GENERALIZATION OF IMAGE DATA TO GIS POLYGONS 
FOR CHANGE DETECTION AND DATA BASE REVISION 
Katarina Johnsson, PhD 
Dept. of Geodesy and Photogrammetry 
Royal Institute of Technology, KTH 
S - 100 44 Stockholm 
Sweden 
Commission IV, Working Group 3 
KEY WORDS: map revision, forest maps,.environmental monitoring, remote sensing 
ABSTRACT: Semi-automatic revision of geographic data bases from satellite imagery requires methods to perform 
change detection between map and image data. Most geographic databases are stored in vector-based geographic 
information systems, while analysis of satellite data requires raster GIS. It is argued that image data must be 
generalized into one or several polygon attributes to enable change detection between map and image data, and that 
change detection should take place in an attribute data base environment, rather than in a raster image environment. A 
framework for image generalization functions is presented, based on descriptive statistics. Statistical measures to 
describe central tendency, dispersion and spectral heterogeneity are discussed for quantitative and qualitative image 
data respectively. A case study is presented, which describes how forest change detection can be performed by 
regression between polygon attributes derived from map and image data of different dates. High detection accuracy is 
achieved for logged forest stands, confusion with objects of similar spectral characteristics is avoided, and the 
influence from natural spectral variation is minimized. 
for soil and forest maps. In these cases, the revision 
process has two distinct steps: 1) detection of changes 
1. INTRODUCTION with respect to database attribute(s), and 2) adjustment 
of geometric properties, e.g. by drawing new boundaries 
There is a need for efficient methods to revise digital and deleting old. This paper discusses the first step. 
geographic data bases. This paper is concerned with 
revision of small-scale geographic data bases Map revision from satellite data requires that change 
(>1:20,000) for natural resources management, and detection takes place from map to image data. This can 
specifically with revision of map polygon features. be done manually, by on-screen image interpretation and 
Satellite imagery provides an adequate data source for map overlay. However, operational revision of large 
revision for geographic databases at this scale. databases require the revision process to be, at least, 
semi-automated. Several issues need to be addressed 
A geographic data base will normally contain one or before semi-automatic database revision becomes 
several layers of digitized maps. Most geographic data reality, for example differences in data formats and in 
bases have been created and are being maintained in levels of abstraction between database and image data. 
vector-based Geographic Information Systems (GIS), 
where map features are represented either as points, 
lines or polygons. Polygon features are especially 2. CHANGE DETECTION FROM MAP TO IMAGE 
common in geographic databases for natural resources 
management, for example forest stands, animal habitats, Since integrated vector/raster analysis is currently not 
soil compartments, geomorphological terrain possible, one of the data sources must be processed to 
components, and watersheds. fit the other, before map-to-image change detection can 
take place. This is not only a question of format 
Satellite imagery is stored and processed in raster based conversion, but also a question of data abstraction. 
GIS or image analysis systems (IAS). Traditionally, Maps are highly abstracted representations of the real 
change detection has been focussed on pixelwise world, while image data is a lower form of information 
analysis between images of different dates (Singh, (Ehlers et al., 1991; Goodchild, 1989). 
1989). 
There are several reasons for why image data should be 
  
Revision of geographical databases can take place generalized to map polygons, rather than converting the 
either with respect to map attributes or with respect to vector map to raster data and performing pixelwise 
geometric properties. For natural resources databases, change detection (the traditional image analysis 
geometry and attributes are often interconnected, since approach): 
the boundaries of the map polygons are drawn based 
their attributes (Veregin, 1989). This is for example true ° The image data becomes immediately comparable 
to other polygon attributes in the attribute 
Current affiliation: T-Kartor Sweden AB, Box 5097, database. 
S-291 05 Kristianstad, Sweden 
email: katarina.johnsson @t-kartor.se 
384 
International Archives of Photogrammetry and Remote Sensing. Vol. XXXI, Part B4. Vienna 1996 
  
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