Volker Walter

Matching spatial data sets: a statistical approach

Although the acquisition and maintenance of spatial data is very costly and time consuming very often the same objects of the real world are captured in many different data models, at different acquisition times, with different quality characteristics or at different scales. This situation will become intensified when more and more digital spatial data are offered by using internet technologies. Integration methods are needed to take advantage of the characteristics of more than one data set. These advantages could be, for example, new applications for which the data models had not been originally designed, higher reusability, improvement of the quality, or cost minimization of data acquisition. In this paper a relational matching approach for integration of spatial data from different sources is introduced. The research work was performed on street centrelines which were captured in different data models. The approach is based on statistical investigations between the data of two data models, and can be ...

Linking Objects of Different Spatial Data Sets by Integration and Aggregation

In order to solve spatial analysis problems, nowadays a huge amount of digital data sets can be accessed: cadastral, topographic, geologic, and environmental data, in addition to all kinds of other types of thematic information. In order to fully exploit and combine the advantages of each data set, they have to be integrated. This integration has to be established at an object level leading to a multiple representation scheme. Depending on the type of data sets involved, it can be achieved using different techniques.Such a linking has many benefits. First, it helps to limit redundancies and inconsistencies. Furthermore, it helps to take advantage of the characteristics of more than one data set and therefore greatly supports complex analysis processes. Also, it opens the way to integrated data and knowledge processing using whatever information and processes are available in a comprehensive manner. This is an issue currently addressed under the heading of ‘interoperability’.Linking has basically two aspects: on the one hand, the links characterize the correspondence between individual objects in two representations. On the other hand, the links also can carry information about the differences between the data sets and therefore have a procedural component, allowing the generation of a new data set based on given information (i.e., database generalization).In the paper three approaches for the linking of objects in different spatial data sets are described. The first defines the linking as a matching problem and aims at finding a correspondence between two data sets of similar scale. The two other approaches focus on the derivation of one representation from the other one, leading to an automatic generation of new digital data sets of lower resolution. All the approaches rely on methodologies and techniques from artificial intelligence, namely knowledge representation and processing, search procedures, and machine learning.

Comparison of the Potential of Different Sensors for an Automatic Approach for Change Detection in GIS Databases

This paper examines data from different sensors regarding their potential for an automatic change detection approach. After a brief discussion of the used approach, results are shown on examples of data from several sensors: scanned analogue aerial photos, an airborne digital line scanner (DPA camera system), the Indian satellite IRS-1C, the MOMS-2P camera and from a laser scanning system as an additional information source. The GIS data which have to be updated are from the German national topographic cartographic database (ATKIS) and were captured in the scale of 1 : 25,000.

Automatic Map Retrieval and Map Interpretation in the Internet

The Internet contains huge amounts of maps representing almost every part of the Earth in many different scales and map types. However, this enormous quantity of information is completely unstructured and it is very difficult to find a map of a specific area and with certain content, because the map content is not accessible by search engines in the same way as web pages. However, searching with search engines is at the moment the most effective way to retrieve information in the Internet and without search engines most information would not be findable. In order to overcome this problem, methods are needed to search automatically for maps in the Internet and to make the implicit information of maps explicit so that machines can process it. In this paper we discuss how maps can be found automatically in the Internet and moreover, how the content of maps can be interpreted automatically.

Automated revsion of GIS databases

Digital spatial data are underlying strong temporal changes. The typical approach of updating these changes is to check the data manually for their correctness by superimposing them on up-to-date orthophotos. The update cycles of large data sets are in the range of several years. At present shorter update cycles are unrealizable for two reasons. The manual inspection of the data is very cost- and time-consuming and aerial photographs for large areas are very often not available in the needed time intervals. However, a decisive turn can be seen in data availability. With new satellite systems, it will be possible to provide up-to-date high resolution orthophotos in short time periods and high quality in the near future. At September 24th, 1999, the optical high resolution satellite IKONOS, developed by the company Space Imaging (http://www.spaceimaging.com), was brought successfully into orbit. Further systems as for example Quickbird of the company EarthWatch, OrbView 3 and 4 of the company ORBIMAGE or EROS A and B of the company West Indian Space will follow shortly (see also [9, 10]). The data which will be delivered from these new satellite systems will close the gap between existing medium resolution satellite data (as for example Spot, Landsat or IRS-1C) and very high resolution data from airborne systems. In near future users will be able to select images from several providers to use them for their mapping tasks. In order to eliminate the still existing bottle-neck of manual updating of GIS data, the Institute of Photogrammetry (ifp), University of Stuttgart developed a software package which is presented in this article.

Modeling Concepts for Consistency Analysis of Multiple Representations and Heterogeneous 3D Geodata

In a dynamic world where the steadily increasing demand for up-to-date geodata drives the continuous acquisition of three-dimensional (3D) data, appropriate systems for managing and analyzing the resulting data become more and more important. Efficient solutions for handling multiple representations and data heterogeneity are of special significance. Existing geoinformation systems are still not able to cope with the huge diversity of geodata. Available approaches and systems that apply merging processes in order to generate one single representation for each real-world object are not practicable any more. Thus, our goal is a hybrid 3D geoinformation system that allows for integrated management of heterogeneous and multiply-represented geodata. Our concept is hybrid with respect to data given in different data models, dimensions, and quality levels. Multiple representations and data inconsistency can be handled through the explicit modeling of geometric correspondences.