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GIS-Guided Road Extraction
form Satellite Imagery *
J. Van Cleynenbreugel F. Fierens P. Suetens A. Oosterlinck
ESAT-MI2, Katholieke Universiteit Leuven
Kardinaal Mercierlaan 94, B-3030 Heverlee, Belgium
email : vanclevn@esat.kuleuven.ac.be
Abstract
We present a (semi-)automatic system for road delineation on high resolution
satellite images that has capabilities to integrate different GIS-related knowledge
sources. The system is developed in an object-oriented image understanding envi
ronment based on an existing knowledge-engineering tool (KEE). In this way, GIS
data are easily represented and expertise can be added flexibly. The feasibility of the
concept has been tested on three practical case studies using SPOT and LANDSAT
TM data.
1 Introduction
Human analysts rely on expertise in combining external data (such as topographic maps
and landcover classifications), to solve a spatial image recognition problem like the ex
traction of roads and linear networks from remotely sensed imagery. Although such data
are now typically stored in a GIS environment, existing approaches to automatic road
extraction from satellite images have been hardly based on any knowledge related to GIS-
datasets. The following data sources and accompanying knowledge are important to human
experts to delineate road networks : global landcover classifications, existing roadmaps and
hydrographic maps and terrain (elevation) models. Depending on the complexity of the
task in terms of road-density, road-complexity and image quality, experts can decide what
sources must be involved. In this paper, we present three case studies employing different
knowledge sources.
The first case study principally deals with landcover-related knowledge. Delineating
forest paths in flat terrain is a typical example. A generic model describing the appearance
"The following text presents research results of the Belgian National incentive-program for fundamental
research in Artificial Intelligence, initiated by the Belgian State - Prime Minister’s Office - Science Policy
Programming. The scientific responsability is assumed by its authors.
