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.     

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。     

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.     

圣保罗大都市区社会空间分异研究——多元统计方法在城市连绵区的应用

空间数据和地理信息系统在城市规划和决策中应用的重要性日见凸显。主要原因在于：重要的人口数据和社会变动经常表现出一定的空间特性,这种特性可以通过空间分析和统计方法被认识和解释。应用多元分析的空间分类方法编制圣保罗大都市区社会分异地图并进行相关分析。研究的主要数据来自2000年巴西全国人口普查,其中包括了圣保罗大都市的所有行政区和39个自治市的21774个人口普查区。为了把都市连绵区从数据全集中分离出来,我们采用混合技术进行互补分析,即在2000年4月30日的陆地卫星7号图像中绘制一个个多边形,这些被识别出来的多边形就是人口普查区。然后,通过目视解译出假彩色多边形集合。应用空间分类评分程序将这些多边形分成五类,并建立人口普查区的数目、覆盖的面积和都市连绵区之间的关系。这种多元分析方法是基于变量的均衡化来生成易于用分级统计图描述平均值,以促进可视化和后续的空间分布分析。基于多元分析的空间分类方法研究,清楚地展现了圣保罗大都市最重要的社会特征,也说明城市社会地图方法和多元分析的空间分类方法在大都市区的管理、公共政策规划和复杂决策中具有重要的应用价值。     

Competitive Learning Approach to GIS Based Land Use Suitability Analysis

This paper uses the expected utility under risk hypothesis to develop a new approach to GIS modeling for land use suitability analysis with competitive learning algorithms (CLG-LUSA). It uses Kohonen’s Self Organized Maps (SOM) and Linear Vector Quantization (LVQ) among other tools to create comprehensive ordering of high number of options. The model uses decision makers preferred locations and environmental data to construct a manifold of the decision’s attribute space. Then, decision and uncertainty maps are derived from this manifold. An application example is provided using the selection of suitable environments for coconut development in a municipality of Cuba. CLG-LUSA model was able to provide accurate visual feedback of key aspects of the decision process, making the methodology suitable for personal or group decision making.