Mechanism of sea ice formation based on comprehensive observation data in Liaodong Bay,China

Sea ice disaster is one of the principal natural hazards that affect some coastal areas of China,and the formation of ice cover in a wave field has important characteristics.However,analysis of the mechanism in which waves affect the thermodynamic process of sea ice is lacking,and the influence of waves is not taken into consideration in numerical models of sea ice,largely because of a lack of simultaneous observations of waves and sea ice.Using observational data of the sea ice cycle in the coastal waters of Liaodong Bay(China),we analyzed the characteristics of hydrology,meteorology,and sea ice thickness during the formation of sea ice,and explored the changes in the interrelationships among heat fluxes,waves,and sea ice under actual sea conditions.The results could provide a decision-making support as a reference to the establishment and improvement of China's early waming system to sea ice disasters,and the protection of ice drilling operations and production platform safety.     

Retrieving volume FeO and TiO_2 abundances of lunar regolith with CE-2 CELMS data using BPNN method

The volume FeO and TiO_2 abundances(FTAs) of lunar regolith can be more important for understanding the geological evolution of the Moon compared to the optical and gamma-ray results. In this paper, the volume FTAs are retrieved with microwave sounder(CELMS) data from the Chang'E-2 satellite using the back propagation neural network(BPNN) method. Firstly, a three-layered BPNN network with five-dimensional input is constructed by taking nonlinearity into account. Then, the brightness temperature(TB) and surface slope are set as the inputs and the volume FTAs are set as the outputs of the BPNN network.Thereafter, the BPNN network is trained with the corresponding parameters collected from Apollo, Luna,and Surveyor missions. Finally, the volume FTAs are retrieved with the trained BPNN network using the four-channel TBderived from the CELMS data and the surface slope estimated from Lunar Orbiter Laser Altimeter(LOLA) data. The rationality of the retrieved FTAs is verified by comparing with the Clementine UV-VIS results and Lunar Prospector(LP) GRS results. The retrieved volume FTAs enable us to re-evaluate the geological features of the lunar surface. Several important results are as follows. Firstly, very-low-Ti(<1.5 wt.%) basalts are the most spatially abundant, and the surfaces with TiO_2> 5 wt.% constitute less than 10% of the maria. Also, two linear relationships occur between the FeO abundance(FA) and the TiO_2 abundance before and after the threshold, 16 wt.% for FA. Secondly, a new perspective on mare volcanism is derived with the volume FTAs in several important mare basins, although this conclusion should be verified with more sources of data. Thirdly, FTAs in the lunar regolith change with depth to the uppermost surface,and the change is complex over the lunar surface. Finally, the distribution of volume FTAs hints that the highlands crust is probably homogeneous, at least in terms of the microwave thermophysical parameters.     

深度卷积神经网络支持下的遥感影像飞机检测

针对YOLOv3算法对小目标检测较差及出现较多漏检的问题,本文提出了一种优化的YOLOv3算法.首先使用K-means算法计算出与数据集相适用的锚框;其次将扩张卷积引入到YOLOv3网络,用来增强网络高层的感受野,改善小目标的检测效果;然后使用深度可分离卷积取代YOLOv3网络残差模块中的普通卷积,可减少计算量,从而得到一种新型卷积神经网络结构;最后在数据集上进行对比试验.结果表明,优化的YOLOv3算法能够检测出更多目标,降低漏检率,相比于YOLOv3算法,其召回率提高11.86%,F1-score提高2.99%.     

多类重力场模型的精度分析

分析国际公布的EGM2008、GECO和EIGEN-6C4等超高阶重力场模型及GOCO03S、GOCONSGCF2DIRR5和GOCONSGCF2TIMR5等低阶重力场模型的内符合精度。利用实测的GNSS/水准数据对各模型进行外符合精度的检核。分析6个模型在不同阶次组合的精度,进而选取可靠的截断阶次确定组合重力场模型。计算结果表明:EGM2008、GECO、EIGEN-6C4及DIRR5四个重力场模型的阶方差均保持在mm级,而GOCO03S在191阶之后的精度达到dm级,TIMR5模型在228阶之后的精度达到dm级;6个重力场模型中,EIGEN-6C4模型的累计阶方差最小;EGM2008、GECO模型的互差阶方差在高频部分呈现差异,而在超高阶部分两种模型的互差阶方差符合性好;与EGM2008模型相比,其组合重力场模型高程异常精度最优可达0.063 m,精度提升幅度为15%,与GECO模型相比,其组合重力场模型高程异常精度最优可达0.060 m,精度提升幅度为23%,与EIGEN-6C4模型相比,其对应的组合重力场模型高程异常精度最优可达0.064 m,精度提升幅度为18%,因此,组合重力场模型能提高重力场模型高程异常的精度。     

黑河上游山地土壤容重分布特征及影响因素

土壤容重不仅可用作计算土壤持水力和导水性,也是估算土壤养分和碳储量的重要变量。野外测定土壤容重一般费时费力,特别是在地形复杂的山区,因此山地土壤容重在国内外大多数清查数据库中缺失。本文以黑河上游山地为例,基于野外调查的124个土壤剖面,研究了山地土壤容重的空间分布特征及影响因素。结果表明:黑河上游山地0~10 cm和0~60 cm土壤容重分别为0.91±0.02 g·cm^-3 和1.04±0.01 g·cm^-3;不同植被类型下,高山寒漠容重最大,山地森林最小。随着土壤深度的增加,容重呈幂函数递增;随着土壤有机质含量的增加,容重呈指数递减。区域上,黑河上游从西北到东南,容重呈递减趋势,从高海拔到低海拔,容重呈先减小后增大趋势。主成分分析(PCA)和一般线性模型(GLM)表明,与土壤容重相关的环境因子中,海拔是影响土壤表层容重的第一主成分,土壤有机质含量是第二主成分,黏粒含量和大于2.0 mm砾石含量分别为第三、四主成分。第一、二、三、四主成分分别解释土壤容重空间变异的24.00%、29.40%、0.01%、6.20%。     

Recognition of Significant Surface Soil Geochemical Anomalies Via Weighted 3D Shortest-Distance Field of Subsurface Orebodies: A Case Study in the Hongtoushan Copper Mine,NE China

Natural Resources Research - Quantitative prediction of concealed mineralization is always confronted with difficulties in comprehensive analysis between 2D and 3D data and between qualitative and...     

函数模型与随机模型双约束的GPS-InSAR数据融合方法建立三维形变场

针对InSAR技术研究地表三维形变时监测信息不足的问题,以GPS监测信息为先验信息,建立附有随机模型约束的地表三维形变模型。考虑到SAR卫星极轨方式运行导致LOS向观测量对南北向形变不敏感的问题,以GPS南北向形变观测值作为强约束,构建三维形变解算的函数约束条件。模拟数据与西安地区实测数据的计算结果表明,基于随机模型与函数模型共同约束的地表三维形变参数最小二乘解的精度优于仅有函数模型约束或仅有随机模型约束及无任何约束的参数解精度。     

唐山地区波速比变化特征研究

选取唐山地区2008~2018年震相数据,利用单台多震和达法和多台多震和达法分别计算波速比,结合研究区内的地震活动对波速比的变化特征进行研究。结果显示,多台多震和达法得到的波速比结果较为稳定,而单台多震和达法得到的结果变化幅度大,显示更多细节;唐山地区ML≥4.5地震发生前单台波速比存在不同程度的异常,异常台站的方位与地震具有一定的对应性。     

GPS天线相位中心校正对GRACE卫星精密定轨的影响

使用GRACE卫星星载GPS观测数据,研究地面获取的先验PCV模型和利用残差法估计的在轨PCV模型对低轨卫星精密定轨的影响,并采用GFZ精密轨道对比和SLR检核手段对其进行评估。结果表明,使用先验PCV模型会降低GRACE卫星定轨精度,相反利用在轨PCV模型可以提高定轨精度,提升数量级可达mm级。