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The process of reading a topographic map requires users to recognize and learn the cartographic symbols of the key (or legend) while interpreting the territory as depicted on the map at a given level of abstraction (the form and nature of features, their saliency and relationships). We present the results of an empirical user study that aims to identify and assess the main graphical characteristics that are used by map users to recognize the design principles which constitute the topographic mapping style adopted by IGN (Institut National de l'Information Géographique et Forestière), France. Our results suggest that 91% of the participants were able to recognize an IGN-France topographic map amongst other topographic map products. We also determine which graphical characteristics play a role in the recognition of this cartographic style, either by visual memory or by visual perception, and identify the representation of relief, including contour lines and shaded relief, as one of the major graphical characteristics of the topographic mapping style of IGN-France. Moreover, the participants of our study considered the representation of touristic POI (points of interest), toponymy, typography, the main roads network, the individual buildings and the forests, to be essential for stylistic recognition.     

专题地图属性信息的LOD表达与TreeMap可视化

提出一种面向专题地图属性信息的LOD可视化方法,应用新型层次结构信息可视化工具TreeMap实现了属性信息的多层次展示,随着专题地图尺度变化自适应调节属性信息的结构层次细节。并将面域拓扑制图技术Cartogram与之结合,建立了顾及区域拓扑特征的多层次属性信息空间定位方法,为受众提供了面向属性信息的跨层次空间认知策略。     

Schematic road network map progressive generalization based on multiple constraints

Multiple constraints for schematic road network map cartographic design are analyzed and summarized. Based on this, a set of quantitative criteria are set up and a new road network generalization method including progressive selection and displacement is proposed. Furthermore, topological checking methods for road networks are researched. Based on these constraints, the points in a road network are classified, and a satisfactory and effective schematic map is designed in a concrete experiment while maintaining topological consistency of the road network between the original and the schematic map.     

The cognition of change: scaling deformations in mind and spatial theories

The dynamics of the earth and its inhabitants have become a core topic and focus in research in the spatial sciences. The spatio-temporal data avalanche challenges researchers to provide efficient and effective means to process spatio-temporal data. It is of vital importance to develop mechanisms that allow for the transition of data not only into information but also into knowledge. Knowledge representation techniques from artificial intelligence play an important role in laying the foundations for theories dealing with spatio-temporal data. Specifically, the advances in the area of qualitative spatial representation and reasoning (QSTR) have led to promising results. Categorical distinctions of spatio-temporal information identified by QSTR calculi potentially correspond to those relevant to humans. This article presents the first behavioral evaluation of qualitative calculi modeling geographic events associated with scaling deformations of entities, that is, changes in size by either expansion or contraction. Examples of such dynamics include a lake flooding its surroundings or an expanding oil spill in the ocean. We compare four experiments using four different semantic domains. Each domain consists of two spatially extended entities: one entity is undergoing scaling deformations while the other is static. We kept the formal QSTR characterization, which are paths through a topologically defined conceptual neighborhood graph, identical across all semantic domains. Our results show that for geographic events associated with scaling deformations (a) topological relations are not equally salient cognitively; (b) domain semantics has an influence on the conceptual salience of topological relations.     

Characterizing and representing inference histories in geologic mapping

Evaluation of the utility of a geologic map can require understanding of its knowledge evolution. In such cases, online usage further requires machine representation of both the knowledge and the evolution. To meet these needs, an informal structure is developed here that involves the interaction of the three reasoning forms of abduction, induction, and deduction. Empirical results are presented that support the structure, and a foundational ontology for science knowledge is adapted to represent the structure. These results lead to a new understanding of the role of the three reasoning forms in geologic mapping and constitute a new approach to the machine representation of geologic knowledge evolution. The approach also has potential to characterize the mapping of many types of geographic regions.     

How much information is geospatially referenced? Networks and cognition

The aim of this article is to provide a basis in evidence for (or against) the much-quoted assertion that 80% of all information is geospatially referenced. For this purpose, two approaches are presented that are intended to capture the portion of geospatially referenced information in user-generated content: a network approach and a cognitive approach. In the network approach, the German Wikipedia is used as a research corpus. It is considered a network with the articles being nodes and the links being edges. The Network Degree of Geospatial Reference (NDGR) is introduced as an indicator to measure the network approach. We define NDGR as the shortest path between any Wikipedia article and the closest article within the network that is labeled with coordinates in its headline. An analysis of the German Wikipedia employing this approach shows that 78% of all articles have a coordinate themselves or are directly linked to at least one article that has geospatial coordinates. The cognitive approach is manifested by the categories of geospatial reference (CGR): direct, indirect, and non-geospatial reference. These are categories that may be distinguished and applied by humans. An empirical study including 380 participants was conducted. The results of both approaches are synthesized with the aim to (1) examine correlations between NDGR and the human conceptualization of geospatial reference and (2) to separate geospatial from non-geospatial information. From the results of this synthesis, it can be concluded that 56–59% of the articles within Wikipedia can be considered to be directly or indirectly geospatially referenced. The article thus describes a method to check the validity of the ‘80%-assertion’ for information corpora that can be modeled using graphs (e.g., the World Wide Web, the Semantic Web, and Wikipedia). For the corpus investigated here (Wikipedia), the ‘80%-assertion’ cannot be confirmed, but would need to be reformulated as a ‘60%-assertion’.     

适宜空间认知结果表达的地图形式

心象地图是驻留在记忆中的关于地理世界空间特征认知结果的表达,具有如下特征:空间表达的非均一性、内容选取的主观性、空间定位的非确定性、度量特征上的非精确性.心象地图的可视化需要由特殊的图形形式来承担,经过分析提出了适宜这一表达特征的3种可视化技术,包括面向道路网认知表达的路网构架图、专题属性空间定位信息认知表达的面域拓扑图、虚拟网络空间导航认知的赛伯网络图.基于地图的定义,对这3种可视化形式度量特征进行了讨论,认为它们在有序量尺度上具有可度量特征.     

旅游者地理空间认知模式研究

根据地理空间认知理论,探讨了旅游者对地理空间认知的基本过程、特征以及基于不同空间信息表达方式的旅游者空间认知效果.研究发现旅游者的空间认知效果受到空间信息表达形式的影响;指出作为特殊群体的旅游者,其地理空间认知明显不同于一般人群,而主要集中在空间特征感知、空间对象认知和空间格局认知3个层次.旅游者空间特征感知受制于旅游场景;在空间对象认知方面侧重于旅游要素认知,主要采用旅游要素决定模式,其中距离认知采用时间决定模式;方向认知主要采用地标定向和拓扑关系判别模式;旅游景区的认知主要依据心理意象,大尺度旅游者采用文化差异选择模式,而中小尺度的旅游者则是功能差异选择模式;旅游空间格局认知则是旅游功能特征、旅游空间对象和地理特征认知的综合.     

LBS中多尺度空间方位的自然语言描述

位置服务是地理信息系统（GIS）应用的重要领域,GIS提供关于空间位置的坐标描述,但这不符合人们的认知和日常习惯。地理空间中人们日常的交流通常使用方位描述。基于自然语言的空间方位的描述对移动目标（如驾驶员）是十分重要的,通过规范的地点描述语言进行快速的地理定位,可提高人的空间反应和处理能力。本文依据人的多尺度空间认知,分析空间参考和定位习惯,结合自然语言描述知识,利用GIS分析功能,给出多尺度环境下空间方位的自然语言描述。     

小尺度环境地形相对高度认知及影响因素——以南京大学浦口校区为例

地形认知虽然是探讨人地互动的重要命题, 但目前研究甚少。本文选取南大浦口校园 为案例地, 在实验设计基础上, 采用非概率和分层比例抽样, 使用问卷调查和深度访谈的数 据收集方法, 历时两年, 共访谈调查了644名被试, 并运用定性与定量数据分析方法, 得出 小尺度环境地形认知一致性、参照体系特征、个体日常环境对认知的影响性等特点, 具体结 论如下:(1)认知一致性:被试在地形相对高度的认知方式与状况、地形特征点的辨识方面 具有较高一致性;且认知偏误率在空间上呈现一定的分布规律。(2)参照体系特征:被试使 用的环境参照物附近的地形多呈凹陷状且地势较低、空间临近特征显着, 并且它们多是被试 熟悉, 视觉通达性较好, 到访率较高的场所。(3)个体日常环境对认知的影响性:地形特征 的辨识及其相对高度认知受地理环境、认知、行为、情绪和态度等多方面因素影响, 其中决 定性因素是个体的日常生活环境。