The CartACom model: transforming cartographic features into communicating agents for cartographic generalisation

Our research is concerned with automated generalisation of topographic vector databases in order to produce maps. This article presents a new, agent-based generalisation model called CartACom (Cartographic generalisation with Communicating Agents), dedicated to the treatment of areas of low density but where rubber sheeting techniques are not sufficient because some eliminations or aggregations are needed. In CartACom, the objects of the initial database are modelled as agents, that is, autonomous entities, that choose and apply generalisation algorithms to themselves in order to increase the satisfaction of their constraints as much as possible. The CartACom model focuses on modelling and treating the relational constraints, defined as constraints that concern a relation between two objects. In order to detect and assess their relational constraints, the CartACom agents are able to perceive their spatial surroundings. Moreover, to make the good generalisation decisions to satisfy their relational constraints, they are able to communicate with their neighbours using predefined dialogue protocols. Finally, a hook to another agent-based generalisation model – AGENT – is provided, so that the CartACom agents can handle not only their relational constraints but also their internal constraints. The CartACom model has been applied to the generalisation of low-density, heterogeneous areas like rural areas, where the space is not hierarchically organised. Examples of results obtained on real data show that it is well adapted for this application.     

土地利用现状图斑的自动综合

本文针对土地利用现状数据中图斑的自动综合,采用语义与空间相结合的方法,分析了影响图斑综合的因素,根据这些因素的影响对土地利用多边形进行合并、融合及聚合操作。并以长沙市宁乡县的土地利用数据为例进行实验,结果表明,该方法较好地保持了宁乡县综合前后各地类的结构布局,能够较好地反映土地利用现状布局,节省了人机交互合并的工作量。     

采用斜拉式弯曲划分的曲线化简方法

线要素化简一直是自动制图综合中的重要研究内容。分析已有线化简算法在线弯曲形态保持和单调弧段划分时只考虑一侧等不足,提出线要素的斜拉式弯曲划分和化简新方法。该方法对线要素采用斜剖方式划分弧段,兼顾线要素两侧的弯曲形态;识别出每个划分的单调弧段是U型弧段还是V型弧段,是大弧段还是小弧段,从而分别对其进行不同的处理;在处理过程中,每化简完一个单调弧段,重新对线要素进行弧段划分,然后再次对每个单调弧段进行化简,以此类推,因此该算法是一种动态化简过程。实例显示,本算法在线要素特征点保持、u型弧段和V型弧段保持、大弯曲的保持、整体形态保持等方面非常有效,且化简率非常高,充分证明本算法的科学性和优越性。     

主流识别的多准则决策模型及其在河系结构化中的应用

在河系拓扑数据的基础上建立两种面向河系空间知识的数据模型:基于河段的数据模型和基于河流实体的数据模型.将多准则决策中的最大隶属度带权平均规划法用于河系各级主流的识别,该方法考虑主流选取中的各种因素,并将各因素的重要性用权向量的形式表示出来.还提出一种基于主流识别的河系结构化方法,将河系结构化的过程看作是确定各级主流的不断重复迭代的过程.最后将主流识别方法用于河系结构化中,并获取了进一步的树结构信息.实验证明,该方法在实用性和准确性方面都能达到满意的效果.     

数字海图水深注记的自动综合研究

以海图中水深综合的基本原则为依据,模拟人在制图综合时的思维方式,提出一种新的水深注记自动综合的模式--表达、识别与综合,并通过试验验证该综合模式的实用性和有效性,为自动制图综合的研究开创新的理论与研究方法.     

DLG空间要素网格综合法研究

通过将网格法用于DLG空间要素综合的数学计算过程的研究,提出DLG要素综合的一种新方法——网格综合法。通过对点、线、面要素网格综合法的系统分析,重点论述线、面典型空间要素的网格综合法的理论和方法,并提出数学模型,为空间要素自动地综合提出一种有效的技术途径,这在各级地理信息空间数据采集和建库中具有重要意义。     

DEM起伏纹理的视觉认知内涵与多变量消隐方法

地形是在内外营力的共同作用之下综合形成的,不同类型的地形具有不同的起伏形态特征,从全局或宏观的观测视角,可以视觉感知到这种地形起伏及其特征规律。纹理是众多物体表面呈现的有规律的线条组合,DEM作为地形的数据表达,不同地形类型区域的起伏形态具有纹理的显著表征。目前,对于DEM纹理研究主要是从DEM影像认知的角度出发,利用图像纹理的计算方法进行地形纹理对象描述和指标的提取,并基于获取的纹理对象进行区域地形特征分析和地貌类型的分类,在视觉上的反映存在不足。DEM起伏纹理作为一种基于某种观测视角和尺度的地形要素组合对象,首先需要对其进行系统的视觉认知,明确基于视觉认知的DEM起伏纹理构成要素和不同视觉变量控制的纹理要素组合结构,通过实现DEM起伏纹理的多维可视化建模,达到DEM数字地形建模的抽象与简化。基于此,本文以DEM地形起伏纹理为研究对象,对DEM起伏纹理进行视觉认知,明确DEM起伏纹理的涵义并建立提取方法,使用建立的方法实现了DEM起伏纹理的提取,取得了较好的提取效果。从视觉感知的机制出发,确定了决定视觉感知结果的视觉变量组合。确定了包含景深、长度和邻域等用于视觉综合的参数,设计建立了多变量的DEM起伏纹理消隐方法。最后设置视觉变量并使用该方法实现了DEM起伏纹理的消隐,消隐后DEM起伏纹理的数量分别降低了45.2%和53.2%,视觉上也取得了较理想的结果,具有一定的应用价值。     

基于空间映射观念的地图综合概念模式

基于关系代数的映射变换思想,将地图综合的概念框架划分为2种映射形式：空间实体映射和空间关系映射,根据变换前后空间实体数目的变化,空间实体映射进一步区分为1－1,n-1,n-m映射。空间关系映射则视为拓扑关系、距离关系、方向关系3种基本关系的复合变换。为描述综合过程中粗化表达,建立了“空间关系分辨率”概念,基于9交叉、主方向模型以及本文自行建立的“等距离关系”模型分别给出了拓扑关系、方向关系、距离关系中分辨率的表达方式。在概念级上讨论了2种映射在地图综合过程的表现形式,这一综合模式与传统方法的显著区别是,它强调了关系也存在综合的问题。     

Editorial

This article presents research that implements a fully automated workflow to generalize a 1:50k map from 1:10k data. This is the first time that a complete topographic map has been generalized without any human interaction. More noteworthy is that the resulting map is good enough to replace the existing map. Specifications for the automated process were established as part of this research.

Replication of the existing map was not the aim, because feasibility of automated generalization is better when compliance with traditional generalizations rules is loosened and alternate approaches are acceptable. Indeed, users valued the currency and relevancy of geographical information more than complying with all existing cartographic guidelines. The development of the workflow thus started with the creation of a test map with automated generalization operations. The reason for the test map was to show what is technologically possible and to refine the results based on iterative users’ evaluation. The generalization operations (200 in total) containing the relevant algorithms and parameter values were developed and implemented in one model. Particular effort was made to enrich the source data in order to improve the results. The model is context aware which means it is able to apply different algorithms or adjust parameter values in accordance with a specific area. The result of the research is a fully automated generalization workflow that produces a countrywide map at scale 1:50k from 1:10k data in 50 hours.

A fully automated workflow may be the only way to produce flexible and on-demand products; consequently, the results were implemented as a new production line in 2013. Issues for further research have been identified.     

第三次国土调查的图斑自动综合方法

从第三次国土调查数据库快速缩编派生出多尺度数据库,是地图制图的重要任务。本文针对大量图斑,首先通过研究图斑栅格综合,减少碎图斑数量;然后构建图斑语义邻近度模型、空间几何拓扑模型,分析了顾及拓扑和地区地理特征约束下的地类图斑制图综合方法;最后形成了自动化图斑缩编生产工艺流程。基于上述方法,采用计算机编程技术研发国土三调缩编系统,并应用于四川省某县23万图斑量的三调数据并试验验证。试验结果表明,通过本文方法的成果符合专题制图要求,极大地提高了三调图斑的自动综合效率。