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INTEGRATION OF GEOSCIENTIFIC DATA SETS AND THE GERMAN DIGITAL MAP 
USING A MATCHING APPROACH 
G. v. Gósseln, M. Sester 
Institute of Cartography and Geoinformatics, University of Hannover, Appelstr. 9a, 30167 Hannover, Germany — 
(guido.vongoesseln, monika.sester} @ikg.uni-hannover.de 
Commission IV, WG IV/7 
KEY WORDS: Cartography, GIS, Geology, Soil, Change Detection, Integration 
ABSTRACT: 
The integration of various data sets can be the answer for geoscientific questions on the one hand, but a disadvantage on the other 
hand, due to the differences in representation and content. Although geoscientific data sets typically refer to the same physical data 
source — the earth surface — and therefore also relate to topographic objects, these data sets differ in geometry, accuracy and actuality 
in most cases. In former times differences between analogue maps were not as apparent as today when different data sets are overlaid 
in a modern GIS-application. Integrating different data sets — in our case topographic data and geoscientific data — allows for a 
consistent representation and thus for the propagation of updates from one data set to the other. This problem leads to three steps, 
namely harmonisation, change detection and updating which are necessary to ensure consistency, but hardly practicable when 
performed manually. 
For a harmonization of data sets of different origin, firstly the revelation of semantic differences is required; to this end, the object 
catalogues are compared and semantically corresponding objects are identified. In this step, also the cardinality of possible 
matchings between the objects in the different representations is determined (l:l, En, n:m). The identification of geometric 
differences between the one-layered geoscientific and the multi-layered German digital map (ATKIS) will be fulfilled in the next 
step. In order to identify corresponding object-pairs between the data sets, different criteria like area, shape and position are used. 
Due to different levels of generalisation the detection of matches between groups of objects and single objects is implemented. 
Corresponding objects which have been selected through semantic and geometric integration are investigated for change detection 
using intersection methods. 
The geometric differences which are visible as discrepancies in position, scale and size due to simple superimposition will lead to 
unsatisfying results. Therefore, the iterative closest point (ICP) algorithm is implemented to achieve the best fit between the objects. 
The evaluated results can be classified into three types, of which two types can be handled automatically, and for one type an 
automatic proposal is given by the software. This leads to a significant reduction of time and resources because the approach reduces 
the objects to be investigated manually to only those situations where manual intervention is inescapable. 
The paper gives an overview of the problem and focuses on the geometric integration, especially on the matching of groups of 
  
  
objects and the adaptation of the object's shape. 
I. INTRODUCTION 
Geoscientific and environmental problems often require the 
usage of different data sources to achieve a satisfying result. 
The combination of different data sources offers the advantage 
to benefit from their respective merits. In former times these 
data sets were used in only analogue representations, but today 
the main part of geoscientific data sets are available as digital 
data sets. 
The data sets which have been acquired for geoscientific 
purposes rely on the same source, the earth surface. 
Despite this fact they show significant differences due to 
different acquisition methods, formats and thematic focus, 
different sensors, level of generalisation, and even different 
interpretation of a human operator. Sometimes new acquisition 
is therefore needed to create a single homogenous data set. 
Another problem which occurs while working with different 
data sets is the problem of temporal inconsistency: 
Even if the data sets originally are related to the same objects, 
different update cycles in the different thematic data sets lead to 
significant discrepancies. Observing this problem it is obvious 
that harmonisation, change detection and updating of different 
data sets is necessary to ensure consistency, but hardly 
practicable when performed manually. 
Professionals from different geoscientific domains in Germany 
take advantage of the geological (GK) and the soil-science map 
(BK). These maps have a very strong thematic focus, but they 
do not contain the amount of topographic content, which is 
mandatory for different tasks to be solved. Therefore these data 
sets are combined with the german digital topographic data set 
(ATKIS). Unfortunately these data sets have been digitized 
from analogue maps and they differ in acquisition time, 
representation type and temporal consistency. which makes 
integration hardly possible. 
In a project of the German Ministry of: Education and Research 
under the headline “GEOTECHNOLOGIEN™, a research group 
at the University of Hannover, consisting of three institutes 
from surveying and computer science, is dealing with the 
problem of data integration, applied to data sets from 
topography, geology and soil science. The project deals with 
different aspects of data integration, namely integration of 
different vector data sets, integration of vector and raster data, 
as well as providing an underlying data structure in terms of a 
federated data base, allowing a separate, autonomous storage of 
the data, however linked and integrated by adapted 
reconciliation functions for analysis and queries on the different 
data sets (Sester et al., 2003). 
This paper focuses on the work of the Institute of Cartography 
and Geoinformatics (ikg), namely the integration of vector data. 
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