机载雷达技术在中小比例尺地形图中的应用研究

机载雷达技术已经广泛应用于各个领域,机载雷达能瞬间获得大量的采样点,采样点具有高密度、高精度的优势,本文阐述了机载雷达技术在中小比例尺地形图中的应用。     

Design of a spatial data structure using the relational normal forms

Abstract

In previous work, a relational data structure aimed at the exchange of spatial data between systems was developed. As this data structure was relational it was of first normal form, but compliance with the higher normal forms was not investigated. Recently, a new procedural method for composing fully normalized data structures from the basic data fields has been developed by H. C. Smith, as an alternative to the process of non-loss decomposition which is difficult to understand. Smith's method has been applied to data fields required to store points, lines and polygons in a chain-node spatial data model. When geographic domain, coverage layer and map are also considered, the procedure naturally leads to a catalogue model, needed for the exchange of spatial data. Although the method produces a fully normalized data structure, it is not as easy to identify which normal forms are responsible for the ultimate arrangement of the data fields into relations, but the benefits of these criteria for data base development also apply to spatial data structures and related ancillary data.     

NET‐DBSCAN: clustering the nodes of a dynamic linear network

NET‐DBSCAN, a method for clustering the nodes of a linear network, whose edges may be temporarily inaccessible, is introduced. The new method extends the idea of a well‐known spatial clustering method, named density‐based spatial clustering of applications with noise (DBSCAN). The new algorithm is described in detail and through a series of examples. A prototype system, which implements the algorithm, developed in Java and tested through a series of synthetic networks, is also presented. Finally, the application of NET‐DBSCAN method to support real‐world situations is briefly discussed.     

基于探空图作岳阳强对流天气预报指标的分析

收集整理2007—2016年岳阳冰雹、雷雨大风、短时强降水3类强对流天气过程及其实况、再分析资料,基于探空图计算能量指标及不稳定指标,分析其与强对流发生的关系,寻找预报指标阈值,并进行预报试验。研究结果表明:①TT≥49℃、A≥20℃、K≥40℃时比较容易出现短时强降水天气,但在降雹与雷雨大风过程中,A10℃或K≥35℃的机率比短时强降水中的低,雷雨大风中的CAPE值明显比冰雹和短时强降水中的大。②2月下旬—4月上旬, LI20℃、Wm1.2 m·s~(-1)、△Z3 000 m(2～3个条件满足)可作为冰雹的预报指标;雷雨大风指标阈值为△θse_(700-850)≤-7℃、SI≤-1.2℃、垂直风切变(1 000～500 hPa)≥10 m·s~(-1);③每年的日能量平衡高度变化可分为两个阶段,当第一阶段中能量平衡高度高于250 hPa,且处于变化曲线中的极值时,往往对应出现强对流天气;第二阶段中能量平衡高度大部分高于250 hPa,要参考其他预报指标进行强对流天气预报。