Ontologies and representation spaces for sketch map interpretation

In this paper, we present a systematic approach to sketch map interpretation. The method decomposes the elements of a sketch map into a hierarchy of categories, from the material sketch map level to the non-material representational sketch map level, and then interprets the sketch map using the five formal representation spaces that we develop. These spaces (set, graph, metric and Euclidean) provide a tiered formal representation based on standard mathematical structures. We take the view that a sketch map bears information about the physical world and systematises this using extensions of existing formal ontologies. The motivation for this work is the partially automatic extraction and integration of information from sketch maps. We propose a set of ontologies and methods as a first step in the direction of a formalisation of partially automatic extraction and integration of sketch map content. We also see this work as a contribution to spatial cognition, where researchers externalise spatial knowledge using sketch mapping. The paper concludes by working through an example that demonstrates the sketch map interpretation at different levels using the underlying method.     

Spatial subdivision of complex indoor environments for 3D indoor navigation

As we realize that we spend most of our time in increasingly complex indoor environments, applications to assist indoor activities (e.g. guidance) have gained a lot of attention in the recent years. The advances in ubiquitous computing made possible the development of several spatial models intending to support context-aware and fine-grained indoor navigation systems. However, the available models often rely on simplified representations (e.g. 2D plans) and ignore the indoor features (e.g. furniture), thereby missing to reflect the complexity of the indoor environment. In this paper, we introduce the Flexible Space Subdivision framework (FSS) that allows to automatically identify the spaces that can be used for indoor navigation purpose. We propose a classification of indoor objects based on their ability to autonomously change location and we define a spatial subdivision of the indoor environment based on the classified objects and their functions. The framework can consider any 3D indoor configuration, the static and dynamic activities it hosts and it enables the possibility to consider all types of locomotion (e.g. walking, flying, etc.). It relies on input 3D models with geometric, semantic and topological information and identifies a set of subspaces with dedicated properties. We assess the framework against criteria defined in previous researches and we provide an example.     

一种启发式A*算法和网格划分的空间可达性计算方法

本文提出了一个适用于研究城市内部的个体或商业区位的微观可达性计算方法,该方法的核心是将研究区域进行等距的网格划分,通过计算每个网格的可达性指标,来研究整个区域的可达性的空间分布特点。在可达性计算中,利用网格内的道路密度和土地利用状态这两个因素来模拟计算每个网格的交通成本,引入了启发式A ^*空间搜索算法来计算网格间路径的交通成本,并且加入适当的启发信息,提高了搜索效率,使搜索结果更符合实际需求。最后,基于本文提出的方法,利用GIS二次开发工具ArcEngine开发了计算程序,收集了多源数据,以广州市商务区的可达性作为计算对象,进行了商务区的可达性和易达性案例计算。     

An algorithm for on-the-fly K shortest paths finding in multi-storey buildings using a hierarchical topology model

This article presents an approach to computing K shortest paths in large buildings with complex horizontal and vertical connectivity. The building topology is obtained from Building Information Model (BIM) and implemented using directed multigraphs. Hierarchical design allows the calculation of feasible paths without the need to load into memory the topology of the entire building. It is possible to expand the graph with new connectivity on-the-fly. The paths calculated may be composed of traversable building components that are located inside the buildings or those that are both inside and outside buildings. The performance (computational time and heap size used) is optimized by using the appropriate collections (maps, lists and sets). The proposed algorithm is evaluated in several use-case scenarios – complete graphs and real building environments. In all test scenarios, the proposed path finding algorithm is faster and uses less memory when compared to the fast version of the Yen’s KSP algorithm. The proposed approach can be successfully used as a first level of coarse-to-fine path finding algorithms.     

Formal representation of qualitative direction

This paper reviews formal approaches to representing spatial knowledge about qualitative direction. Unlike geometric direction information, qualitative information does not employ numerical values but relies on comparison. The qualitative approach is often regarded as suitable for capturing commonsense concepts and thus is relevant to human-centered interfaces for spatial information systems. To establish a context for the work on qualitative direction, we preset a brief history of the development of qualitative temporal and spatial representations from different scientific perspectives. We identify main focal areas of these representations of spatial direction and propose a taxonomy. In the light of more than three decades of fruitful research, we obtain a map of formal representations that reveal interrelationships between different research strands in the field.     

3D building roof reconstruction from airborne LiDAR point clouds: a framework based on a spatial database

Three-dimensional (3D) building models are essential for 3D Geographic Information Systems and play an important role in various urban management applications. Although several light detection and ranging (LiDAR) data-based reconstruction approaches have made significant advances toward the fully automatic generation of 3D building models, the process is still tedious and time-consuming, especially for massive point clouds. This paper introduces a new framework that utilizes a spatial database to achieve high performance via parallel computation for fully automatic 3D building roof reconstruction from airborne LiDAR data. The framework integrates data-driven and model-driven methods to produce building roof models of the primary structure with detailed features. The framework is composed of five major components: (1) a density-based clustering algorithm to segment individual buildings, (2) an improved boundary-tracing algorithm, (3) a hybrid method for segmenting planar patches that selects seed points in parameter space and grows the regions in spatial space, (4) a boundary regularization approach that considers outliers and (5) a method for reconstructing the topological and geometrical information of building roofs using the intersections of planar patches. The entire process is based on a spatial database, which has the following advantages: (a) managing and querying data efficiently, especially for millions of LiDAR points, (b) utilizing the spatial analysis functions provided by the system, reducing tedious and time-consuming computation, and (c) using parallel computing while reconstructing 3D building roof models, improving performance.     

Computing the fewest-turn map directions based on the connectivity of natural roads

In this article, we introduce a novel approach to computing the fewest-turn map directions or routes based on the concept of natural roads. Natural roads are joined road segments that perceptually constitute good continuity. This approach relies on the connectivity of natural roads rather than that of road segments for computing routes or map directions. Because of this, the derived routes possess the fewest turns. However, what we intend to achieve are the routes that not only possess the fewest turns but are also as short as possible. This kind of map direction is more effective and favored by people because they bear less cognitive burden. Furthermore, the computation of the routes is more efficient because it is based on the graph encoding the connectivity of roads, which is substantially smaller than the graph of road segments. We experimented on eight urban street networks from North America and Europe to illustrate the above-stated advantages. The experimental results indicate that the fewest-turn routes possess fewer turns and shorter distances than the simplest paths and the routes provided by Google Maps. For example, the fewest-turn-and-shortest routes are on average 15% shorter than the routes suggested by Google Maps, whereas the number of turns is just half as much. This approach is a key technology behind FromToMap.org – a web mapping service using openstreetmap data.     

How much past to see the future: a computational study in calibrating urban cellular automata

The objective of this computational study was to investigate to which extent the availability and the way of use of historical maps may affect the quality of the calibration process of cellular automata (CA) urban models. The numerical experiments are based on a constrained CA applied to a case study. Since the model depends on a large number of parameters, we optimize the CA using cooperative coevolutionary particle swarms, which is an approach known for its ability to operate effectively in search spaces with a high number of dimensions. To cope with the relevant computational cost related to the high number of CA simulations required by our study, we use a parallelized CA model that takes advantage of the computing power of graphics processing units. The study has shown that the accuracy of simulations can be significantly influenced by both the number and position in time of the historical maps involved in the calibration.     

基于Lowry模型的北京市城市空间结构模拟

以Lowry模型为理论支撑,以北京市发展现状为研究对象,从模型构建、参数设置和情景模拟三个方面探索Lowry 模型框架在城市空间结构研究中的应用。① 基于杜能区位论,构建以区域地租总额最大化为目标函数,以北京市经济发展现状、现有土地资源供给为约束条件的线性规划模型。② 以北京市2010 年投入产出表、2011 年北京市统计年鉴、2010 年北京市企业调查数据等数据来源为支撑,完成模型相关参数的设置。③ 以北京市市域为研究对象,以乡镇街道办为基本研究单元,基于对北京市基本行业分布格局分析,构建模型的情景约束条件。④ 模拟分析了在北京市基本行业空间格局框架确定情况下的城市产业、居住空间分布特征,总结了模型的结构启示及模型的模拟启示。本文不仅丰富了模型框架的内涵,而且在实际应用中检验了模型的技术流程和分析能力,为基于Lowry模型的城市空间结构分析框架形成奠定基础,拓展了国内城市空间结构研究的研究视角。     

An Extended Minimum Spanning Tree method for characterizing local urban patterns

Detailed and precise information on urban building patterns is essential for urban design, landscape evaluation, social analyses and urban environmental studies. Although a broad range of studies on the extraction of urban building patterns has been conducted, few studies simultaneously considered the spatial proximity relations and morphological properties at a building-unit level. In this study, we present a simple and novel graph-theoretic approach, Extended Minimum Spanning Tree (EMST), to describe and characterize local building patterns at building-unit level for large urban areas. Building objects with abundant two-dimensional and three-dimensional building characteristics are first delineated and derived from building footprint data and high-resolution Light Detection and Ranging data. Then, we propose the EMST approach to represent and describe both the spatial proximity relations and building characteristics. Furthermore, the EMST groups the building objects into different locally connected subsets by applying the Gestalt theory-based graph partition method. Based on the graph partition results, our EMST method then assesses the characteristics of each building to discover local patterns by employing the spatial autocorrelation analysis and homogeneity index. We apply the proposed method to the Staten Island in New York City and successfully extracted and differentiated various local building patterns in the study area. The results demonstrate that the EMST is an effective data structure for understanding local building patterns from both geographic and perceptual perspectives. Our method holds great potential for identifying local urban patterns and provides comprehensive and essential information for urban planning and management.     

基于手机信令数据的深圳市二元居住空间迁居模式研究

迁居是城市空间重构的基础动力,了解其行为机制对改善住房结构、优化空间组织具有重要意义,然而目前针对大城市内部、正规与非正规二元居住空间并存的迁居研究仍较薄弱。本文基于生命历程理论与家庭迁居理论,利用2018年12月至2019年12月的手机信令等多源数据,识别深圳市二元居住空间分布和迁居流样本,从迁居流特征、邻里属性和二元空间类型三方面选取指标开展基于主成分分析的K-means聚类,探究迁居模式、结构特性与形成原因。结果表明：(1)非正规内部、正规与非正规交互、正规内部三层次迁居类型间存在年龄和居住质量递增的趋势,但均呈现通勤导向;(2)二元迁居的主体是短距离迁移,形成了4个大规模迁居网络集群,总体方向表现出郊区化趋势;(3)迁居模式可聚类为社区型、改善型、家庭型、事业型4类,结合二元空间分异影响呈现出8亚类,不同类型迁居群体属性和动因存在显著差别,总体反映出人们在不同生命历程下的迁居过程。最后,文章针对不同迁居模式提出差异化空间治理政策建议。     

Wholeness as a hierarchical graph to capture the nature of space

According to Christopher Alexander’s theory of centers, a whole comprises numerous, recursively defined centers for things or spaces surrounding us. Wholeness is a type of global structure or life-giving order emerging from the whole as a field of the centers. The wholeness is an essential part of any complex system and exists, to some degree or other, in spaces. This paper defines wholeness as a hierarchical graph, in which individual centers are represented as the nodes and their relationships as the directed links. The hierarchical graph gets its name from the inherent scaling hierarchy revealed by the head/tail breaks, which is a classification scheme and visualization tool for data with a heavy-tailed distribution. We suggest that (1) the degrees of wholeness for individual centers should be measured by PageRank (PR) scores based on the notion that high-degree-of-life centers are those to which many high-degree-of-life centers point, and (2) that the hierarchical levels, or the ht-index of the PR scores induced by the head/tail breaks, can characterize the degree of wholeness for the whole: the higher the ht-index, the more life or wholeness in the whole. Three case studies applied to the Alhambra building complex and the street networks of Manhattan and Sweden illustrate that the defined wholeness captures fairly well human intuitions on the degree of life for the geographic spaces. We further suggest that the mathematical model of wholeness be an important model of geographic representation, because it is topological oriented, which enables us to see the underlying scaling structure. The model can guide geodesign, which should be considered as the wholeness-extending transformations that are essentially like the unfolding processes of seeds or embryos, for creating built and natural environments of beauty or with a high degree of wholeness.     

The right to move: informal use rights and urban practices of mobility

Everyday urban practices are enabled by both formal and informal rights regimes. Researchers often focus on the effects of formal rights; informal rights to use urban spaces have been less widely examined, particularly in North America. This article examines practices of intra-urban mobility in a gentrifying area of Portland, Oregon. We find that rights regimes regarding movement in urban space importantly shape who uses particular transit strategies and infrastructures. Specifically, we identify rights regimes rooted in explications of a city ideal and a neighborhood ethic. We suggest that Portland’s widely admired transit planning process has not sufficiently engaged with informal use rights in transit spaces, leading to uneven adoption of a transportation infrastructure that re-inscribes historic racialized injustices. An examination of informal use rights complicates common rights analytics, including those leveraging Lefebvre’s right to the city, emphasizing how all urban rights are contingent, contested and negotiated.     

LOCATIONAL PROBLEMS AND PREFERENCES IN PRESCHOOL CHILD CARE*

With the increased use of formal child care, the number of child care alternatives has grown. The locational problems and preferences of University of Connecticut employees who use formal child care for children under age 6 are examined because an on-site program is available as one option. Difficulty finding care at a convenient location is related to residential location. Preference for worksite care decreases with increasing commuting distance. Variations in reported locational preferences by commuting zone are consistent with the notion of locating services within the activity spaces of the users. As commuting distance increases, worksite day care represents a greater displacement from the activity spaces of the child and possibly of other family members.     

A spatial cognition-based urban building clustering approach and its applications

This article presents a spatial cognition analysis technique for automated urban building clustering based on urban morphology and Gestalt theory. The proximity graph is selected to present the urban mrphology. The proximity graph considers the local adjacency among buildings, providing a large degree of freedom in object displacement and aggregation. Then, three principles of Gestalt theories, proximity, similarity, and common directions, are considered to extract potential Gestalt building clusters. Next, the Gestalt features are further characterized with seven indicators, that is, area difference, height difference, similarity difference, orientation difference, linear arrangement difference, interval difference, and oblique degree of arrangement. A support vector machine (SVM)-based approach is employed to extract the Gestalt building clusters. This approach transforms the Gestalt cluster extraction into a supervised discrimination process. The method presents a generalized approach for clustering buildings of a given street block into groups, while maintaining the spatial pattern and adjacency of buildings during the displacement operation. In applications of urban building generalization and three-dimensional (3D) urban panoramic-like view, the method presented in this article adequately preserves the spatial patterns, distributions, and arrangements of urban buildings. Moreover, the final 3D panoramic-like views ensure the accurate appearance of important features and landscapes.     

A combinatorial data model for representing topological relations among 3D geographical features in micro‐spatial environments

This research is motivated by the need for 3D GIS data models that allow for 3D spatial query, analysis and visualization of the subunits and internal network structure of ‘micro‐spatial environments’ (the 3D spatial structure within buildings). It explores a new way of representing the topological relationships among 3D geographical features such as buildings and their internal partitions or subunits. The 3D topological data model is called the combinatorial data model (CDM). It is a logical data model that simplifies and abstracts the complex topological relationships among 3D features through a hierarchical network structure called the node‐relation structure (NRS). This logical network structure is abstracted by using the property of Poincaré duality. It is modelled and presented in the paper using graph‐theoretic formalisms. The model was implemented with real data for evaluating its effectiveness for performing 3D spatial queries and visualization.     

广州主城区建筑组合的类型、空间分布与影响因素

基于2017年广州市单体建筑数据,以建筑高度和建筑间距2个指标,确定主城区基本的建筑组合,利用热点分析辨识更高尺度上的建筑组合,在此基础上分析广州建筑组合的空间分布及其影响因素.主要结论有:1)建筑组合有9种基本类型,4272斑块数量与面积在占比上具有很强的同步性.2)百米尺度斑块构成了主城区建筑组合的基本单元,并以混...     

Multi-criteria modelling and clustering of spatial information

To improve the formal integration of verbally given spatial information in a geographical information system, a methodology for converting such information to a geographical representation was developed. This was applied to examples of a spatial-related analysis of natural language text messages in the domain of disaster management. This article presents an approach for such a conversion by using a suitable knowledge representation as well as formal modelling structures. The structures are provided by an ontology-supported knowledge base. With respect to spatial uncertainty, a formal representation based on possibility theory was defined. Moreover, a cluster algorithm was developed for handling information of different sources and building a spatial context.