximum detectable depth for Brillouin scattering lidar in low-latitude sea regions based on the multiple scattering lidar equations. Subsequently, a theoretical method for calculating the Brillouin scattering frequency shift and linewidth was derived based on the international thermodynamic equation of seawater-2010 and the coupled wave equations. Then we used the theoretical method and the temperature-salinity (T-S) profile of the global Argo data in low-latitude regions to simulate the vertical profile distribution of the Brillouin scattering frequency shift and linewidth. Furthermore, we used a maximum angle method to estimate the ocean MLD in low-latitude regions based on the vertical profile distribution of the Brillouin scattering frequency shift and density in seawater. They are well correlated, which indicates that the frequency-shift component of the Brillouin scattering lidar signal for estimating ocean MLD is feasible and reliable. It appears that airborne or spaceborne Brillouin scattering lidar technology provides great potential for high-efficiency, large-area, and long-term monitoring of the global ocean MLD and upper-ocean water bodies.

Effects of temperature and pressure on the threshold value of SBS LIDAR in seawater.

Effects of temperature and pressure on the threshold value of stimulated Brillouin scattering (SBS) in seawater were analyzed theoretically and experimentally. Theoretically, the change of threshold value of SBS versus the ocean depth was simulated based on the International Thermodynamic Equation of Seawater-2010 (TEOS-10) and the World Ocean Atlas 2013 (WOA13). Experimentally, an ocean temperature and pressure simulator (OTPS) was designed to measure the threshold value of SBS through simulating the changes of temperature and pressure of seawater in 0∼1000 meters. The theoretical and experimental results exhibit that the threshold value of SBS decreases with the increase of temperature at the same seawater pressure and increases with the increase of pressure at the same seawater temperature. The results imply that the SBS process is more likely to occur in upper seawater of lower-latitude areas. The theoretical and experimental results are helpful for remote sensing in ocean using the SBS LIDAR.

Distinguishing N2O and N2 ratio and their microbial source in soil fertilized for vegetable production using a stable isotope method.

Vegetable production systems with excessive nitrogen fertilizer result in severe N2O emission. It is pivotal to identify the source of N2O for reducing N2O emission, but estimating microbial pathways of N2O production is very difficult due to the existence of N2O reduction. A promising tool can address this problem by using δ18O and δ15NSP of N2O to construct a dual isotopocule plot. For ascertaining the microbial pathways of N2O production and consumption in soil fertilized for vegetable production, four treatments were set up: urea (U), half urea and half organic fertilizer (UO), organic fertilizer (O) and no fertilizer (NF), and the experiment was carried out continuously for two years. The δ18O vs. δ15NSP plot method indicated that the nitrification/fungal denitrification was a dominant in N2O emission, and the U treatment was the highest, followed by OU, O and NF in the both years. Among the different treatments, furthermore, the N2O flux had the same trend, whereas the extent of N2O reduction showed an opposite trend. Overall, inorganic fertilizer enhances nitrification/fungal denitrification and hinders reduction of N2O to N2, resulting in a larger amount of N2O emission. However, organic fertilizer increases the contribution of denitrification and greatly improves the extent of N2O reduction, which helps to reduce N2O emission. Therefore, organic fertilizer is crucial to reducing N2O emission by enhancing N2O reduction and should be properly applied in production practice.

Stimulated Brillouin scattering in combination with visible absorption spectroscopy for authentication of vegetable oils and detection of olive oil adulteration.

Vegetable oils provide high nutritional value in the human diet. Specifically, extra virgin olive oil (EVOO) possesses a higher price than that of other vegetable oils. Adulteration of pure EVOO with other types of vegetable oils has attracted increasing attentions. In this work, a stimulated Brillouin scattering (SBS) combined with visible absorption spectroscopy method is proposed for authentication of vegetable oils and detection of olive oil adulteration. The results provided here have demonstrated that the different vegetable oils and adulteration oils exhibit significant differences in normalized absorbance values of two relevant wavelengths (455 and 670 nm) and frequency shifts of SBS. The normalized absorbance values of all spectra at the two relevant wavelengths of 670 nm and 455 nm linearly decrease with the increase of the adulteration concentration. The Brillouin frequency shifts exponentially increase with the increase of the adulteration concentration. Due to non-destructive and requiring no sample pretreatment procedure, this method can be effectively employed for authentication and detection of oils adulteration.