Fundamental operations in computer-assisted map analysis

Abstract

Geographical information systems (GIS) provide capabilities for the mapping, management and analysis of cartographic information. Unlike most other disciplines, GIS technology was born from specialized applications. A comprehensive theory relating the various techniques used in these applications is only now emerging. By organizing the set of analytic methods into a mathematical structure, a generalized framework for cartographic modelling is developed. Within this framework, users logically order primitive operators on map variables in a manner analogous to traditional algebra and statistics. This paper describes the fundamental classes of operations used in computer-assisted map analysis. Several of the procedures are demonstrated using a fourth-generation computer language for personal computers.     

The establishment and application of the geographic mapping database by city/county unit in China

Abstract

Based on information contained in the third population census and the second industrial investigation, and illustrated by maps, this paper discusses the conceptual design, methodology and procedures used in the establishment and application or the geographic mapping database. The statistical cartographic expert system is specifically introduced as an application.     

国家经济地图集的设计和制图可视化的方法技术

国家经济地图集是第一部全面,系统反映我国当前经济社会发展面貌和空间分布的大型科学参考地图集,它的编制是一项重大的制图系统工程,本文简要地阐述了图集编制研究的主要方面,包括从分析我国经济社会发展和现状出发,确定图集设计总体目标,为科学和形象地表达我国经济社会特征,而采用的可视化方法技术,以及智能化的计算机制图系统在图集制中的应用。     

MAPPING FROM AN AUTOMATED DISPLAY SYSTEM*

This paper outlines recent developments in computer mapping and points out its importance for visualizing contents of geographic information systems. The authors present an integrated system of mapping packages and spatial-data files. Map examoles generated with this system are used to illustrate characteristics of various computer-mapping methods. The diversity of displays created from a single set of data demonstrates that mapping from automated display systems requires the user to take some decisions which have to be based on an understanding of the phenomena displayed, of cartographic communication, and of technical aspects of automated map processing.     

Methods for visualizing the explosive remnants of war

This study aimed to answer the question how cartography can help decision makers visualize the problem of contamination by explosive remnants of war (ERW). We thus explored a set of six cartographic visualization methods and systematically evaluated their usefulness with respect to four categories of stakeholders in the humanitarian demining process (i.e., database administrators, operations officers, directors of national mine action authorities, and donors) at four geographical scales, ranging from municipal to global. The main application of our work is for stakeholders involved in humanitarian demining. We provide them with a comprehensive framework for visualizing ERW hazards at the geographical scale at which they have to make decisions, as well as customized cartographic visualization tools and recommendations to help them make informed decisions. For example, we provide potential donors with a method for obtaining a global overview of ERW contamination while remaining aware of regional variation and hot spots. We also enhance cartographic visualization capabilities using traditional kernel density estimation by customizing key parameters. Specifically, we propose a method for adjusting kernel bandwidth for datasets with highly heterogeneous spatial distributions and a method for generating kernel surfaces from polygon data that consists of infilling the polygons with points before using them as inputs in the kernel density estimation.     

A Review of “Geographies of Media and Communication”

Contemporary cartographic research on mapmaking and map use has a broad mandate and, as a consequence, researchers need a broad suite of methods. Consistent with research developments in other geographic subdisciplines, cartographic researchers now use qualitative methods. They offer the advantage of bringing research closer to the problem-solving realms of mapmakers and map users. Our purpose here is to discuss an array of qualitative methods for mapmaking and map use. Questionnaires, interviews, and protocol methods are used to gather verbal data about mapmaking and map use. Ethnographies produce data from direct observation of mapmakers and users. Maps also are sources for document analysis. We use examples of published cartographic research to elaborate on each of these methods.     

Cartographic generalisation of lines based on a B‐spline snake model

The automation of cartographic map production is still an important research field in Geographical Information Systems (GIS). With the increasing development of monitoring and decision‐aid systems either on computer networks or wireless networks, efficient methods are needed to visualise geographical data while respecting some application constraints (accuracy, legibility, security, etc.). This paper introduces a B‐spline snake model to deal with the current operators involved in the cartographic generalisation process of lines. This model enables us to perform those operators with a continuous approach. In order to avoid local conflicts such as intersections or self‐intersections, the consistency of the lines is checked and discrete operations such as segment removal are performed during the process. We apply the method to map production in the highly constrained domain of maritime navigation systems. Experimental results of marine chart generalisation yield some discussions about generalisation robustness and quality.     

A Review of: “Applications of Spatial Data Structures: Computer Graphics,Image Processing,and GIS”. By H. SAMET. (Addison-Wesley Publishing Company,Inc, 1989.) [Pp. xv + 507; figures,tables, appendix,references, name and credit index,subject index.] Price US $49.95. ISBN 020150300 X (hardback).

The introduction of automated generalisation procedures in map production systems requires that generalisation systems are capable of processing large amounts of map data in acceptable time and that cartographic quality is similar to traditional map products. With respect to these requirements, we examine two complementary approaches that should improve generalisation systems currently in use by national topographic mapping agencies. Our focus is particularly on self‐evaluating systems, taking as an example those systems that build on the multi‐agent paradigm. The first approach aims to improve the cartographic quality by utilising cartographic expert knowledge relating to spatial context. More specifically, we introduce expert rules for the selection of generalisation operations based on a classification of buildings into five urban structure types, including inner city, urban, suburban, rural, and industrial and commercial areas. The second approach aims to utilise machine learning techniques to extract heuristics that allow us to reduce the search space and hence the time in which a good cartographical solution is reached. Both approaches are tested individually and in combination for the generalisation of buildings from map scale 1:5000 to the target map scale of 1:25 000. Our experiments show improvements in terms of efficiency and effectiveness. We provide evidence that both approaches complement each other and that a combination of expert and machine learnt rules give better results than the individual approaches. Both approaches are sufficiently general to be applicable to other forms of self‐evaluating, constraint‐based systems than multi‐agent systems, and to other feature classes than buildings. Problems have been identified resulting from difficulties to formalise cartographic quality by means of constraints for the control of the generalisation process.     

Qualitative Methods for Research on Mapmaking and Map Use

Contemporary cartographic research on mapmaking and map use has a broad mandate and, as a consequence, researchers need a broad suite of methods. Consistent with research developments in other geographic subdisciplines, cartographic researchers now use qualitative methods. They offer the advantage of bringing research closer to the problem‐solving realms of mapmakers and map users. Our purpose here is to discuss an array of qualitative methods for mapmaking and map use. Questionnaires, interviews, and protocol methods are used to gather verbal data about mapmaking and map use. Ethnographies produce data from direct observation of mapmakers and users. Maps also are sources for document analysis. We use examples of published cartographic research to elaborate on each of these methods.     

Road network simplification with knowledge-based spatial analysis

A typical requirement in digital society is the rapid distribution and effective application of digital products. Geographical data bases are far more complex than other ones in that both attribute and spatial data have to be stored and handled under the same framework. On the other hand, the number of end users of digital cartographic data is explosively increasing, ranging from professional map makers to vehicle drivers and individual tourists. Thus arises a question: how can a data supplier give the “best” service to each user? In nature it involves such difficult problems as cartographic generalization and map simplification. In this paper, the author argues that the visual knowledge or perception experience can be effectively exploited and used to guide the process of data simplification. We have developed a prototype system with a subset of the vector road database covering Munich city.

     

Automatic extraction of road intersection points from USGS historical map series using deep convolutional neural networks

ABSTRACT

Road intersection data have been used across a range of geospatial analyses. However, many datasets dating from before the advent of GIS are only available as historical printed maps. To be analyzed by GIS software, they need to be scanned and transformed into a usable (vector-based) format. Because the number of scanned historical maps is voluminous, automated methods of digitization and transformation are needed. Frequently, these processes are based on computer vision algorithms. However, the key challenges to this are (1) the low conversion accuracy for low quality and visually complex maps, and (2) the selection of optimal parameters. In this paper, we used a region-based deep convolutional neural network-based framework (RCNN) for object detection, in order to automatically identify road intersections in historical maps of several cities in the United States of America. We found that the RCNN approach is more accurate than traditional computer vision algorithms for double-line cartographic representation of the roads, though its accuracy does not surpass all traditional methods used for single-line symbols. The results suggest that the number of errors in the outputs is sensitive to complexity and blurriness of the maps, and to the number of distinct red-green-blue (RGB) combinations within them.     

Cartographic Visualization: An Assessment and Epistemological Review*

This article examines the concept of cartographic visualization. The value of cartographic visualization as an essential component in the study of geographic phenomena is discussed. Ontological and epistemological perspectives are addressed, with examinations of positivist, realist, postmodern, feminist, and anarchist approaches to visualization. Critiques of cartographic visualization from social theorists and quantitative positivists are presented. The author asserts that cartographic visualization is not restricted to any one particular epistemological framework but may combine methods of knowledge production. For comprehensive analysis of spatial data, cartographic visualization must be included along with other qualitative and quantitative analysis.     

School Students' Understanding of Choropleth Maps: Evidence From Collaborative Mapmaking Using GIS

Abstract

Pairs of students from two age groups made choropleth maps using Arc View. Evidence from their discourse is used to assess aspects of their cartographic understanding as well as the nature of their collaboration. Students from both age groups spent a high percentage of their time talking about cartographic strategy and a low percentage of time on technical aspects of GIS functionality. Older students engaged in more reasoning and questioning. Key areas for teacher intervention include promoting better student understanding of what the mapped data mean (including directionality and numerical characteristics) and the most effective strategies for raising the level of students' conceptual exchange during collaborative learning.     

The impact of geographical information systems on the role of spatial data libraries

Abstract

The proliferation of digital cartographic and geographic information technologies has provided an obvious alternative to paper for the storage of maps. Not unlike their paper predecessors, digital maps must be indexed to provide sufficient access points to information and to allow the librarian carto-bibliographic control over the collection. Maps have traditionally been treated as ‘unusual’ books and librarians have relied primarily on cataloguing strategies designed for books. Most automated cataloguing efforts involve nothing more than the computerization of card catalogues without altering the nature and design of the task. This paper examines the utilities and unique qualities of cartographic materials and accounts for deficiencies of traditional cataloguing methods for the handling of both analogue and digital cartographic products. In view of the increased availability of digital cartographic databases, this paper also evaluates requirements and presents issues beyond the conventional responsibilities of spatial data librarianship.     

地图可视化研究

建立在计算机技术基础上的地图可视化是现代地图学的核心内容之一。文章从分析地图可视化的含义出发,提出了地图可视化研究的一个基本框架,同时简要分析了地图可视化的特点。认为地图可视化的主要研究领域有:可视化变量研究、可视化分类研究、时空数据结构研究、视觉感受与视觉效果研究、虚拟现实研究、空间认知与信息传输研究等 6个方面。最后,就北京地区地形三维可视化实践作了简单介绍。     

Algorithms for automated line generalization1 based on a natural principle of objective generalization

Abstract

This article describes a new set of algorithms for locally–adaptive line generalization based on the so-called natural principle of objective generalization. The drawbacks of existing methods of line generalization are briefly discussed and the algorithms described. The performance of these new methods is compared with benchmarks based on both manual cartographic procedures and a standard method found in many geographical information systems.     

From 1 dimension to N dimensions-fractal in automated cartographic generalization

Automated cartographic generalization has been an intensive research topic in cartography for decades. Some problems associated with this topic could be resolved to a certain extent using fractal analysis and fractal dimension. This paper investigates the fundamental theories and operational methods of generalization. Among others, methods of calculating fractal dimensions of curves and even complicated 3-dimensional geographic objects are explained. Fractal dimensions can be used as an objective criterion for both scaling the natural geographic objects and economical computer storage. More important is that the generalization algorithms based on fractal dimensions can be performed automatically.     

Quadtree storage of vector data†

Abstract

Vector data storage has various advantages in a cartographic or geographical information system (GIS) environment, but lacks internal spatial relationships between individual features. Quadtree structures have been extensively used to store and access raster data. This paper shows how quadtree methods may be adapted for use in spatially indexing vector data. It demonstrates that a vector quadtree stored in floating point representation overcomes the classical problem with raster quadtrees of data approximation. Examples of vector quadtrees applied to realistic size data sets are given     

Land cover and land use change in the Italian central Apennines: A comparison of assessment methods

Analyses of land-use cover changes (LUCC) are fundamental to the understanding of numerous social, economical and environmental problems and can be carried out rapidly, using either cartographic or census data. However, the trends of the two methods differ in direction and quantity.For this study, a historical and a recent remote sensing-derived map were homogenized to reduce misleading changes and to assess spatial aggregation errors. This was carried out by means of a data integration procedure based on landscape metrics, allowing cartographic and census trends to be compared. Discrepancies between data were thus highlighted, both in absolute surface value and in evolution.The methodology presented, and the results obtained, could be employed to evaluate and improve LUCC analyses aimed at assessing landscape identity, both in the case of analyses based only on LU census data, or of those based only on LC cartographic data. This could lead to benefits for both biodiversity conservation and environmental planning on a large scale.