目标构成与目标描述

针对数字测绘生产中,如按「１」中所述面向目标的观点进行空间数据采集的情况,进一步介绍和讨论了目标定义和目标与目标体系结构,目标构成与目标描述的基本规则等,并指出其对数字测绘产品生产的积极参考意义。     

基于水下多目标定位的目标识别和辨析处理

在水下多目标的定位过程中,对不同目标发射源的标识和分辨是非常关键的一部分。介绍一种方法,即在目标发射数据的文件头加上一个目标号进行标识。在数据处理中采用三级顺序的数据分离,层层提取,能够分辨出不同目标定位所需的数据。     

目标概念的理解与意义

讨论了空间数据处理中的经典数据模型,及面向目标数据模型的兴起,并重点介绍了在数字测绘生产中目标概念的理解与目标理解的意义,最后分析了应用面向目标数据模型对基础测绘和专业应用领域的基本要求。     

目标概念的理解与意义

讨论了空间数据处理中的经典数据模型,及面向目标数据模型的兴起,并重点介绍了在数字测绘生产中目标概念的理解与目标理解的意义,最后分析了应用面向目标数据模型对基础测绘和专业应用领域的基本要求。     

复合目标的赋值──聚合操作

介绍了有关目标聚合的一般特征，在ＧＩＳ软件Ｓｍａｌｌｗｏｒｌｄ上讨论了聚合操作的一般过程。按目标属性本身的特点，将数值聚合归为三个基本类，以实例形式介绍了这些属性值的聚合方法。并根据Ｓｍａｌｌｗｏｒｌｄ支持的面向对象语言ｍａｇｉｋ，利用面向对象的数据模型实现其聚合操作过程。     

GIS中空间目标的表达方法探讨

首先分析和总结了不确定空间目标表达的一些主要研究成果和方法，建立了场模型下的统一表达，继而，基于可拓工程方法探讨了动态空间目标的表达，并详细阐述了动态集合的概念和定义。     

GIS中空间目标的表达方法探讨

首先分析和总结了不确定空间目标表达的一些主要研究成果和方法,建立了场模型下的统一表达;继而,基于可拓工程方法探讨了动态空间目标的表达,并详细阐述了动态集合的概念和定义.     

复合目标的赋值—聚合操作

介绍了有关目标聚合的一般特征，在ＧＩＳ软件Ｓｍａｌｌｗｏｒｌｄ上讨论聚合操作的一般过程。按目标属性本身特点，将数值聚合归为三个基本类，以实例形式介绍了这些属性值的聚合方法。并根据Ｓｍａｌｌｗｏｒｌｄ支持的面向对象语言ｍａｇｉｋ，利用面向对象的数据模型实现其聚合操作过程。     

基于GIS的军事目标专题研究

目标情报是重要的侦察情报组成部分,目标专题研究对目标情报的管理和分析具有重要作用。本文提出一种基于GIS的专题军事目标研究策略,通过专题制图可视化管理专题军事目标情报,融合地理信息、社会经济信息、目标情报特征属性信息,以地图形式直观反映侦察国家或区域范围内某专题属性的目标情报。在组件接口功能分析基础上,研究了军事目标遥感影像情报数据库检索提供的专题目标信息转化为空间数据的流程,及目标专题图的制作方法。最后,基于矢量化思想研究了组合目标的子目标管理。     

用于空间目标表达的智能化判决方法

面对海量的空间目标,用户在感知空间态势过程中,需要解决"哪些空间目标需要表达出来,表达出来的目标中哪些需要重点表达"的问题。手工设置可以一定程度上满足需求,但是其过程复杂、繁琐。因此引入人工智能领域的智能代理和人工神经元网络来解决空间目标表达问题,分别将其应用于空间目标表达内容辅助筛选及重点目标确定上,共同完成空间目标的表达;并进行了实验验证。实验结果表明:Agent与神经网络结合可有效解决空间目标表达问题,并且具有一定的智能性。     

基于约束条件的地图目标移位

地图目标移位是地图综合和空间信息可视化研究中的一个重要问题,其难点是如何在移位过程中满足一定的约束条件以保持目标之间的空间关系。本文以城市道路扩张为例,借助带约束性Delaunay三角网,结合有限元和空间推理方法,重点探讨顾及空间关系的基于约束条件的地图目标移位问题,并给出满足一定约束条件下的节点移位算法和计算实例。     

基于弹性力学思想的居民地点群目标位移模型

本文引入弹性力学思想对空间目标进行冲突探测及受力分析 ,用空间距离聚类及建立最小生成树的方法把空间关系较近的、相互独立的点状要素聚类组合成多个有机的整体 ,对每个整体用有限元的方法通过多次迭代。本算法的实验结果满足了诸多的制图约束条件 ,能够很方便地应用在制图综合中的位移操作中     

地图目标移位的空间关系维护

在分析有限元方法处理地图目标移位问题的基本思路和地图目标移位产生的空间关系冲突传播特征的基础上 ,提出了一个利用空间推理和有限元分析相结合的方法维护地图目标空间关系的算法     

Building Displacement Based on the Topological Structure

Map data at smaller scales than their source can result in spatial conflict, whereby map symbols become too close, or overlaid. Server map generalisation operators may be applied to solve this problem, including displacement. In this paper, we show how an optimisation algorithm, the snake algorithm, was used to displace multiple objects in order to resolve spatial conflicts and maintain important spatial relationships between objects during displacement. Two principles based on the snake algorithm are proposed in this paper. First, the truss structure mirroring spatial proximity relationships between buildings and between building and road is formed based on the weighted proximity graph derived from constrained Delaunay triangulations (CDT) in each map partition. In the weighted proximity graph, each connecting line is determined as a snake and as an element unit to assemble the global stiffness matrix in snake algorithm. Second, a buffer method that calculates force between a building and a road (or other linear features) or between pair of buildings is adopted in the snake algorithm. This avoids the imbalance phenomenon caused by different force calculation methods during the displacement. The feasibility of the approach is demonstrated in obtaining real geographic data. Finally, the results are cartographically usable and in particular, the spatial relationships between objects are preserved.     

Quantitative relations between spatial similarity degree and map scale change of individual linear objects in multi-scale map spaces

Quantitative relations between spatial similarity degree and map scale change in multi-scale map spaces play important roles in map generalization and construction of spatial data infrastructure. Nevertheless, no achievements have been made regarding this issue. To fill the gap, this paper firstly proposes a model for calculating spatial similarity degrees between an individual linear object at one scale and its generalized counterpart at the other scale. Then psychological experiments are designed to validate the new model, taking four different individual linear objects at five different scales as test samples. The experiments have shown that spatial similarity degrees calculated by the new model can be accepted by a majority of the subjects. After this, it constructs a formula that can calculate spatial similarity degree using map scale change (and vice versa) for individual linear objects in multi-scale map spaces by the curve fitting method using the point data from the psychological experiments. Both the formula and the model can calculate quantitative relations between spatial similarity degree and map scale change of individual linear objects in multi-scale map spaces, which facilitates automation of map generalization algorithms for linear features.     

Solving Space Conflicts in Map Generalization: Using a Finite Element Method

A finite element method was developed to handle conflicts during the generalization of maps. The method is holistic and solves conflict problems for the entire map surface simultaneously. When a generalized object changes size, the method immediately causes displacements in surrounding objects. Boundary constraints were introduced which make it possible to maintain the shape of objects, and simultaneously change the size of the objects. An iterative solution procedure for the Finite Element problem was shown to give solutions that better fulfill topological requirements than a direct solution of the problem.     

线图形简化与移位算子的协同方法

在地图综合过程中,线的图形简化和移位算子通常是分别执行的,图形简化和移位有时都会产生新的空间冲突。本文试图把这两种算子进行协同,避免在地图综合过程中进行空间冲突的多次探测,提高地图综合数据处理的效率。本文通过把线图形简化转换为线上的点移位,并构建邻近地图目标之间的移位传播路径,在考虑空间上下文关系和地图感受规则的前提下,使移位过程能考虑到线图形简化,并尽量保持有关地图目标的空间特征。最后,以道路和其周边的建筑物群为例,验证了该算法的有效性和可行性。     

Map Generalization with a Triangulated Data Structure

Automation of map generalization requires facilities to monitor the spatial relationships and interactions among multiple map objects. An experimental map generalization system has been developed which addresses this issue by representing spatial objects within a simplicial data structure (SDS) based on constrained Delaunay triangulation of the source data. Geometric generalization operators that have been implemented include object exaggeration, collapse, amalgamation, boundary reduction and displacement. The generalization operators exploit a set of primitive SDS functions to determine topological and proximal relationships, measure map objects, apply transformations, and detect and resolve spatial conflicts. Proximal search functions are used for efficient analysis of the structure and dimensions of the intervening spaces between map objects. Because geometric generalization takes place within a fully triangulated representation of the map surface, the presence of overlap conflicts, resulting from individual operators, can be detected due to the introduction of singularities in the triangulation, the structure of which is used to generate displacement vectors to resolve the conflict. Examples of the application of the implemented operators are described and illustrated using large scale topographic map data.     

基于CDT骨架线的地图目标邻近冲突识别

制图综合过程中随着比例尺的缩小,不可避免地产生邻近冲突。为了在数字环境下自动地解决这类冲突,首先需要实现这些冲突的自动识别。文中提出一种基于CDT骨架线的地图目标邻近冲突识别方法。该方法首先基于CDT提取地图目标之间空白区域的骨架线;然后沿着每一条骨架线弧段所穿过的三角形路径搜索相邻地图目标之间的冲突区域(宽度小于阈值的三角形集合);最后,从冲突涉及的地图目标、发生冲突的空间位置以及冲突严重程度3个方面给出所识别冲突的定量化描述,从而为邻近冲突的解决提供依据。     

基于场论分析的建筑物群的移位

在多边形群目标综合中,移位是一种旨在解决空间邻近冲突的重要操作.以建筑物群在街道拓宽后产生移位操作为例,提出一种基于场论分析的移位方法,认为街区块多边形边界的收缩产生向街区块内部逐步传递并衰减的作用力,从而促使建筑物多边形的空间位置移动,借助于物理学场论中的"等势线"模型来表达这一移位现象.基于Delaunay三角网建立了类似于Voronoi图的建筑物群剖分结构,用于表达移位场模型的"等距离关系曲线".在移位场中目标的运动方向与运动距离由矢量和运算及梯度衰减函数计算完成.算法思想在一地图综合软件系统中已实现.