Integrating general principles into mixed-integer programming to optimize schematic network maps

ABSTRACT

Schematic maps are popular for the representation of transport networks. Many automated methods have been developed to generate such maps. In these methods, optimization techniques work with various sets of constraints. Most of these constraints govern geometric properties of individual features. A few constraints address relationships among features, but none explicitly deal with the main structure of an entire network. We believe that preservation of main structure is the most important and preservation of relative relations is helpful. This is because human perception follows a global-to-local process. These constraints have recently been formed into four general principles, with two for global structure and two for relativity of features. This study develops an automated method by integrating these principles into the mixed-integer programming (MIP) framework. Experimental evaluations have been conducted with two sets of real-world transit networks. In comparison to the existing method, the proposed method has smaller fractal dimensions, better computational performance and higher scores in terms of clarity, recognition of major lines, visual simplicity and satisfaction. Therefore, it is concluded that the proposed method can generate schematic maps with improved clarity and aesthetics. The idea in this study is also helpful for the design of other visual representations.     

An individual cognitive evacuation behaviour model for agent-based simulation: a case study of a large outdoor event

Route selection is a complex issue in simulating the pedestrian’s walking behaviour during the evacuation. In many current studies, the agent-based model has been widely used to simulate the individualized behaviour, and growing concern is given to the cognitive aspects in route selection. However, the influence of incomplete spatial knowledge and the preferences for different routing strategies has not been fully considered. To represent more reliable route choice by different pedestrians, this study presents an individual cognitive evacuation behaviour model which is mainly focusing on the individual differences in routing strategy and spatial knowledge. The model consists of two major components, namely the multiple routing strategies and personalized spatial cognitive road network. Based on a review of the previous studies, the potential factors that may affect the evacuation behaviour were discussed. The quantitative relationships between these potential factors and the pedestrian’s routing preference, as well as the possibilities of recognizing different roads, were explored using the regression method. As a case study, the proposed model was implemented using the data collected from a field survey of a real outdoor event. When applied in an agent-based simulation, the implemented model will support more reliable simulation of route choices corresponding to the pedestrians’ behaviour in the real event.     

Automatic alignment of contemporary vector data and georeferenced historical maps using reinforcement learning

ABSTRACT

With large amounts of digital map archives becoming available, automatically extracting information from scanned historical maps is needed for many domains that require long-term historical geographic data. Convolutional Neural Networks (CNN) are powerful techniques that can be used for extracting locations of geographic features from scanned maps if sufficient representative training data are available. Existing spatial data can provide the approximate locations of corresponding geographic features in historical maps and thus be useful to annotate training data automatically. However, the feature representations, publication date, production scales, and spatial reference systems of contemporary vector data are typically very different from those of historical maps. Hence, such auxiliary data cannot be directly used for annotation of the precise locations of the features of interest in the scanned historical maps. This research introduces an automatic vector-to-raster alignment algorithm based on reinforcement learning to annotate precise locations of geographic features on scanned maps. This paper models the alignment problem using the reinforcement learning framework, which enables informed, efficient searches for matching features without pre-processing steps, such as extracting specific feature signatures (e.g. road intersections). The experimental results show that our algorithm can be applied to various features (roads, water lines, and railroads) and achieve high accuracy.     

空三加密在数字摄影测量中的精度分析

该文结合章丘市1∶2000地形图绘制项目的具体实践,认为航空摄影测量产品误差来源主要为空三加密这一重要工序,影响空三加密精度的因素主要为:影像质量(分辨率、清晰度、重叠度)、像控点选取及精度、加密点的选取及加密解算方法、加密人员的经验等。找出影响空三加密精度的主要因素及解决办法,结合生产实践解决了1∶2000地形图绘制空三加密精度问题。     

基于MicroStation V8的地形图更新与质检系统的开发

在MicroStation VBA环境下,对MicroStation V8进行二次开发,实现了一套基于MicroStation V8平台的多比例尺地形图要素更新与质检系统。该文着重阐述了该系统在处理点、线、面、注记、属性、出图效果及质量检查控制等方面的设计。通过二次开发,快速实现了地形图的更新与维护,并有利于质量的控制,符合入库要求。     

专题地图数据库建设研究——以安徽省专题数据库为例

该文以建设安徽省专题地图数据库为基础,探讨了专题地图数据的建设方法,阐述了系统的总体设计、数据库的分层设计、功能设计和系统的框架设计。     

基于游客认知的历史地段城市记忆研究——以北京南锣鼓巷历史地段为例

城市记忆是城市特色形成的重要源泉,而历史地段则盛载着与城市的前世今生所相关的城市记忆.因而,探讨人们对历史地段城市记忆的认知规律,将为有效保存城市记忆、有机更新历史地段提供重要思路.本文选取北京南锣鼓巷历史地段作为研究对象,归纳游客对城市记忆的认知变量,构建了由信息和载体2 个一级变量衍生而得的20 个二级变量、89 个三级变量组成的城市记忆认知测量的指标体系,通过问卷对历史地段城市记忆的游客认知进行调查.基于调查数据统计,采用序次Logistic 回归模型,分析影响游客城市记忆认知水平的相关因素,构建城市记忆认知程度公式,归纳游客认知规律,以便为历史地段和城市旅游的规划、管理提供参考.     

Combination of historical maps and satellite images of the Banat region—Re-appearance of an old wetland area

The area of Banat, a historical region shared by Romania and Serbia, has been hit by a centennial flood event in spring 2005. The Temes (Tamiš/Timiş) River flooded several hundred km², with many settlements. The extent of the flood was partly unexpected, especially in positional sense. In order to achieve a better understanding of the phenomenon, we analysed the SRTM digital elevation model as well as historical maps. Several historical maps, dating back to the 16th century, indicate marshland or even a large lake in the area, not existing today but almost exactly coinciding with the extent of the 2005 flood.The historical and archive maps document the water regulation measures taken since the early 19th century. The actual flood is found to be a sort of a restoration of the original natural conditions. Via the analysis of the DEM and historical maps the unexpected extent of the flood scenario can be explained and understood. We suggest that an analysis of historical and archive maps, combined (geo-referenced) with high-resolution DEMS in other flood-endangered areas, should be used in order to be better prepared for decadal or centennial flood events induced by climatic change.     

旅游目的地形象与目的地感知吸引力关系——以厦门市为例

为明确目的地形象的细分维度与目的地感知吸引力的关系,以厦门市为例,基于问卷调查,利用Logistic回归模型实证研究认知形象、情感形象、总体形象对目的地感知吸引力的影响。结果表明：1）目的地品牌、自然和文化2个认知形象因子对目的地感知吸引力有显著正向影响,休闲娱乐和接待环境2个认知形象因子对目的地感知吸引力没有显著正向影响;2）情感形象、总体形象对目的地感知吸引力皆有显著正向影响;3）情感形象对目的地感知吸引力的影响大于认知形象对目的地感知吸引力的影响。