SEA LEVEL RISE OF THE ZHUJIANG RIVER DELTA AND NEOTECTONICS

A linear regression analysis of 28 selected tide-gauge stations of the Zhujiang Estuary shows that there has been a tendency of local sea level rise at a rate of 2.028 mm per year. The origin of the variation is significantly attributed to the local tectonic movement of discrepant fault-block. Based on this, four types of relative local sea level changes are classified. According to calculation, half of the fertile land, or 800 km2 of the delta plain will have been submerged by sea water by about 2040. This will yield a significant influence on the economic construction and human activities.     

Effect of n?3 HUFA levels in rotifers and Artemia on growth and survival of larval black sea bream ( Sparus macrocephalus )

Requirement for dietary n−3 HUFA (n−3 highly unsaturated fatty acid) for growth and survival of black sea bream (Sparus macrocephalus) larvae was studied using rotifers andArtemia at various levels of n−3 HUFA. Five treatments with rotifers andArtemia differing in n−3 HUFA were prepared by enriching them with various oil emulsions. Results indicated that dietary n−3 HUFA significantly influence fish n−3 HUFA levels and are essential for growth and survival of black sea bream larvae. The results also indicated that the incorporation of n−3HUFA TG (triacylglycerols) into tissues of larval black sea bream was more effective from natural fish oil in comparison with n−3 HUFA fatty acid ethyl esters from ethyl-esterified oil. Project No. 39770588 supported by the NSFC.     

Shape数据模型的研究与实践

对应用较为广泛的Shape数据模型进行分析和研究,并且针对一幅全要素海图由于数据量大的原因导致读取和图形显示速度慢的问题,在实践中采用快速读取内存的方法,实现了数字海图的快速读取及显示,并且同以往循环读取方法进行了比较.     

武汉市1：1万土地利用数据库建设与应用

1:1万土地利用数据库是土地管理信息化的基础,其最终目的是为国土资源管理以及其它行业服务。本文在土地管理基本理论和武汉市土地利用数据库应用实践的基础上,研究了数据库应用的多种方法,总结了数据库的应用模式以及多种应用成果表达方式。结果表明,土地利用数据库在日常地籍管理、土地资源与资产管理以及经济社会发展等领域有着广泛的应用。     

GAINS中重力传感器信息的扰动改正

重力辅助惯性导航系统GAINS(Gravity Aided Inertial Navigation System)是利用地球物理特征信息重力来完成水下运动载体的辅助惯性导航与定位.为实现重力匹配以校正惯性导航随时间累积的误差,首先必须对重力传感器输出信息进行扰动改正.分析了水下运动状态下重力传感器受到的各种重力扰动,如垂直扰动加速度、水平扰动加速度以及厄特弗斯效应影响所产生的原因,研究了扰动误差模型与INS导航精度之间的关系,并通过计算,提出了可直接以INS输出数据而无需其它外部有源导航信息进行扰动分离的方法.     

UKF在惯性/重力组合导航中的应用

将UKF(Unscented Kalman Filter)方法用于惯性/重力组合导航系统.UKF方法设计了少量的呈高斯分布的σ点,在每个更新过程中,σ点随着非线性状态方程和测量方程传播,从而获得滤波值及较高的计算精度,而且避免了对非线性方程的线性化过程.仿真结果表明:UKF方法比传统卡尔曼滤波及其改进的滤波模型都有更高的估计精度,并能有效的克服非线性严重时出现的滤波发散问题.     

Dim and Small Target Detection Based on Characteristic Spectrum

Dim and small target detection is one of the most challenging issues based on space-based detector. Original space-based detector only uses infrared bands, and the target information is limited in one-band image, so that detection error rate is high. In order to increase the target information, we suppose spectral imaging technology can be applied to the space-based detection system. Use bands of stronger radiation of targets than that of background as detection bands theoretically; the detection bands also can be called as the characteristic bands of targets. On these bases, the paper proposes methods of fuzzy fusion and fusion segmentation to achieve the target detection. Fusion is a combination of images from the characteristic bands, which can eliminate background, restrain noise, and enhance the target. Threshold segmentation and fuzzy algorithm assisted fusion algorithm to complete the final detection. In the simulation experiment, missile plume is considered as the detection target, atmosphere, cloud and jet plume is considered as the detection background, and the advantages of the characteristic spectrum detection and the proposed algorithm are verified from SNR, SCR, ROC curve, and time.     

Study on Sampling Rule and Simplification of LiDAR Point Cloud Based on Terrain Complexity

It is difficult to obtain digital elevation model (DEM) in the mountainous regions. As an emerging technology, Light Detection and Ranging (LiDAR) is an enabling technology. However, the amount of points obtained by LiDAR is huge. When processing LiDAR point cloud, huge data will lead to a rapid decline in data processing speed, so it is necessary to thin LiDAR point cloud. In this paper, a new terrain sampling rule had been built based on the integrated terrain complexity, and then based on the rule a LiDAR point cloud simplification method, which was referred as to TCthin, had been proposed. The TCthin method was evaluated by experiments in which XUthin and Lasthin were selected as the TCthin’s comparative methods. The TCthin’s simplification degree was estimated by the simplification rate value, and the TCthin’s simplification quality was evaluated by Root Mean Square Deviation. The experimental results show that the TCthin method can thin LiDAR point cloud effectively and improve the simplification quality, and at 5 m, 10 m, 30 m scale levels, the TCthin method has a good applicability in the areas with different terrain complexity. This study has theoretical and practical value in sampling theory, thinning LiDAR point cloud, building high-precision DEM and so on.     

基于DBN的车载激光点云路侧多目标提取

提出一种基于深度信念网络（DBN）的车载激光点云路侧多目标提取方法。首先通过预处理对原始数据进行分段,并将地面和建筑物点云与路侧目标进行分离;然后利用连通分支聚类分析算法进行路侧点云聚类,并采用基于体素的归一化分割方法分割重叠点云,从而生成独立目标点云;在此基础上,生成基于多方向目标对象的二值图像并展开成二值向量作为独立目标点云的描述特征;最后构建并训练DBN,利用训练好的DBN提取行道树、车辆及杆状目标等3类路侧目标。试验采用两份不同城市道路场景的点云数据,行道树、车辆及杆状目标提取结果的准确率分别达97.31%、97.79%、92.78%,召回率分别达98.30%、98.75%和96.77%,精度分别达95.70%、93.81%和90.00%,F1值分别达97.80%、96.81%和94.73%。试验结果验证了本文的有效性。