Correction of seabed layer thickness in processing subbottom profile data

The subbottom profiling is an important means of marine engineering survey, hazardous geology study and continental shelf scientific research. The accuracy of subbottom profile data interpretation has a direct impact on the research and investigation results. Because some of profilers’ transducer and hydrophone are separately installed, when the survey area is very shallow, distortion of shallow layers will be caused if it is seen as a self-excited and self-collected single-channel seismic system. According to the principle of subbottom profiler, the distortion correction formula is deduced and analyzed, providing actual value to using C-View software to interpret such subbottom profile data more accurately. In addition, the seabed sediments sound velocity is one of the key parameters when acquiring and processing the subbottom profile data. On the basis of comparing some sound velocity forecasting empirical equations, the LU Bo’s equation was considered the most appropriate to predict the seabed sediments, sound velocity at near-shore of China. In a survey of an artificial island site, the LU Bo’s equation and the porosity data obtained from geological drilling were utilized to predict the sediments sound velocity, and the sound velocity structure profile was plotted, which was applied in processing the subbottom profile data of the artificial island investigation. The method of using porosity data to predict sediments sound velocity in processing subbottom profile data can improve the interpretation accuracy and it’s of practical significance.

Performance evaluation of operational atmospheric correction algorithms over the East China Seas

To acquire high-quality operational data products for Chinese in-orbit and scheduled ocean color sensors, the performances of two operational atmospheric correction(AC) algorithms(ESA MEGS 7.4.1 and NASA Sea DAS 6.1) were evaluated over the East China Seas(ECS) using MERIS data. The spectral remote sensing reflectance R_(rs)(λ), aerosol optical thickness(AOT), and ?ngstr?m exponent(α) retrieved using the two algorithms were validated using in situ measurements obtained between May 2002 and October 2009. Match-ups of R_(rs), AOT, and α between the in situ and MERIS data were obtained through strict exclusion criteria. Statistical analysis of R_(rs)(λ) showed a mean percentage difference(MPD) of 9%–13% in the 490–560 nm spectral range, and significant overestimation was observed at 413 nm(MPD>72%). The AOTs were overestimated(MPD>32%), and although the ESA algorithm outperformed the NASA algorithm in the blue-green bands, the situation was reversed in the red-near-infrared bands. The value of α was obviously underestimated by the ESA algorithm(MPD=41%) but not by the NASA algorithm(MPD=35%). To clarify why the NASA algorithm performed better in the retrieval of α, scatter plots of the α single scattering albedo(SSA) density were prepared. These α-SSA density scatter plots showed that the applicability of the aerosol models used by the NASA algorithm over the ECS is better than that used by the ESA algorithm, although neither aerosol model is suitable for the ECS region. The results of this study provide a reference to both data users and data agencies regarding the use of operational data products and the investigation into the improvement of current AC schemes over the ECS.

Analysis of York Pigs Feeding Behavior Using Stepwise Regression and Principal Component Regression

A statistical analysis was conducted on the feeding behavior of 106 York breeding pigs.Pearson correlation analysis,principal component correlation analysis and multiple stepwise regression equation methods were applied to establish regression equations of the York breeding pigs total feed intake per time and average feed intake per time with corrected fat thickness,feed conversion rate,and corrected daily gain.The results showed that:①there were three peak feed intake periods for the pigs,and the correlation coefficient between the feed intake and the corrected fat thickness of the pigs in the 24 h period was positive or negative,that is,increasing the number of feeding times and the feed intake was not necessarily conducive to the fat thickness accumulation,but the breeding goal of fat thickness could be achieved by controlling the feeding times and feed intake;②the average feed intake of pigs in the 60-90 kg body weight stage was 30%-50%higher than that of the 30-60 kg body weight stage,but the number of feeding times decreased,the peak feeding time was more concentrated,and the feeding duration per time was 3.0 min longer,indicating that as the weight of pigs increased,the feed intake increased significantly;and③the stepwise regression equations and the principal component equations showed that the feeding behavior of York pigs in the 30-90 kg growth stage was not only affected by the feeding time within 24 h,but also by environmental factors such as temperature and humidity.The feeding behavior of York pigs is a complex process of interaction between environmental factors and animal factors.