Academic journal article Cartography & Geographic Information Systems

Generating Street Center-Lines from Inaccurate Vector City Maps

Academic journal article Cartography & Geographic Information Systems

Generating Street Center-Lines from Inaccurate Vector City Maps

Article excerpt

ABSTRACT: This paper addresses the problem of automatically generating city street networks from a possibly inaccurate vector description of their blocks. The street network, represented as a graph structure with attributes related to both streets and crossings, is a fundamental data structure for a large number of applications, including urban planning and transport management. The considered inaccuracies derive from the typical errors introduced during hand digitizing; i.e., undershooting, overshooting, stacking, and layer misplacing. Extracting the street net when all these possible errors are present is not an easy task because of the huge amount of particular cases to be considered. The presented algorithm is based on the translation of the vector information directly into a run-length encoded binary image. Then, corrections of the above errors and of the street net extraction can be expressed in terms of well known, simple, morphological operations. In order to lower computational costs, the key idea has been to carry out these operations directly on the encoded image. The result is an algorithm that is faster than expected, easy to implement, and, as a consequence, more generally applicable.

Introduction

Maps are frequently obtained by processing terrain images from satellite vision systems. Not only hand digitizing but also image processing and pattern recognition techniques have been used to extract different kinds of information from these aerial photographs for geological or topographical purposes (Pike 1992). This information lies at the base of most geographic information systems (GIS), i.e. systems that are both databases designed to work with data referenced by spatial or geographic coordinates, as well as sets of procedures for analyzing these data (Star and Estes 1990).

Geographic information systems are widely used in different areas, including military applications, environmental studies, and geological exploration. They have proved to be of particular interest in town mapping where a huge amount of structured data, including street names, street numbers, special site locations, etc., have to be linked to particular geometric entities. We will focus on this kind of maps.

City maps are usually obtained by standard manual digitizing of aerial photographs. One of the major tasks of this labor-intensive work consists of digitizing the road sides and storing the result in a particular layer linework. Utility companies use this information and insert their own distribution networks and related information on separate layers.

The algorithm discussed herein automatically extracts the street network--which is seldom directly available--from the road layer. This information, represented as a graph structure with attributes related to both streets and crossings, is a fundamental data structure for a large number of applications used by utility companies.

On the Difficulty of the Task

It seems to be an easy task to decide where the streets are by simply inspecting where the city blocks have been placed. In practice, however, this is a hard task because of two mare reasons: (a) vector drawing representations are not unique; and (b) they are, in general, neither accurate nor complete. Below, we present a brief discussion of problems associated with street network automation.

Vector representations have great advantages when working with town maps. They certainly reduce storage costs, simplify scaling, and ease geometric structure modifications. Nevertheless, they do have a major drawback which results from the fact that completely different vector drawings, i.e., with very different underlying geometric entities, lead to the same graphical appearance. These differences are often due to errors in digitizing, as explained below.

For example, the triangle in Figure 1 can be represented using a three-sided polygon, a polyline, and a set of possibly overlapping segments, all of them providing the same appearance on the screen. …

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