机载激光雷达点云与定位定姿系统数据辅助的航空影像自动匹配方法

本文针对LiDAR点云和POS数据辅助航空影像的连接点自动匹配,设计了用于相关系数匹配的最佳匹配点位快速搜索算法;提出一种基于虚拟地面控制点的相机安置角误差自动检校方法,在此基础上自适应确定影像匹配搜索范围。试验结果表明,本文提出的最佳匹配点位快速搜索算法可在保证匹配正确性的情况下节省约25%的匹配耗时;相机安置角误差补偿方法能够有效地提高由POS数据计算的影像外方位元素的精度,从而明显改善同名点匹配时的点位预测精度;本文算法能处理多分辨率、多视角的交叉飞行航空影像,获得高精度的匹配结果。     

核聚类改进的RBF神经网络遥感影像分类

为提高RBF神经网络遥感影像分类算法的分类效果,本文提出了一种基于核聚类的改进方法。文中采用武汉地区的SPOT影像为实验数据,比较了改进算法与传统基于K均值的RBF神经网络的分类结果,试验表明改进算法的总体精度和Kappa系数均高于传统算法。     

The Relationship Between Indian Ocean SST and Tropical Cyclone Genesis Frequency over North Indian Ocean in May

Tropical cyclone (TC) activities in the North Indian Ocean (NIO) peak in May during the pre-monsoon period, but the TC frequency shows obvious inter-annual variations. By conducting statistical analysis and dynamic diagnosis of long-term data from 1948 to 2016, the relationship between the inter-annual variations of Indian Ocean SST and NIO TC genesis frequency in May is analyzed in this paper. Furthermore, the potential mechanism concerning the effect of SST anomaly on TC frequency is also investigated. The findings are as follows: 1) there is a broadly consistent negative correlation between NIO TC frequency in May and SST in the Indian Ocean from March to May, with the key influencing area located in the southwestern Indian Ocean (SWIO); 2) the anomalies of SST in SWIO (SWIO-SST) are closely related to a teleconnection pattern surrounding the Indian Ocean, which can significantly modulate the high-level divergence, mid-level vertical motion and other related environmental factors and ultimately influence the formation of TCs over the NIO; 3) the increasing trend of SWIO-SST may play an essential role in the downward trend of NIO TC frequency over the past 69 years.